期刊
IEEE TRANSACTIONS ON SMART GRID
卷 7, 期 2, 页码 992-1001出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2015.2512503
关键词
Distributed optimization; model predictive control; storage; AC optimal power flow; approximate Newton direction method
资金
- National Science Foundation [ECCS 1027576]
- SYSU-CMU Joint Institute of Engineering
In electric power systems, multiple entities are responsible for ensuring an economic and reliable way of delivering power from producers to consumers. With the increase of variable renewable generation it is becoming increasingly important to take advantage of the individual entities' (and their areas') capabilities for balancing variability. Hence, in this paper, we employ and extend the approximate Newton directions method to optimally coordinate control areas leveraging storage available in one area to balance variable resources in another area with only minimal information exchange among the areas. The problem to be decomposed is a model predictive control problem including generation constraints, energy storage constraints, and AC power flow constraints. Singularity issues encountered when formulating the respective Newton-Raphson steps due to intertemporal constraints are addressed and extensions to the original decomposition method are proposed to improve the convergence rate and required communication of the method.
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