Stochastic Optimal Load Shedding with Heterogeneous Load Zones

被引:0
|
作者
Zhang, Yu [1 ]
Moura, Scott [2 ]
机构
[1] Univ Calif Santa Cruz, Santa Cruz, CA 95064 USA
[2] Univ Calif Berkeley, Berkeley, CA 94720 USA
关键词
D O I
10.1109/isgt45199.2020.9087700
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Reliability and resilience in power distribution networks are vitally important to ensure seamless electricity delivery to end users. In this paper, we provide an optimization framework for stochastic optimal load shedding in power distribution networks that consists of heterogeneous load zones. Considering uncertain estimates of power consumption and energy shortfall, we formulate the system planning task as a chance-constrained integer quadratic program. By leveraging binary decomposition and McCormick relaxations, we develop two efficient algorithms yielding minimum total load shedding cost while respecting fairness among different end users. Simulation results corroborate the merits of our proposed framework and algorithms, which outperform the off-the-shelf solver BARON.
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页数:5
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