Abstract:
This presentation describes an effective algorithm for optimizing distribution system
operation in a smart grid, from cost and system stability points of view. The proposed algorithm
mainly aims at controlling the power available from different sources such that they satisfy the
load demand with the least possible cost while giving the highest priority to renewable energy
sources. Moreover, a smart battery charger was designed to control the batteries in such a way
that they are allowed to discharge only when there is no very big load predicted within an
immediate future period. This will make such a storage available to act as a buffer for the
predicted large load to increase the stability of the system and reduce voltage dips. In addition,
batteries are used to serve another purpose from an economic point of view, which is peak shifting
during the day in order to avoid the relatively high prices of grid power during peak
periods. Since this algorithm is mainly dependent on forecasted data of the power available from
different renewable energy sources as well as the load demand, a full attention has been paid to
the forecasting process. Hence, a non-linear regression technique was applied to build accurate
forecasting models for different sources and for the load. These models help in monitoring and
predicting the total power generation and demand online. Furthermore, a fuzzy controller was
utilized to make use of the forecasted data of the coming peak period then decide dynamically
the amount of power that should be taken out of energy storage. Different case studies were
investigated to verify the validity of the proposed algorithm and define the system behavior
under several conditions.
The presentation will also describe efforts currently underway on the development of a
wide area measurement (WAMS) system for smart grid applications. This system is based on
synchronized phasor measurement technology with the access of a broadband communication
capability. The purpose is to increase the overall system efficiency and reliability for all power
stages via significant dependence on WAMS as distributed intelligence agents with improved
monitoring, protection, and control capabilities of the power network. An example of consisting
of a 50 kW generation station, 20 kW wind turbine, three transformers, four circuit breakers, four
buses, two short transmission lines, and two 30 kW loads is presented. The communication layer
consists of three PMUs, located at generation and load buses, and one Phasor data concentrator
(PDC) collecting the data received from remote PMUs and send it to the control center for
analysis and control actions. The power system status can be easily monitored and controlled in
real time by using the measured bus values online which improves the overall system reliability
and avoids cascaded blackout during fault occurrence. The simulation results confirm the
validity of the proposed WAMS technology for smart grid applications.
Bio: Dr. Osama A. Mohammed received his M.S. and Ph.D. degrees in Electrical
Engineering from Virginia Tech He is currently a Professor of Electrical
Engineering at Florida International University. He has more than 30 years of
teaching, research and industrial consulting experience. He authored and coauthored
more than 300 technical papers in the archival literature and in National
and International Conference records in addition to several book Chapters and
numerous technical and project reports.
Professor Mohammed specializes in Electrical Energy Systems especially in
areas related to alternate and renewable energy systems and smart grid applications.
He is also interested in design optimization of electromagnetic devices, Artificial
Intelligence Applications to Energy Systems as well as Electromagnetic Field
Computations in Nonlinear Systems for these energy system applications. He has current interest in
Shipboard power systems and integrated motor drives. Dr. Mohammed has been successful in obtaining a
number of research contracts and grants from industries and Federal government agencies. He has a
current active and funded research programs in several areas funded by the office of Naval Research and
the US Department of Energy.
Professor Mohammed is a Fellow of IEEE and is a Fellow of the Applied Computational
Electromagnetic Society. He is an Editor of IEEE Transactions on Energy Conversion, IEEE Transactions
on Magnetics, Power Engineering Letters and also an Editor of COMPEL.
He received many awards for excellence in research, teaching and service to the profession. Professor
Mohammed has been General Chair of several major IEEE conferences including, IEEE IEMDC, IEEE
CEFC, IEEE ISAP and the COMPUMAG Conferences.
Professor Mohammed was the chair of the IEEE PES Electric Machinery Committee and was a
member of the PES Governing Board and the Chair of the PES Constitution and Bylaws Committee. He
is currently the Chair of the International Steering Committee for IEEE IEMDC conference and the IEEE
CEFC Conference and is a member of several other PES committees subcommittees and working groups.
July 20, 2011, Wed, 10:00-11:30, CNLS conference room [student seminar]:
Yunjian Xu (MIT)
Cournot oligopoly and PHEV scheduling
and Scheduling Problems
Abstract:
The first part of the talk is devoted to a research topic I conducted last year. We consider a Cournot oligopoly model where multiple suppliers (oligopolists) compete by choosing quantities. We compare the social welfare achieved at a Cournot equilibrium to the maximum possible, for the case where the inverse market demand function is convex. We establish a lower bound on the efficiency of Cournot equilibria in terms of a scalar parameter extracted from the inverse demand function.
Through the methodology used in our social welfare analysis, we then construct a framework to compare the social welfare, consumer surplus, and supplier profit realized at a Cournot Equilibrium (CE), a Social Optimum (SO) where the social welfare is maximized, and a Monopoly Output (MO) where the aggregate profit of suppliers is maximized. We derive a lower bound on the ratio of the aggregate profit earned by all suppliers at a CE to the maximum possible aggregate profit, that is, the profit that would have been achieved if the suppliers were to collude at a MO. Our results provide nontrivial quantitative bounds on the loss of social welfare and aggregate profit for several inverse demand functions that appear in the economics literature.
In the second part of the talk, we study the scheduling problem for PHEVs to maximize social welfare. If the decision is made by a centralized operator, the centralized PHEV scheduling problem can be formulated as a dynamic programming problem. The difficulty of solving the formulated dynamic programming problem is that the state space grows exponentially with the number of vehicles. The issue on computation complexity can be addressed through an approximate dynamic programming approach. We use limited look ahead policies where the heuristics can be obtained through greedy algorithms, or by solving a simplified dynamic programming problem with an aggregated state space. For the case where each vehicle makes its decision to maximize its own benefit, we construct a dynamic game theoretical model to study the decentralized PHEV scheduling problem.
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July 19, 2011, Tue, 10:30-12:00:
Prof. Zhihua Qu (University of Central Florida)
Distributed Optimization, Control and Dynamic Game Algorithms for Transmission Network and Self-Organizing Distribution Networks in Smart Grids
Abstract:
It is well recognized that distributed energy sources such as solar and wind are intermittent, that their presence will shift the operation of power system from the current mode of regulated utilities to a competitive generation provision, and that a high penetration level of these sources demands new regimes of measurement and estimation, communication, control, protection, security, and operation. On the other hand, contemporary sensing and communication networks enable real-time collection and subscription of geographically-distributed information and such information can be used to significantly enhance the performance of electric power systems at the levels of generation, transmission and distribution. Through a shared sensing/communication network, distributed generation can now be controlled to operate autonomously and robustly as micro grids, and operation of these micro grids can exhibit cooperative behaviors to enhance voltage stability of distribution networks. By incorporating dynamic game and cooperative control algorithms, pooled generation/consumption of micro-grids can be automatically optimized to enhance both energy dispatch and transient stability of the overall power system.
The talk illustrates analysis and design tools for the so-called cooperative networked systems among which information exchanges are local and intermittent, their changing patterns are not known a priori, and may have significant latencies. Canonical forms and designs of distributed cooperative control are introduced to ensure cooperative stability and design cooperative control for networked linear and nonlinear systems. Formulations and distributed algorithms of estimation, optimization and dynamic games are also illustrated.
Based on these methodologies and tools, innovative algorithms of distributed control and optimization can be implemented to enable robust, intelligent and efficient operations for power systems with distributed and intermittent power generation sources. As an illustration, the following three-layered control-optimization-control structure is discussed: (i) A cooperative control algorithm that enables micro-grids to form autonomously and to evolve as distributed generation changes over time; (ii) Each of the self-evolving micro-grids negotiates with the main grid to determine the best operating conditions by following the incentive (and limit) specified by the main grid and by maximizing the group energy output; and (iii) In the event of a major disturbance or fault, distributed generations and their inverter-based controls provide transient controls that maintain voltage stability of distribution networks; (iv) Dynamic game algorithms enable multi-level optimization that improves both energy dispatch and transient stability of the overall power system. Sample results from the on-going DoE SEGIS and NSF projects will be presented to illustrate their effectiveness.
Bio:
Dr. Qu received his Ph.D. degree in Electrical Engineering at the Georgia Institute of Technology in June 1990. Since then, he has been with the University of Central Florida and is currently the SAIC Endowed Professor at UCF and a Professor of Electrical Engineering. Dr. Qu's areas of expertise are nonlinear systems and control, energy and power systems, and robotics. His recent research activities in controls have been cooperative control of heterogeneous dynamical systems as well as control of nonholonomic systems. In energy systems, his current research covers such subjects as dynamic stability of distributed power systems, anti-islanding control and protection, distributed generation and load sharing control, distributed VAR compensation, and distributed optimization. Dr. Qu is the author of three books: Robust Tracking Control of Robot Manipulators by IEEE Press (1996), Robust Control of Nonlinear Uncertain Systems by John Wiley & Sons (1998), and Cooperative Control of Dynamical Systems with Applications to Autonomous Vehicles by Springer Verlag (2009). His research has been supported by governmental agencies (NSF, Army, AFOSR, ONR, NASA, Oak Ridge, DoE) and industry (Lockheed, L-3, SAIC). Dr. Qu is a Fellow of IEEE, and is serving or served on Board of Governors of IEEE Control Systems Society and as Associate Editor for Automatica, IEEE Transactions on Automatic Control, and International Journal of Robotics and Automation.
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July 12, 2011, Wed, 10:00-11:30, CNLS conference room [student seminar]:
Sarah G. Nurre (Rensselaer Polytechnic Institute)
Solution Methodologies for Integrated Network Design
and Scheduling Problems
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Abstract:
We discuss solution techniques for the new class of Integrated Network Design
and Scheduling problems. Motivating applications for this problem class include
infrastructure restoration after an extreme event and plug-in hybrid electric
vehicle (PHEV) battery charging and discharging within a smart grid.
Infrastructures, such as power grids and transportation systems, can be modeled
as networks. Network managers must coordinate repairs or operational decisions
using limited resources in order to maximize performance. Selecting which
components to repair or utilize (i.e. downed power lines) can be viewed as
network design decisions. Traditional network design decisions only focus on the
end performance of the design, i.e., the network operation after all components
are repaired. Clearly, in infrastructure restoration the success of the efforts
depend on how well the services come back online. Therefore, it is important to
allocate resources, such as work groups, to implement network design decisions.
This resource allocation can be viewed as scheduling decisions. This novel
model incorporating the combination of decisions occurring simultaneously does
increase the problem difficulty, which motivates the need for both exact and
approximate solution methods. I will present complexity results on the problem
class under standard network performance metrics, exact and approximate solution
methods, and case studies based on real-life data sets representing the
infrastructure systems of lower Manhattan and New Hanover county, NC.
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June 22, 2011, Wed, 10:00-11:30, CNLS conference room [student seminar]:
K. Dvijotham (U of Washington)
Operations-Based Planning for Placement and Sizing of
Energy Storage in a Grid With a High Penetration of
Renewables
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Abstract:
As the penetration level of transmission-scale time-intermittent renewable generation resources increases, control of flexible resources will become important to mitigating the fluctuations due to these new renewable resources. Flexible resources may include new or existing synchronous generators as well as new energy storage devices. The addition of energy storage, if needed, should be done optimally to minimize the integration cost of renewable resources, however, optimal placement and sizing of energy storage is a difficult optimization problem. The fidelity of such results may be questionable because optimal planning procedures typically do not consider the effect of the time dynamics of operations and controls. Here, we use an optimal energy storage control algorithm to develop a heuristic procedure for energy storage placement and sizing. We generate many instances of intermittent generation time profiles and allow the control algorithm access to unlimited amounts of storage, both energy and power, at all nodes. Based on the activity of the storage at each node, we restrict the number of storage node in a staged procedure seeking the minimum number of storage nodes and total network storage that can still mitigate the effects of renewable fluctuations on network constraints. The quality of the heuristic is explored by comparing our results to seemingly "intuitive" placements of storage. Joint work with S. Backhaus and M. Chertkov.
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June 20, 2011, Mon, 10:00-11:30, T-DO conference room [Notice Special Date, Time Span and Place!!]:
Prof. Alejandro D. Dominguez-Garcia (Urbana Champaign)
Coordination and Control of Distributed Energy Resources for Provision of Ancillary Services
Abstract:
On the distribution side of a power system, there exist many distributed energy resources (DERs) that can be potentially used to provide ancillary services to the grid they are connected to. An example is the utilization of power electronics grid interfaces commonly used in distributed generation to provide reactive power support. While the primary function of these power electronics-based systems is to control active power flow, when properly controlled, they can also be used to provide reactive power support. Another example is the utilization of plug-in-hybrid vehicles (PHEV) for providing active power for up and down regulation. For instance, such resources could be utilized for energy peak-shaving during peak hours and load-leveling at night. Proper coordination and control of DERs is key for enabling their utilization for ancillary services provision. One solution to this problem can be achieved through a centralized control strategy where each DER is commanded from a central controller located, for example, at the substation that interconnects the distribution network and the transmission/subtransmission network. In this talk, we propose an alternative approach to this centralized control.
The alternative approach rely on a distributed control strategy where each DER can exchange information with a number of other ``close-by" DERs, and subsequently make a local control decision based on this available information. Collectively, the local control decisions made by the DERs should have the same effect as the centralized control strategy. Such a solution could rely on inexpensive and simple communication protocols, e.g., ZigBee technology, that would provide the required local exchange of information for the distributed control approach to work. We provide algorithms that solve this coordination/cooperation problem when i) there is no limit on the amount of active or reactive power that each DER can provide (though some notion of fair distribution of the contribution of active or reactive power among DERs might be imposed); and ii) the maximum amount of active or reactive power each DER can provide is limited, which is a more realistic case. We will provide a careful analysis of the applicability capabilities and limitations of each of these strategies.
Speaker's bio:
Alejandro Dominguez-Garcia is an Assistant Professor in the Electrical and Computer Engineering Department at the University of Illinois, Urbana, where he is affiliated with the Power and Energy Systems area. His research interests lie at the interface of system reliability theory and control, with special emphasis on applications to electric power systems and power electronics.
Dr. Dominguez-Garcia received the Ph.D. degree in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology, Cambridge, MA, in 2007 and the degree of Electrical Engineer from the University of Oviedo (Spain) in 2001.
After finishing the Ph.D., he spent some time as a post-doctoral research associate at the Laboratory for Electromagnetic and Electronic Systems of the Massachusetts Institute of Technology. Prior to joining MIT as a graduate student, Dr. Dominguez-Garcia was with the Department of Electrical Engineering of the University of Oviedo where he held the position of Assistant Professor. Dr. Dom\'{i}nguez-Garc\'{i}a received the NSF CAREER Award in 2010.
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June 09, 2011, Wed, 10:00-11:30, CNLS conference room [First presentation of our ``student" seminar this summer]:
Florian Dörfler (UCSB)
Synchronization and Kron Reduction in Power Networks
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Abstract:
We discuss the modeling and synchronization problem for structure-preserving power
system models with either frequency-dependent or linear load models. The latter
load model leads to the network-reduced model of the generator swing dynamics. We
exploit the relationship between the considered power network models and the
well-known Kuramoto model of coupled oscillators. Extending methods from transient
stability analysis, synchronization theory, and consensus protocols, we establish
static synchronization conditions for the dynamic power network and
coupled-oscillator models. First, we focus on a network of coupled first-order
Kuramoto oscillators and derive purely algebraic conditions for synchronization. Our
conditions are necessary and sufficient for a complete and homogeneous network, they
are sufficient for a topological network with heterogeneous coupling, and they
improve upon previously-available tests for the Kuramoto model. Second, we discuss
the extension of these synchronization conditions to the second-order
coupled-oscillator models arising in power networks. This extension from first-order
to second-order dynamics can be made rigorous by means of topological conjugacy
arguments, by a singular perturbation analysis, or by strict-mechanical Lyapunov
functions. In the end, we are able to state concise and purely algebraic conditions
that relate synchronization in a power network to the underlying network state,
parameters, and topology. Third, we analyze the network-reduction process relating
the network-reduced and the more detailed structure-preserving power system model.
The network reduction process, termed Kron reduction, is characterized by iterative
Schur complementation of the admittance matrix. A detailed algebraic and
graph-theoretic analysis of the Kron reduction process allows us to extend the
synchronization conditions obtained for the network-reduced model to the
structure-preserving model. In the end, we are able to state one spectral and one
resistance-based condition for synchronization. Time permitting, we briefly touch
upon other networked-control approaches to power network problems.
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May 10, 2011, Tue, 10:30-12:00:
Prof. Le Xie (Texas A & M)
Distributed Look-ahead Coordination of Intermittent Resources and Storage in Electric Energy Systems
Abstract:
The major subject of this talk is the introduction and testing of a new operating paradigm necessary for sustainable performance of the changing electric power industry. We first show that it is very difficult with today's software tools to balance power system supply and demand with large amount of variable resources due to their hard-to-forecast nature. This creates the need for fundamentally new algorithms in support of short-term forecast and flexible operation. We then propose a distributed look-ahead dispatch concept, which leverages (1) the near-term forecasts of intermittent wind generation, (2) flexibility in price responsive demand, and (3) the storage capabilities such as Plug-in Hybrid Electric Vehicles to participate into real-time energy balancing and frequency regulation services. Through an IEEE Reliability Test System example, we show that the proposed dispatch will lead to an overall cost-effective and environmentally benign utilization of the electric energy system portfolio in electricity markets. The proposed approach provides a theoretical framework for systematic integration of sustainable energy resources, such as wind and solar, with quantifiable performances.
Bio: Le Xie is an Assistant Professor in the Department of Electrical and Computer Engineering at Texas A&M University, College Station, Texas, where he is affiliated with the Electric Power and Power Electronic Group. He received his B.E. in Electrical Engineering from Tsinghua University, Beijing, China in 2004. He received S.M. in Engineering Sciences from Harvard University in June 2005. He obtained his Ph.D. from Electric Energy Systems Group (EESG) in the Department of Electrical and Computer Engineering at Carnegie Mellon University in 2009. His industry experience includes an internship in 2006 at ISO-New England and an internship at Edison Mission Energy Marketing and Trading in 2007. His research interest includes modeling and control of large-scale complex systems, smart grid applications in support of variable energy integration, and electricity markets. He also serves as the founding faculty advisor to Texas A&M Energy Club, a university-wide student-run organization focusing on energy.
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May 2, 2011, Mon, 10:30-12:00 [Notice Special Date !!]:
Prof. Alla Kammerdiner (NMSU)
Neighborhood structures for solving the problem of transmission network expansion planning
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Abstract:
The goal of the transmission network expansion planning (TNEP) is to determine the optimal plan for power grid expansion. The plan must specify the number of new power lines to be installed in each transmission corridors and the number of new control components added at each bus. The problem of long-term transmission system planning based on the so-called DC model is considered. Due to constraints imposed by physical laws of the power flows, the resulting optimization problem is a nonlinear mixed-integer problem (NLMIP) with high complexity, especially for large-scale and real-world problems. Many of the solution algorithms for TNEP problem are constructive heuristics that are developed based on specific (approximate) models of power flows. The goal is to develop adaptive optimization algorithms that can be applied for solving TNEP for a wide variety of power models. Inspired by recent metaheuristics, such as the variable neighborhood search (VNS) and the iterated local search (ILS), several neighborhood structures on the TNEP problem solution space are investigated.
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April 26, 2011, Tue, 10:30-12:00:
Robert Carrington, Amelia Musselman and Mark Wilson
2010-11 Math Clinic Team
Claremont Graduate University
A Hybrid Optimization Approach for Power Grid Design
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Abstract:
As the transfer from non-renewable to renewable energy resources has become
increasingly widespread, certain assumptions regarding power grid efficiency
have changed. Power generators have become cheaper to build and install,
but may be situated large distances from demand, as for instance in the
case of wind power. We consider the problem of optimal transmission line
placement and conductance assignment, given the combined costs of resistive
power loss and line construction. We adopt the DC model of Johnson and
Chertkov, with a single generator and multiple loads, all at known locations.
Transmission line construction costs are made up of a fixed cost for each
line present, as well as variable costs proportional to each line's conductance,
leading to a nonconvex optimization problem. We have developed a novel
two-part discrete and continuous hybrid algorithm for this problem. The
discrete method, genetic algorithms, is used to sample over the space of
grid topologies. As the topologies are sampled, they are sent to a continuous
optimization procedure that uses Newton's method to determines the optimal
line conductance values for a related convex optimization problem. We have
studied, implemented and tested this hybrid algorithm, obtaining results
compatible with those of Johnson and Chertkov. We will discuss possible
modifications to the algorithm that may improve upon these results.
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April 18, 2011, Mon, 10:30-12:00 [Notice Special Date !!]:
Dr. Lijun Chen (Caltech)
Market models and algorithmic design for demand response in power networks
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Abstract:
Demand side management will be a key component of future smart grid that can help reduce peak load and adapt elastic demand to fluctuating generations. In this talk, after a briefly review of the motivation and the main issues in demand response design, we will first discuss an abstract market model for designing demand response to match power supply. We characterize the resulting equilibria in competitive as well as oligopolistic markets, and propose distributed demand response algorithms to achieve the equilibria. We then discuss another market model for designing demand response to shape power demand. We consider households that operate different appliances including PHEVs and batteries and propose a demand response approach based on utility maximization. Each appliance provides a certain benefit depending on the pattern or volume of power it consumes. Each household wishes to optimally schedule its power consumption so as to maximize its individual net benefit subject to various consumption and power flow constraints. We show that there exist time-varying prices that can align individual optimality with social optimality, i.e., under such prices, when the households selfishly optimize their own benefits, they automatically also maximize the social welfare. The utility company can thus use dynamic pricing to coordinate demand responses to the benefit of the overall system. We propose a distributed algorithm for the utility company and the customers to jointly compute these optimal prices and demand schedules. Numerical experiments show that it is effective in reducing the peak load, smoothing the entire demand profile, and saving significant generation costs.
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April 12, 2011, Tue, 10:30-12:00:
Prof. Zeb Tate (U of Toronto)
Estimating and Visualizing the Impact of Forecast Errors on System Operations
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Abstract:
As significant variable generation is added to the power grid, operators have to make decisions in the presence of power output uncertainties at multiple locations throughout the network. The cumulative effects of all the uncertainties on the system are non-obvious, and incorrect assessment of the cumulative effect could affect the reliability and stability of the power system. This paper proposes a method of combining confidence intervals of short term (one to eight hours ahead) wind forecast errors with the existing unit commitment on the system to determine possible operational impacts. The output is a visualization that can alert system operators to the potential for transmission line overloads and indicate whether changes to the existing commitment schedule should be considered. In addition, a modified confidence interval estimation method has been developed that, based on simulation results, outperforms existing methods for short term wind forecasts.
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March 1, 2011, Tue, 10:30-12:00:
Prof. Igor Mezic (UCSB)
Smart Grid and Analysis of Large-Scale Interconnected Dynamical Systems
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Abstract:
In 2003 blackout in the large portion of the eastern national power grid an environmental uncertainty - falling of a tree branch on a power line -caused a disturbance that propagated dynamically at a rapid pace through the grid causing one power plant after another to fail. The possibility of such events occurring frequently becomes large when one starts thinking about the scenario of a power grid with subcomponents providing wildly fluctuating amounts of power and storage capacity as would be the case if current thinking on the issues such as co-generation and alternative power sources plays a substantial role in the future power generation network. We are interested in elucidating core causes of instabilities leading to large disturbances and failure of catastrophic proportions. It turns out that it is the coupling of architecture and dynamics of the system that matter the most. If two parts of the system are completely separated from each other, a big disturbance in one will, of course, not influence the other. But, if the subsystems are connected, even weakly, and the dynamics is resonant, a small disturbance in one subsystem can grow, spill to the other part and cause the whole system to fail. This is true even if there are controls in place attempting to stabilize one side - the phenomenon is of the emergent kind, and the only way to control it is to act early at the root cause or provide system-wide regulation that prevents catastrophes. I will discuss the technical aspects of this phenomenon that in the context of power grid we named a "Coherent Swing Instability" (CSI). A simple ring architecture will be presented first, followed by more complex New England Grid model. In order to treat such more complex, large-scale models, we needed to develop new tools, drawing from an operator-theoretic point of view, that also incorporates, in a strong way, the geometric point of view that is so fruitful in low dimensions. This approach leads to a new proposal for model reduction that is rooted in the dynamics of the system rather than in energy-minimization arguments (like in POD). We named the modes that appear in such reduction the "Koopman modes". I will show how this leads to extraction of single-frequency, spatial modes embedded in non-stationary data of short-term,nonlinear swing dynamics, and provides a novel technique for identification of coherent swings and machines. In addition, I will present a technique for identifying CSI by using Koopman modes, by providing a precursor signal based on their interaction. The set of techniques that we have developed also enables analysis of uncertain and stochastic systems - where initial conditions and/or parameter values are not known exactly - within the same framework. Most of the tools apply equally to discontinuous systems.
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Feb 22, 2011, Tue, 10:30-12:00:
Prof. Hsiao-Dong Chiang (Cornell)
On-Line Transient Stability Assessments and Control of PJM Power Systems:
Methodology and Evaluations
Abstract:
For many utilities around the world, there has been
considerable pressure to increase power flows over existing
transmission corridors, partly due to economic incentives (a
trend towards deregulation and competition) and partly due
to practical difficulties of obtaining authorization to build
power plants and transmission lines (environmental
concerns). This consistent pressure has prompted the
requirement for extending EMS to take account of dynamic
security assessment (DSA) and control. Such extension,
however, is a rather difficult task and requires several breakthroughs
in measurement systems, analysis tools,
computation methods and control schemes.
Indeed, on-line DSA, concerned with power system
stability/instability after contingencies, requires the handling
of a large set of nonlinear differential equations in addition
to the nonlinear algebraic equations involved in the static
security assessment. The computational efforts required in
on-line DSA is roughly three magnitudes higher than that for
the SSA (static security assessment). This explains why
dynamic security assessment and control has long remained
in off-line activity. Hence, current power system operating
environments have prompted the need to significantly
enhance time-domain stability analysis programs to meet
new requirements. In addition, it is becoming advantageous
to move transient stability analysis from the off-line
planning area into the on-line operating environment. There
are significant financial benefits expected from this
movement. It appears that there is always significant
incentive to find superior approaches for stability analysis
and control.
The PJM Interconnection has successfully designed and
implemented a Transient Stability Analysis & Control
(TSA&C) system at its energy management system (EMS).
EMS provides a real time snapshot including power flow
case data from the state estimator, dynamic data and
contingency list to the TSA&C application. For each real
time snapshot, TSA&C performed a transient stability
assessment against the list of 3000 contingencies, calculated
stability limits on key transfer interfaces.
TEPCO-BCU was selected as the leading fast screening
tool for improving the performance of the PJM TSA system.
The TEPCO-BCU software was evaluated for three months
in the PJM TSA Test System environment. The three-month
evaluation period was chosen to include the scheduled
outage season and the summer peak load season. This period
historically encountered a wide range of real time scenarios
that can happen on the PJM power system. During this
evaluation period, both the PJM TSA software and the
TEPCO-BCU software were run periodically in parallel,
every 15 minutes in the PJM TSA Test System environment.
The goal was to evaluate TEPCO-BCU in a real time
environment as a transient stability analysis screening tool.
This talk will present a comprehensive evaluation of the
dynamic contingency screening function of TEPCO-BCU
and an overview of the solution methodologies behind
TEPCO-BCU. Requirements for an on-line screening and
ranking tool for PJM systems are presented and evaluated.
This evaluation study is the largest in terms of system size,
14,500-bus, 3000 generators, for a practical application of
direct methods. The total number of contingencies involved
in this evaluation is about 5.3 million.
The integrated package TEPCO-BCU is based on the
theory of the controlling UEP method, BCU method, energy
function method and BCU-guided time-domain method The
controlling UEP method and the boundary of stabilityregion-
based controlling UEP (BCU) method will be
described at a level sufficient to comprehend the concept of
a transient-stability screening program for TSA systems.
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Feb 15, 2011, Tue, 10:30-12:00:
Prof. Patrick McDaniel and
Stephen McLaughlin (Penn State)
Security and Privacy Issues in Smart Electric Meters
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Abstract:
Smart electric meters are arguably the most well developed aspect of the smart grid to date. With increased economic stimulus for smart grid pilots and new vendors constantly entering the market, smart meters are poised to become ubiquitous within the decade. As with any emerging system, their security should be well understood at both the architectural and implementation levels before standardization and deployment ramp up. We present a first step in this direction through the use of systematic penetration testing to discover security and privacy problems in commercially available smart meters. To address the challenges of pen-testing a diverse set of metering equipment, we use attack trees to reason about potential architectural and implementation flaws in smart meters. Our results show basic shortcomings in the security of metering systems from two different vendors.
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Jan 12, 2011, Tue, 10:30-12:00:
Prof. Aranya Chakrabortty (North Carolina State U)
A Network-Theoretic Approach for Wide-area Modeling and Control of Large Power Systems using Distributed
Synchrophasors
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Abstract:
Recent advances in the wide-area measurement system (WAMS) technology using phasor measurement units (PMU) have given a new impetus to control-oriented research in large-scale electric power systems. One of the main challenges in the dynamic analysis and control of power systems is the development of analytical tools from limited measurement data. In this talk I will address this problem and develop methods for model identification, dynamic stability assessment and controller designs for large power systems using PMU measurements. The discussion will be broadly divided into two parts. In Part-1, I'll present several novel coherency-based algorithms for constructing dynamic equivalents of different classes of radial power systems, with and without intermediate voltage control. In Part-2, I'll address the application of these equivalent models in wide-area monitoring and distributed damping control of multi-machine power systems using a novel control inversion approach. A brief note on how PMU's should be placed optimally in the network for generating the most accurate control strategies, especially when the PMU data are noisy and unreliable, will also be discussed. The overall motivation of the talk would be to understand how the WAMS technology can help us in gaining valuable insight about the physical behavior of the North American grid, which is becoming more expansive, and, hence, more chaotic day by day.
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Dec 14, 2010, Tue, 10:30-12:00:
Prof. Claudio Canizares (U of Waterloo)
Stability-constrained Optimal Power Flows and Their Applications to Electricity Markets
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Abstract:
This talk will concentrate on presenting and discussing various novel methodologies for the inclusion of stability constraints in optimal power flow (OPF) models to better represent power system security in OPF applications. Comparisons of the proposed methods with respect to classical security constrained OPF techniques typically used in energy auctions will be presented, concentrating on discussing the effect that the proposed new models can have on electricity prices as well as system security in the context of competitive electricity markets.
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Dec 7, 2010, Tue, 10:30-12:00:
Prof. Mladen Kezunovic (Texas A & M)
The Smart Grid Data “Explosion”: Translational Knowledge Challenge
Abstract:
The smart grid efforts are focused, among other tasks, on getting better use
of abundant data coming from substations, feeders/transmission lines, loads and
generators equipped with advanced intelligent electronic devices (IEDs) such as
digital protective relays, digital fault recorders, remote terminal units of SCADA,
phasor measurement units, smart meters, equipment monitors, etc. As the
amount of the smart grid data increases in the future, it becomes critical that the
data integration and conversion to information be performed automatically. A
major challenge remains to convert information into actionable knowledge. This
requires full understanding of the cause-effect relationship between data and
knowledge, often termed “Translational Knowledge”. This lecture focuses on
better understanding the features of the data recording issues such as front-end
data processing, accuracy, time synchronization, and eventually the conversion
of data to information. Several smart grid applications enabled by the
translational knowledge approach are discussed and open issues are mentioned.
[slides of the first part of Prof. Kezunovic presentation on ``Smart Energy Center at TAMU".]
Bio:
Dr. Mladen Kezunovic is a Professor at the Department of
Electrical and Computer Engineering at Texas A&M University
(TAMU) and holds the Eugene E. Webb Endowed Professorship.
He worked for Westinghouse Electric in the U.S.A. as a
Systems Engineer on development of the first all-digital
substation during 1979-1980 and for Energoinvest Company in
Europe as the Technical Lead for substation automation
development during 1980-86. He also spent sabbaticals at EdF’s Research
Centre in Clamart, France in 1999/2000 and at the University of Hong Kong in
the fall of 2007. Dr. Kezunovic served as a consultant to over 50 utilities and
vendors worldwide. He is TAMU Site Director of the Power Systems Engineering
Research Center (PSerc), and Deputy Director of the PHEV/BEV Center for
Transportation and Electricity Convergence (CTEC), both Industry/University
Cooperative Research Centers (I/UCRCs) of the National Science Foundation.
Dr. Kezunovic acted as a PI on close to 100 R&D projects covering
analysis of faults and other disturbances. His current research activity includes
new concepts for substation automation, new approaches to condition-based
asset management, and new applications in relaying and control.
Dr. Kezunovic has published more than 400 journal and conference papers
and has given over 100 invited lectures, short courses and seminars around the
world. He is a Fellow of the IEEE and a member of CIGRE-Paris. He is a
registered Professional Engineer in the State of Texas. Dr. Kezunovic is listed as
the IEEE Distinguished Speaker.
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Nov 23, 2010, Tue, 10:30-12:00:
Dr. Annarita Giani (UC Berkeley)
Wide Area Monitoring System Security
Abstract:
A wide area measurement system (WAMS) consists of advanced measurement technology, information tools, and operational infrastructure that facilitate the understanding and management of the increasingly complex behavior exhibited by large power systems. Synchro-phasors or Phase Measurement Units (PMUs) are a technology that offers absolute time-stamped voltage phase measurements and even more detailed voltage profiles at buses in the electricity grid. The first WAMS was installed in 2000 by the Bonneville Power Administration. Only 200 PMUs are already installed in North America. In 2009, the U.S. government announced an investment of 3.4 B $ in energy grid modernization. This investment will include the installation of more than 850 PMUs that will monitor the complete U.S. electric grid.
Static-state estimation is a well-known and widely used technique for determining optimal estimates of phase angles ? from noisy real power P, reactive power Q, and voltage magnitude V measurements at generator and large substation buses. This technique permits monitoring the relative phase angles between adjacent generators. Large changes in phase angle between two generators is an early indicator of transient stability problems. Phasor Measurement Units sense the relative phase angle between generators directly and transmit them to a data aggregator. It is crucial to identify any attacks that change PMU measurements since PMU data is used directly and critically for monitoring the power system.
In this talk I will begin with a brief survey of cyber security for physical systems. I will then present a taxonomy of cyber-attacks on PMU systems. Following this, I will briefly review WAMS systems and applications. Then, I will present some preliminary research ideas on how to detect integrity attacks on the devices. These attack detection algorithms are based on checking for consistency of the [possibly] corrupted data against the underlying physical models that constrain the phase measurements. The consistency checks are based on static state estimation. I will offer some synthetic simulation results, and close with a discussion of computational and implementation issues that require further exploration.
Bio: Annarita received her Laurea (Master) degree in Mathematics from the Universitá di Pisa, Italy and a Ph.D in Computer Engineering at Thayer School of Engineering at Dartmouth College, Hanover, NH. There she participated to the Process Query System (PQS), project, sponsored by the Advanced Research and Development Activity (ARDA). She graduated with a dissertation on computer security, anomaly tracking and cognitive attacks. She is currently a postdoctoral fellow at the Department of Electrical Engineering and Computer Science at the University of California at Berkeley working with Professor Kameshwar Poolla and Professor Shankar Sastry. She is part of the Team for Research in Ubiquitous Secure Technology (TRUST) project, sponsored by the National Science Foundation, Science and Technology Center.
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Nov 2 , 2010, Tue, 10:30-12:00:
Prof. Manimaran Govindarasu (Iowa State University)
Cyber-Physical Systems Security of Power Grid: Risk Modeling and Mitigation
Abstract:
Critical infrastructures are complex physical and cyber-based systems that form the lifeline of modern society, and their reliable, secure, and safe operations are of paramount importance to national security and economic vitality. The electric power grid, one of the key critical infrastructures, is a highly automated network that uses a variety of sensors, information/control systems, and communication networks (collectively known as SCADA, EMS, WAMS, DMS) for the purpose of sensing, monitoring, and controlling the physical grid. The recent findings, as documented in federal reports and in the literature, indicate the growing threat of cyber-based attacks in numbers and sophistication on the nation's electric grid and other critical infrastructure systems. Therefore, cyber security of the power grid-encompassing attack prevention, detection, mitigation, and resilience-is among the most important research issues today and in the emerging smart grid.
This talk will provide a brief taxonomy of potential cyber attacks on the power grid, and present a cyber-physical systems framework for risk modeling and mitigation of cyber attacks on the power grid that accounts for dynamics of the physical system, as well as the operational aspects of the cyber-based control system. In particular, the talk will focus on risk modeling of intrusion-based attacks on the substation automation system and data integrity attacks on the wide-area control network. The core of the modeling lies in the integration of cyber attack/defense modeling with physical system simulation capabilities, which makes it possible to quantify the potential consequences of a cyber attack on the power grid in terms of load loss, stability violations, equipment damage, or economic loss. Finally, the talk will conclude with discussing the experience in building a SCADA cyber security testbed and its operational capabilities.
Biography:
Dr. Manimaran Govindarasu is currently an Associate Professor and Director for Student Professional Development in the Department of Electrical and Computer Engineering at Iowa State University; he also is affiliated to industry-funded Electric Power Research Center (EPRC) and NSF-funded Information Assurance Center (IAC) at Iowa State. He received his Ph.D. in Computer Science and Engineering from Indian Institute of Technology, Madras, India, in 1998 and joined Iowa State in 1999. At Iowa State, he received the Young Engineering Research Faculty Award in 2003 and the Outstanding Engineering Faculty Award in 2009. His research expertise is in the areas of real-time systems, cyber security, and cyber security of power grid. He has published over 100 peer-reviewed research papers of which 50 are in archival journals. He is co-author of the text "Resource Management in Real-Time Systems and Networks," MIT Press, 2001. He has given tutorials in reputed conferences and delivered industry short courses on the subject of cyber security. He has served in leadership roles in many IEEE conferences, symposiums, and workshops. He contributed to the DoE NASPInet Specification project, and is currently chairing the Cyber Security Task Force at IEEE Power and Energy Systems CAMS Subcommittee.
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Oct 5 , 2010, Tue, 10:30-12:00, Research Park
[Canceled]
:
NEDA (Japanese consortium collaborating with LANL & LA county) engineers visit
TBA
Sep 21 , 2010, Tue, 10:30-12:00:
Nandakishore Santhi, CCS-3
Analyzing Cascading Failures in Power Grids: Modeling and Data Challenges
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Abstract:
Large blackouts are usually the result of a cascade of failures of various components. A power grid being made of millions of components, occasionally a few of these components do not perform their function as desired putting additional burden on the working components, causing them to misbehave, and thus leading to a cascade of failures. The complexity of the power grid makes it difficult to model each and every individual component and study the stability of the entire system. We therefore construct an abstract model which is computationally tractable and a reasonable approximation to the power grid. We theoretically analyze this model and perform simulations which confirm the theory.
(Joint work with S. Kadloor)
Improvements to make the simulations much more realistic will be discussed. Reasonably good data on the transmission grid is needed to achieve further realism. I will talk about some of my recent attempts to gather openly available transmission grid data. The resulting incomplete data set is now available. Some results from analyzing the grid data (such as degree distributions/power-law) will be presented.
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Sep 14 , 2010, Tue, 14:00-15:30, T-DO conference room [Notice Special Time and Place!!]:
Prof. Paul Hines (U of Vermont)
Potential indicators of cascading failure risk in power systems
Abstract:
Cascading failures contribute disproportionately to power system blackout risk due
to the sizes of the blackouts that can result. Providing information to electricity
decision makers about risk is crucial for both real-time operations and long-term
decision making. This talk will discuss results from the analysis of two approaches
to blackout risk analysis in electric power systems. In the first analysis, we
compare two topological (graph-theoretic) methods for finding vulnerable locations
in a power grid, to a simple model of cascading outage. This comparison indicates
that topological models can lead to misleading conclusions about vulnerability. In
the second analysis, we describe preliminary results indicating that both a simple
dynamic power system model and frequency data from the August 10, 1996 disturbance
in North America show evidence of critical slowing down as the system approaches a
failure point. In both data sets, autocorrelation in the time-domain signals
(frequency and phase angle), significantly increases before reaching the critical
point. These results indicate that critical slowing down could be a useful indicator
of increased blackout risk.
Bio:
Paul Hines is an Assistant Professor in the School of Engineering at the University
of Vermont. He is also a member of the Carnegie Mellon Electricity Industry Center
Adjunct Research Faculty and a commissioner for the Burlington Electric Department.
He received the Ph.D. in Engineering and Public Policy from Carnegie Mellon U. in
2007 and the M.S. degree in Electrical Engineering from the U. of Washington in
2001. Formerly he worked at the US National Energy Technology Laboratory, where he
participated in Smart Grid research, the US Federal Energy Regulatory Commission,
where he studied interactions between nuclear power plants and power grids, Alstom
ESCA, where he developed load forecasting software, and for Black and Veatch, where
he worked on substation design projects. His main research interests are in the
areas of complex systems and networks, the control of cascading failures in power
systems and energy security policy.
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Sep 14 , 2010, Tue, 10:30-12:00, T-4 conference room
[Notice Special Place!!]
:
Prof. Thomas J. Overbye (Urbana)
Modeling and Simulation of a Renewable and Resilient Electric Power Grid
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Abstract: Electricity and the electric grid will play a crucial role in our transition to a sustainable energy infrastructure. Integrating a significant percentage of renewable energy sources into the nation's energy mix, and delivering it through electric transmission and distribution systems is a major research challenge since these sources are less controllable than the fossil-fuel-based generation they will displace. Simultaneous with these changes is the need to make the electric grid even more resilient in order to insure maximum continuity of electric service, even during severe system disturbances. This talk will focus on the modeling and simulation aspects of these problems.
[slides of WECC Frequency Contour for Opening Palo Verde 1 and 2
6 Seconds of Simulation]
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Aug 23 , 2010, Mon, 10:30-12:00 [Notice Special Date!!]:
Prof. Charles Meneveau (Johns Hopkins University)
Fluid mechanics and turbulence in the wind-turbine array boundary layer
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Abstract:
When wind turbines are deployed in large arrays, their ability to extract kinetic energy from the flow decreases due to complex interactions among them and the atmospheric boundary layer. In order to improve our understanding of the vertical transport of momentum and kinetic energy across a boundary layer flow with wind turbines, Large Eddy Simulations and wind-tunnel experimental studies are undertaken. A suite of LES, in which wind turbines are modeled using the classical `drag disk' concept, are performed for various wind turbine arrangements, turbine loading factors, and surface roughness values. In the wind tunnel studies, the boundary layer flow includes a 3 by 3 array of lightly loaded model wind turbines. The results of both the simulations and experiments are used to shed light on the vertical turbulent transport of momentum and kinetic energy across the boundary layer. The results are also used to develop improved models for effective roughness length scales and to obtain new optimal spacing distances among wind turbines in a large farm. This work is a collaboration with M. Calaf, J. Meyers, R. Cal, J. Lebron, H.S. Kang, and L. Castillo, and is supported by the National Science Foundation.
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July 20, 2010, Tue, 10:30-12:00:
Mark C. Hinrichs (D-4, LANL)
Tutorial on PSLF electric power modeling simulation software
Abstract:
As electric generation and transmission systems have become more complex and congested, new supply patterns are pushing transmission systems to the limits resulting in reduced margins and a significant challenge to system reliability. At the same time, system planners are seeing more volatile dispatch patterns. This trend will continue as market prices and new initiatives into Smart Grids affect the demand for power in a competitive market. The growth in "destabilizing" renewable resources presents challenges that were not realized just a few years ago.
All of these factors point to the need for increased accuracy in modeling, and greater productivity in system planning. GE Positive Sequence Load Flow Software (PSLF) can help utilities achieve these goals. This full-scale program is designed to provide comprehensive and accurate load flow, dynamic simulation and short circuit analysis. PSLF provides for analysis of transfer limits while performing economic dispatch.
PSLF is a suite of analytical tools that can simulate large-scale power systems up to 80,000 buses. Since PSLF has its own fully configured programming language (EPCL), users can build new models that interact with models within the program, perform post-processing and construct macros that automate execution of repetitive simulations and generate reports.
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July 6, 2010, Tue, 10:30-12:00:
Prof. Arun Phadke (Virginia Tech)
Synchronized Phasor Applications for Power Grids
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Abstract:
The talk will discuss catastrophic failures in power systems. Some of the past failures will be described, and the reasons for their occurrence explained. The focus of this discussion will be on the protection system used on power systems, and the reasons for their inappropriate operations under stressed power system states. One of the developments which offers interesting countermeasures for power system failures is the synchrophasor technology. The lecture will go over the origin of this technology, and explain why this technology offers superior capabilities for making black-outs less frequent and less intense.
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June 29, 2010, Tue, 10:30-12:00:
Prof. Federico Milano (Univ. Castilla, Spain)
Continuous Newton's Method for Power Flow Analysis
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Abstract:
This talk presents the application of the continuous Newton's method to
the power flow problem. This method consists in formulating the power
flow problem as a set of autonomous ordinary differential equations.
Based on this formal analogy, an entire family of numerically efficient
algorithms for solving ill-conditioned or badly-initialized power flow
cases is proposed.
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April 27, 2010, Tue, 10:30-12:00:
Dr. Rajan Gupta (LANL)
Walk through the Global Energy Observatory
April 13, 2010, Tue, 10:30-12:00:
Dr. Bernie Neenan (Technical Executive, Electric Power Research Institute) &
Dr. Theresa Flaim (Principal, Energy Resource Economics, LLC)
U.S. Wholesale Electricity Market Fundamentals
Abstract:
Seven Independent System Operators and Regional Transmission Organizations (ISO/RTOs) operate regional electricity markets and manage bulk power system reliability operations. However, they differ in important ways in terms of the functions they perform. Some establish and operate capacity markets to support meeting regional adequacy standards. Others limit their involvement to provide planning services to assist other entities, such as state public service commissions, determine and oversee the provision of capacity requirements. Most operate some form of real-time energy market to balance supply with demand, but the structure of those markets (using auctions versus accommodating bi-lateral arrangements) vary considerably. All are actively involved in operating the system dynamically to ensure that North American Electric Reliability Council (NERC) standards are met, but the mechanics of how that responsibility is achieved are not uniform.
One market structure does not fit all. Understanding the differences is important for comparing market performance. It is also important to characterize how retail markets interface with ISO/RTO market operations. Those interfaces between wholesale and retail markets are important for achieving a high degree of overall market performance. In some regions, ISO/RTO interfaces have influenced the way retail consumers buy electricity. In other regions there is little or no relationship between retail tariffs and wholesale market transactions.
Drs. Neenan and Flaim will address the extent to which ISO/RTO market structure has influenced the development of efficient retail electricity prices and services needed to achieve the efficiency gains upon which electricity market restructuring was premised. A prognosis will be offered as to the extent to which Smart Meter and Smart Grid initiatives will improve the integration of wholesale and retail markets.
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April 6, 2010, Tue, 10:30-12:00:
Prof. Duncan Callaway (Energy & Resources and Mechanical Engineering, UC Berkeley)
Aggregated Electricity Load Modeling & Control for Fast Ancillary Services
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Abstract: This talk will present new methods to model and control the aggregated power
demand from a population of thermostatically controlled loads. The control
objective is to produce relatively short time scale responses (hourly to
sub-hourly) for ancillary services such as load following and regulation.
The control signal is applied by manipulation of temperature set points. The
methods leverage the existence of system diversity and use physically-based
load models to inform the development of a new theoretical model that
accurately predicts - even when the system is not in equilibrium - changes
in load resulting from changes in thermostat temperature set points. Insight
into the transient dynamics that result from set point changes is developed
by deriving a new exact solution to a well-known hybrid state aggregated
load model. A straightforward minimum variance control law is developed and
it is shown that the high frequency components of the output of a wind plant
can be followed with very small changes in the nominal thermostat
temperature set points.
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March 23, 2010, Tue, 10:30-12:00:
Christian Claudel (UC Berkeley)
Optimization formulations for inverse modeling problems, with applications to Mobile Sensing
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Abstract: This talk describes a new method for solving inverse modeling problems in systems modeled by conservation laws, with applications to highway traffic flow estimation.
The state of the system is written in the form of a scalar Hamilton-Jacobi (HJ) partial differential equation (PDE), for which the solution is fully characterized by a Lax-Hopf formula. Using the properties of the solution, we prove that when the data of the problem is prescribed in piecewise affine form, the constraints of the model are convex. This property enables us to identify a class of inverse modeling problems that can be formulated using convex programs.
The inverse modeling algorithms presented in this talk are part of the Mobile Millennium traffic information system, launched recently by UC Berkeley, Nokia and Navteq. The purpose of this system is to use GPS data generated by the smartphones of the driving public of Northern California to estimate the state of traffic on highways and secondary roads.
The algorithms presented in this talk are used to estimate the state of traffic (data assimilation and data reconciliation) in Mobile Millennium, detect some sensor failures (in particular inductive loop detector failures), give guaranteed bounds on some traffic parameters (for instance travel time), and detect cyber attacks.
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March 18, 2010, Thu, 10:00-11:30
[Notice Special Time and Date !!]:
Prof. Ross Baldick (UT Austin)
Wind and Energy Markets: A Case Study of Texas.
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Abstract: Many jurisdictions worldwide are greatly increasing the amount of wind production,
with the expectation that increasing renewables will cost-effectively reduce
greenhouse emissions. We discuss the interaction of increasing wind, transmission
constraints, renewable credits, wind and demand correlation, intermittency, carbon
prices, and electricity market prices using the particular example of the Electric
Reliability Council of Texas (ERCOT) market.
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March 16, 2010, Tue, 10:00-11:30:
Prof. Takashi Nishikawa (Clarkson U)
Visual analytics for discovering group structures in networks
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Abstract: We propose a visual and interactive method for discovering distinct groups of nodes in a network using a user-selected set of node properties computed from the network structure. The user's input on the visual separation of nodes in random 2D projections of a high-dimensional node property space is systematically analyzed to divide the nodes into distinct groups, the number of which is selected by the user interactively. The discovered groups are then examined to reveal their distinguishing characteristics. Our method is capable of discovering communities structures, k-partite structures, or any other structures in which the groups can be distinguished by a combination of node properties. We demonstrate that our method can effectively find and characterize a variety of group structures in model and real-world networks. Joint work with A. Motter.
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March 9, 2010, Tue, 10:30-12:00:
Dr. Richard O'Neill
(Federal Energy Regulatory Committee)
Computational Enhancements for Transforming Wind, Rain and Fire
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Abstract: The ISO market design has evolved over time using traditions, economic theory, power system operations heuristics and operational experience. Early market design made simplifying assumptions and approximations often due to the inability to solve the more detailed design. Complicating
features in market design such as reactive power, unit commitment,
switching of transmission assets, renewable generation, storage and demand
participation make the market non-convex and add new uncertainties that
have little empirical information. We discuss the need and ability to
solve more complex market models faster.
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March 2, 2010, Tue, 10:30-12:00:
Prof. Eric Matzner-Lobel (University of Rennes, France)
Forecasting French electricity consumption using statistics
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Abstract:
Everyday at noon, the french transport system operator has to forecast the next 36 hours of the french electricity consumption for the electricity balance.
We will present the motivation of the work and the solution we proposed using IBR (iterative bias correction) R package.
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Feb 16, 2010, Tue, 10:30-12:00:
Prof. Francesco Bullo (UCSB)
Synchronization in Power Networks and in Non-uniform Kuramoto
Oscillators
Abstract: We discuss the synchronization problem for the network-reduced
model of a power system with non-trivial transfer conductances. Our key
insight is to exploit the relationship between the power network model
and
a first-order model of coupled oscillators. Assuming overdamped
generators
(possibly due to local excitation controllers), a singular perturbation
analysis shows the equivalence between the classic swing equations
and a non-uniform Kuramoto oscillator model. Here, non-uniform Kuramoto
oscillators are characterized by multiple time constants, non-
homogeneous
coupling, and non-uniform phase shifts. Extending methods from
transient
stability, synchronization theory and consensus protocols, we establish
sufficient conditions for synchronization of non-uniform Kuramoto
oscillators. These conditions reduce to and improve upon
previously-available tests for standard Kuramoto model. Combining our
singular perturbation and Kuramoto analyses, we derive concise and
purely
algebraic conditions that relate synchronization and transient
stability of
a power network to the underlying system parameters and initial
conditions.
Biosketch: Francesco Bullo received the Laurea degree in Electrical
Engineering from the University of Padova in 1994, and the Ph.D.
degree in
Control and Dynamical Systems from the California Institute of
Technology
in 1999. From 1998 to 2004, he was affiliated with the Coordinated
Science
Laboratory at the University of Illinois at Urbana-Champaign. He is
currently a Professor with the Mechanical Engineering Department at the
University of California, Santa Barbara. His students' papers were
finalists for the Best Student Paper Award at the IEEE Conference on
Decision and Control (2002, 2005, 2007), and the American Control
Conference (2005, 2006). He is the coauthor of the book "Geometric
Control
of Mechanical Systems" (Springer, 2004) and of the book "Distributed
Control of Robotic Networks" (Princeton, 2009). His main research
interest
is multi-agent networks with application to robotic coordination,
distributed computing and power networks. He is also interested in
vehicle
routing, geometric control, and motion planning problems.
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Feb 2, 2010, Tue, 10:30-12:00:
Dr. Katerine Marvel (Stanford)
Random Matrix Theory and the Electric Grid
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Abstract:
Random Matrix Theory is useful in the study of complex networks such as electric grids. These
transmission systems can be modeled as complex networks, with
high-voltage lines the edges that connect nodes representing power
plants and substations. We draw upon established literature of
complex systems theory and introduce new methods from nuclear and
statistical physics to identify new characteristics of these networks.
We show that most grids can be characterized by the Gaussian
Orthogonal Ensemble, an indicator of chaos in many complex systems.
Under certain circumstances, however, grids may be described by
Poisson statistics, an indicator of regularity.
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Jan 19, 2010, Tue, 10:30-12:00:
Prof. Ian A. Hiskens (U of Michigan, Ann Arbor)
Hybrid Dynamics of Wind Turbine Models
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Abstract: The dynamic behavior of wind turbines is dominated by
interactions between continuous and discrete processes. Care must be
taken to ensure appropriate modeling of such hybrid dynamics. The
talk will discuss various issues that arise in both large- and
small-disturbance analysis of wind turbine systems. We will show
that industry-standard models may exhibit deadlock and Zeno-type
behavior, and consider implications for eigenvalue analysis. We will
explore model revisions that establish well-defined solution
concepts.
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Jan 12, 2010, Tue, 10:30-12:00:
David P. Chassin (PNNL)
Is Statistical Thermodynamics Helpful in Understanding Power Market Behavior?
Abstract:
The smart grid is a vision for the electric system of the future that goes far beyond simply generating, transmitting and delivering power more reliability and more efficiently. Part of the vision includes bringing the behavior of individual loads and energy consumption to bear on the processes that govern large-scale system phenomena.
This talk gives an elementary account of how a statistical thermodynamic approach can help us understand certain economic and physical behaviors of the smart grid. We will discuss how entropy measures the flexibility of a system and how an efficient distribution market can choose the state that maximizes entropy.
When two separate power systems are connected they freely exchange power, the total power remains constant, but the constraints on individual exchanges are lifted and the price of energy changes. The result is a transfer of benefit from one system to another that increases the combined systems entropy to a state which an efficient market will always find, but a flawed market may not find.
This observation allows us to derive a number of useful aggregate system parameters that can be observed and perhaps used to monitor and control market-based systems. Beyond the observed relation between entropy maximization and market efficiency, we can also identify a parameter analogous to thermodynamic temperature, T, that is associated with the net flow of benefits from the market with higher T to the one with lower T; and an analog to electrochemical potential, M, that is associated with the net transfer of control from the system with higher M to the one with lower M.
While this approach differs from traditional methods used to study power markets, the results appear consistent with them but may provide the opportunity for useful insights into the behavior of the future smart grid as it matures.
Biography:
David Chassin is a staff scientist at Pacific Northwest National Laboratory, where he has worked in energy systems modeling, diagnostics, and control system research and development since 1992. Prior to that, he was Vice-President of Development at Image Systems Technology, where he led the commercialization of his thesis work on image processing for computer aided design systems, which is marketed today by Autodesk as gCAD Overlayh. Today, he is the principle investigator for the development of GridLAB-D, DOEfs next generation smart grid simulator.
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Dec 8, 2009, Tue, 10:30-12:00 [Cancelled = Snow Day!!] :
Prof. A. Bayen (UC Berkeley)
Mobile Millennium: using smartphones as monitoring sensors in privacy aware environments
Abstract:
This talk describes how the mobile internet is changing the face of traffic monitoring at a rapid pace. In the last five years, cellular phone technology has bypassed several attempts to construct dedicated infrastructure systems to monitor traffic. Today, GPS equipped smartphones are progressively morphing into an ubiquitous traffic monitoring system, with the potential to provide information almost everywhere in the transportation network. Traffic information systems of this type are one of the first instantiations of participatory sensing for large scale cyberphysical infrastructure systems.
However, while mobile device technology is very promising, fundamental challenges remain to be solved to use it to its full extent, in particular in the fields of modeling and data assimilation. The talk will present a new system, called Mobile Millennium, launched recently by UC Berkeley, Nokia and Navteq, in which the driving public in Northern California can freely download software into their GPS equiped smartphones, enabling them to view traffic in real time and become probe vehicles themselves.
The smartphone data is collected in a privacy-by-design environment, using spatially aware sampling. Using data assimilation, the probe data is fused with existing sensor data, to provide real time estimates of traffic. The data assimilation scheme relies on the appropriate use of Ensemble Kalman Filtering on networked hyperbolic first order partial differential equations, and the construction of lower-semicontinuous viability solutions to Moskowitz Hamilton-Jacobi equations.
Results from experimental deployments in California and New York will be presented, as well as preliminary results from a pilot field operational test in California, with already more than 5,000 downloads.
Additional applications will be discussed, in particular how to use smartphones interfaced with sensors to monitor chemical agents which might be transported by air, social networks user generated content (such as twitter from the phone) for emergency response (for example earthquakes or attacks).
Biography:
Alexandre Bayen received the Engineering Degree in applied mathematics from the Ecole Polytechnique, France, in July 1998, the M.S. degree in aeronautics and astronautics from Stanford University in June 1999, and the Ph.D. in aeronautics and astronautics from Stanford University in December 2003. He was a Visiting Researcher at NASA Ames Research Center from 2000 to 2003. Between January 2004 and December 2004, he worked as the Research
Director of the Autonomous Navigation Laboratory at the Laboratoire de Recherches Balistiques et Aerodynamiques, (Ministere de la Defense, Vernon, France), where he holds the rank of Major. He has been an Assistant Professor in the Department of Civil and Environmental Engineering at UC Berkeley since January 2005. He is the recipient of the Ballhaus Award from Stanford University, 2004. His project Mobile Century received the 2008 Best of ITS Award for ‘Best Innovative Practice’, at the ITS World Congress, and a TRANNY Award from the California Transportation Foundation. He is the recipient of a CAREER award from the National Science Foundation, 2009.
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Nov 16, 2009, Mon, 10:30-12:00, T-DO Conference room,
[Notice Special Date and Place!!] :
Prof. Joydeep Mitra (Michigan State U)
Long-term planning of Generation, Transmission and Distribution Assets
Abstract:
This decade marks the beginning of a process of renewal of the electric energy industry. Widespread deployment of new, diverse and distributed generation assets has begun, and it has become increasingly evident that significant additions need to be made to the transmission and distribution (T&D) system. At the same time, new sensing and control technologies are being deployed system-wide. Consequently, it will become necessary to be considerably more prudent in planning for expansion than we have been in the past. Responsible, long-term strategies will become necessary, and the planning process will become more complex. It will become important to take into account the impacts on controllability, stability and reliability.
The speaker will share some of his research experience with strategic planning of distribution assets and distributed generators, particularly in the area of reliability-centered design and planning for optimal expansion of distribution systems, in both customer-driven and utility-driven scenarios. He will present applications of both evolutionary and traditional methods in reliability-centered expansion planning. He will discuss ways of adapting and applying some of these approaches to the bulk power system. The speaker hopes to stimulate discussion on directions for future research on long-term planning for tomorrow’s cyber-enabled power system, and on opportunities for collaborative work in this emerging field.
Biography: Joydeep Mitra is Associate Professor of Electrical Engineering and Faculty Associate of the Institute of Public Utilities at Michigan State University, East Lansing. He received his B.Tech. (Hons.) degree in Electrical Engineering from the Indian Institute of Technology, Kharagpur, and his Ph.D. degree, also in Electrical Engineering, from Texas A&M University, College Station. Dr. Mitra’s experience includes five years in industry and nine in academia. His research interests include power system reliability, distributed energy resources, and power system planning. His research has been funded by the National Science Foundation, Sandia National Laboratories, Bonneville Power Administration, and Ottertail Power Company. Dr. Mitra is a Senior Member of the IEEE, and recipient of a Career Award from the National Science Foundation, USA.
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Sep 8, 2009, Tue, 10:30-12:00:
Prof. Shmuel S. Oren (UC Berkeley)
Improving Economic Dispatch through Transmission Switching: New Opportunities for a Smart Grid
Abstract:
Traditional security constrained economic dispatch of electricity resources treats the transmission network as a fixed static topology while optimizing deployment of generation assets. However, it is well known that the redundancy build into the grid in order to handles the multitude of contingencies over a long planning horizon can in the short run create congestion and necessitate costly out of merit dispatch. While it is quite common for operators to occasionally open lines that reach their thermal limit, such practices are employed on an ad hoc basis and are not driven by cost considerations. The objective of our work is to explore, from an economic perspective, the potential of treating the grid as a flexible topology that can be co-optimized along with generation dispatch, subject to reliability constraints, so as to minimize the cost of serving load.
This talk will review recent work by the authors demonstrating that optimizing the network topology with generation unit commitment and dispatch can significantly improve the economic operations while maintaining the traditional “N-1 reliability” standard. Our analysis also provides an assessment of potential economic gains from smart grid technologies that will enable of the N-1 reliability standard in favor of new reliability concepts such as “just in time N-1 reliability’. Test results based on a DC OPF analysis are presented for the IEEE 118 bus model, the IEEE RTS 96 system and the ISO-NE 5000 bus electric grid.
(Based on joint work with Kory Hedman, Emily Bartholomew Fisher, Richard P. O’Neill and Michael C. Ferris.)
Biography:
Shmuel S. Oren is the Earl J. Isaac Chair Professor in the Science and Analysis of Decision Making in the Industrial Engineering and Operations Research department at the University of California, Berkeley. He is the Berkeley site director of PSERC – a multi-university Power System Engineering Research Center sponsored by the National Science Foundation and industry members. His academic research focuses on planning and scheduling of power systems and on various aspects of electricity market design and regulation. He has been a consultant to various private and government organizations in the US and abroad and is currently a Senior Adviser to the Market Oversight Division of the Public Utility Commission of Texas (PUCT), and a consultant to the Energy Division of the California Public Utility Commission (CPUC). He holds B.Sc. and M.Sc. degrees in Mechanical Engineering from the Technion in Israel and also M.S. and Ph.D. degrees in Engineering Economic Systems in 1972 from Stanford University. He is a Fellow of the IEEE and of INFORMS.
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Aug 25, 2009, Tue, 10:30-12:00:
Prof. Pravin Varaiya (UC Berkeley)
Risk-Limiting dispatch of the smart grid
Abstract: Federal programs are subsidizing deployments of smart grid elements. But for these initial deployments to grow, the smart grid needs to become self sustaining. This will require modifications in system operations that create a level field for both reliable and interruptible power. One such modification is proposed, founded on the concept of risk-limiting dispatch, and realized in a way that permits incremental deployment. The current practice of worst-case dispatch assumes reliable power sources and limited information. Risk-limiting dispatch relies on information—from sensors, generators and customers—to coordinate interruptible power sources and demand response.
Biography:
Pravin Varaiya is Nortel Networks Distinguished Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. From 1975 to 1992 he was also Professor of Economics at Berkeley. His current research interests include transportation networks, electric power systems, and hybrid systems.
His honors include a Guggenheim Fellowship, three Honorary Doctorates, the Field Medal and Bode Prize of the IEEE Control Systems Society, and the Richard E. Bellman Control Heritage Award. He is a Fellow of IEEE, a member of the National Academy of Engineering, and a Fellow of the American Academy of Arts and Science
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July 14, 2009, Tue, 10:30-12:00:
Prof. Daniel Bienstock (Columbia)
New algorithms for power flow problems
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In this talk we describe ongoing work with new methodologies for two classes of problems: (1) vulnerability analysis of large-scale transmission systems, and (2) algorithms for throughput maximization in transmission systems.
Vulnerability analysis, in particular the so-called "N-k" problem and derivatives, are well-known. As mathematical problems these are quite difficult. We first present results with a mixed-integer programming formulation that addresses a standard version of the problem. We then present results with an indirect approach that proves vastly more scalable and informative while at the same time being able to address a more realistic version of the problem, including 'noise' and model uncertainty.
Concerning (2) we describe a primal-dual approach which combines techniques from convex programming, linear programming and branching techniques.
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June 2, 2009, Tue, 10:30-12:00:
Dr. James J. Nutaro (ORNL)
Modeling Power Systems of the Future: Information Technology and Power System Dynamics
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Information technology is expected to have a central role in the future of electric power delivery. In this presentation, I will discuss techniques for modeling and simulation of future power systems that have classical electro-mechanical elements which interact with communication networks, software agents, real-time price signals, and other discrete event systems. Applications and supporting simulation technology will be discussed in the context of a notionally emergency load shedding system and a study of the impact that market clearing time and communication delay has on the stability of electric power markets.
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May 5, 2009, Tue, 10:30-12:00:
Prof. Michael Caramanis(Boston U)
Management of Electric Vehicle Charging to Mitigate Renewable Generation Intermittency and Distribution Network Congestion
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We consider the management of electric vehicle (EV) loads within a market-based Electric Power System Control Area.
EV load management achieves cost savings in both (i) EV battery charging and (ii) the provision of additional
regulation service required by wind farm expansion. More specifically we develop a decision support method for an
EV Load Aggregator/Energy Service Company (ESCo) that controls EV battery charging. At the beginning of each
period in a 24 hour cycle, the ESCo purchases firm energy from the real-time wholesale market and bids for a
non-firm block of energy which the ESCo commits to allow the Independent System Operator (ISO) to schedule
up or down for regulation service over 5 second intervals. The ESCO’s regulation service bid may or may not
be accepted depending on the clearing of the real time regulation service market. The ESCo is also assumed
to have access to information about local distribution network congestion constraints, namely the maximal
additional load that may be applied along a specific low voltage distribution network feeder without
stressing transformer and other distribution hardware tolerances. This retail-transactions-market information
is employed together with wholesale market information on expected wind farm generation and clearing prices
to make optimal feasible decisions regarding the quantity and bid prices for firm and non-firm energy nominations.
Note that the quantity committed to regulation service must be backed by additional battery charging capacity
allowing response to an up regulation service command, and, moreover, by setting aside sufficient unused feeder
capacity so as to accommodate a commensurate increase in consumption that may be requested by the ISO,
even momentarily, in conjunction with the regulation service bid. Wind farm generation forecasts affect
the clearing price and the demand for regulation service. This is crucial to the ESCo’s decision on how
much non-firm regulation service capacity and at what price it is profitable to bid for.
A hierarchical decision making methodology is proposed for hedging in the day-ahead market and for
playing the real-time market in a manner that yields regulation service revenues and allows for
negotiated discounts on the use-of-distribution-network payments. The proposed methodology employs
a rolling horizon look-ahead stochastic dynamic programming algorithm solved approximately by linear programming.
Its implementation and the observed numerical/computational experience are also reported.
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May 19, 2009, Tue, 10:30-12:00:
Dr. David Mooney (NREL)
Renewable Systems Integration at the National Renewable Energy Laboratory
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As deployment rates for new energy technologies rapidly increase, there is growing emphasis on infrastructure and systems operations upgrades that will be needed to accommodate the unique operating characteristics of new renewable, efficiency, and end-use technologies. To meet these integration challenges, the National Renewable Energy Laboratory (NREL) is implementing a comprehensive systems approach to its R&D and engineering efforts on integration. Through its new center – The Electricity, Resources, and Building Systems Integration Center – NREL is looking across electricity system interfaces to explore the impacts of new technology introduction on the whole system. As the centerpiece for these efforts, the U.S. Department of Energy has commissioned the design and construction of a state-of-the-art laboratory facility – the Energy Systems Integration Facility (ESIF). The ESIF will be constructed to enable complex systems research and development that fully integrates the most advanced simulation, data analysis, engineering, and evaluation techniques to enable optimal deployment of advanced energy technologies. This presentation will overview the ESIF’s role in NREL’s approach to addressing large-scale renewable and efficiency technology integration issues, and discuss specific capabilities and efforts in technology development and integration in generating, transmission, distribution, and end-use systems.
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April 15, 2009, Wed, 1:30-3:00: [Notice Special Date and Time!!]
Prof. Ian Dobson (U of Wisconsin Madison)
Can we quantify the risk of cascading failure blackouts with branching processes?
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Blackouts of the electric power transmission infrastructure are complicated cascading events in a huge network with diverse, interacting failures. In these cascading failures, a series of dependent failures successively weaken the system and making further failures more likely.
The cascading causes power law and criticality phenomena in blackout statistics.
One contention is that we should study not arbitrary networks, but engineered networks, and we outline a complex systems simulation approach to generate "engineered" data when this data is not otherwise available.
We model cascading in a bulk statistical fashion as initial failures propagating probabilistically according to a branching process. We estimate branching process parameters from data and hence
estimate the probability of cascading failures of various sizes.
Initial testing of these methods on real and simulated data open the possibility that the probabilities of large blackouts could be practically estimated from power system observations or non-exhaustive simulation runs.
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March 19, 2009, Thu, 10:00-11:30 [Cancelled !!] :
Prof. Marija Ilic (Carnegie Mellon U)
New systems control problem formulations for the changing electric energy industry
Much has changed in the electric power industry. However, the basic theoretic problem formulations used have remained unchanged.
Unfortunately, these no longer lend themselves to the future needs.
In this talk we start by summarizing monitoring, estimation and control problem formulation for the traditional electric power industry.
Simple simulations are provided to point out the key issues and room for improvement.
We next consider a representative future electric energy systems architecture and contrast its objectives with the objectives of the old industry.
The emphasis is on multi-layered industry capable of integrating distributed resources close to the end users.
A possible problem posing for this industry architecture is presented. The problem posing is used to illustrate challenges, opportunities and open questions.
It is described how the new problem lends itself to the distributed model-predictive control for network systems.
State-of-art sufficient conditions for predictable performance of such systems is discussed in light of what must
be relaxed to be used and useful for future energy systems. Possible solutions must go beyond competitive decentralized system assumptions,
and have to rely on digitally enabled cooperation among the industry participants.
Finally, implications of such novel problem formulation on facilitating technically feasible integration of intermittent resources such as
wind and PVs, in cooperation with small hydro, demand side management and small storage are illustrated.
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March 17, 2009, Tue, 11:00-12:00 [Notice Special Date and Time!!] :
Prof. Chaouki Abdallah (UNM)
Electric Grid Control: Algorithms and Open Problems
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In this talk, I will review problems arising in the modeling, monitoring, and controlling large electrical grids.
A summary of current approaches to such problems is provided as well as an introduction to various control approaches for general dynamical systems.
The talk will conclude by presenting an array of open problems in light of the recent movement to a smarter and more robust electrical grid.
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March 10, 2009, Tue, 10:30-12:00:
Prof. Seth Blumsack (Penn State )
Structural Partitioning for Reliability and Economic Assessments
in Electric Power Networks
A wide variety of analysis problems in large-scale power
systems have historically relied upon partitioning the network into a
number of distinct clusters or zones, each of which is analyzed
independently. Examples include reliability or deliverability
assessments and tests for "load pockets" where some generators in
competitive markets are likely to possess market power. In regionally
integrated systems such as Regional Transmission Organizations (RTOs),
the network has been subdivided into zones based on historical ownership
of transmission assets or some other geographic criteria.
Recent work in the science of networks has drawn connections between
network structure and network performance, or the vulnerability of
networks to certain types of failures. Devising structural measures for
power systems is difficult because a power grid's structure contains
both topological and electrical dimensions. However, defining network
partitions based on structural information rather than asset ownership
or historical affiliation has the potential to improve the utility of
planning procedures that are based on zone boundaries. This talk
presents some ongoing work on using structural information for network
partitioning, based on the concept of electrical centrality proposed by
Hines and Blumsack [1]. The electrical centrality measure is used to
define a set of quality metrics for network partitions. We use these
metrics to build a fitness function that is used to solve a network
clustering problem with explicit reliability or economic objectives.
Preliminary results from an exploratory study of the PJM Interconnection
by Blumsack, et al. [2] demonstrate the feasibility of the proposed
clustering approach, and suggest that structural partitioning can be a
useful tool for improving planning assessments in power systems.
[1] P. Hines and S. Blumsack. A Centrality Measure for Electrical
Networks. Proc. of the 41st Hawaii International Conference on System
Scienes, Waikoloa HI, 2008.
[2] S. Blumsack, P. Hines, M. Patel, C. Barrows and E. Cotilla Sanchez.
Defining Power Network Zones by Measures of Electrical Distance.
Forthcoming in Proc. of the IEEE Power Engineering Society General
Meeting, Calgary AB, 2009.
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March 9, 2009, Mon, 10:30-12:00 [Notice Special Time and Date !!] :
Prof. Paul Hines (U of Vermont)
Complexity in Power Grids: Surviving and Mitigating Large Failures in Power Grids
About 25% of primary energy is consumed in the production of electricity. After conversion losses, about half of this is delivered to consumers over the global electricity infrastructure. Most predict that this percentage will increase substantially in the foreseeable future, particularly with growing interest in electric-drive vehicles.
While power grids are generally robust to small failures, and thus provides a fairly high level of reliability, they are notably vulnerable to large, often spectacular, cascading failures. Single component failures rarely impede the ability of a power grid to serve its customers. But larger sets concurrent outages can produce blackouts with sizes that are highly improbable from the perspective of Gaussian statistics. Because of the number of components in a power grid it is impossible to plan for and mitigate all sets of failures.
Maintaining a high level of reliability in the midst of this risk is challenging. As market forces, variable sources (eg. wind and solar
power) and new loads (eg. electric cars) increase stress on power grids, the challenge of managing reliability and costs will certainly increase. Therefore we need strategies that enable the most important services that depend on electricity infrastructure to continue in the midst of risks. This talk will focus on two strategies for enabling the most important services that depend on electricity continue in the midst of significant systemic vulnerability. The first, as proposed by Talukdar et al. [1] is survivability, in which backup electricity sources provide a very high level of reliability for services that are economically and socially vital. The second, as proposed by Hines et al. [2], is Reciprocal Altruism, under which agents that manage the infrastructure are encouraged to align personal goals with those of the system as a whole. Results from simulated reciprocally altruistic agents indicate that this approach can substantially reduce the size and costs of large blackouts.
[1] S.N. Talukdar, J. Apt, M. Ilic, L.B. Lave, and M.G. Morgan.
Cascading
failures: survival versus prevention. The Electricity Journal, 2003.
[2] P. Hines and S. Talukdar. Reciprocally altruistic agents for the mitigation of cascading failures in electrical power networks. In Proc. of the International Conference on Infrastructure Systems, Rotterdam, 2008.
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