Journal
IEEE TRANSACTIONS ON POWER SYSTEMS
Volume 32, Issue 5, Pages 3427-3438Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2017.2656080
Keywords
Distribution systems; model predictive control; optimal power flow; renewable integration; voltage regulation
Categories
Funding
- U.S. Department of Energy [DE-AC36-08GO28308]
- National Renewable Energy Laboratory
- Laboratory Directed Research and Development Program at the National Renewable Energy Laboratory
- Grid Modernization Laboratory Consortium
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This paper focuses on distribution systems featuring renewable energy sources (RESs) and energy storage systems, and presents an AC optimal power flow (OPF) approach to optimize system-level performance objectives while coping with uncertainty in both RES generation and loads. The proposed method hinges on a chance-constrained AC OPF formulation, where probabilistic constraints are utilized to enforce voltage regulation with prescribed probability. A computationally more affordable convex reformulation is developed by resorting to suitable linear approximations of the AC power-flow equations as well as convex approximations of the chance constraints. The approximate chance constraints provide conservative bounds that hold for arbitrary distributions of the forecasting errors. An adaptive strategy is then obtained by embedding the proposed AC OPF task into a model predictive control framework. Finally, a distributed solver is developed to strategically distribute the solution of the optimization problems across utility and customers.
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