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Center for Nonlinear Studies |
The modernization of electricity networks to accommodate increasing renewable energy targets and new technologies, such as electric vehicles and demand management, leads to system control and planning challenges and so analytical challenges. To name two, we will have to deal with much greater uncertainty and scale in computations. For example, the latter arises from the increasing granularity of modeling and control devices across transmission and distribution all the way to households. This presentation is based on a Future Grid (FG) project in Australia funded by the CSIRO and four universities. It takes a long-term view out to 2050. Advanced modeling and analytical techniques will be developed to provide a suite of tools to help understand and design future grids. This is being done by following a tree structure of alternative scenarios according to technology and policy changes, probabilistic modeling of generation sites and outputs, use of enhanced Monte Carlo methods with learning, network science methods, automated scanning tools for system properties such as stability and multi-objective stochastic optimization on networks for planning. One way or another, grids must become more adaptive and resilient to changing power supply and demand, failures and attacks through coordinated planning and control more than ever before. The talk will introduce some key ideas and preliminary results from the FG project.
Host: Misha Chertkov