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Chance constrained unit commitment approximation under stochastic wind energy
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DOI：10.1016/j.cor.2021.105398.png)
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En 中文
With the increasing integration of renewable energy into power networks, the scheduling and operation of power systems become more challenging, in particular because of the intermittency of wind speed. Thus, appropriate optimization tools are needed to efficiently manage the operation of modern power systems. This paper considers the unit commitment problem of power systems under high wind energy penetration. To mitigate the potential negative effects of inaccurate wind energy forecast, a chance constrained model is employed to guarantee that supply and demand for energy be balanced at each time period over a finite planning horizon. As joint chance constraint is known to be difficult to handle analytically, two approximation approaches, namely quantile- and p-efficiency-based, are proposed and benchmarked against the well-known scenario-based approximation. The results indicate that the proposed schemes provide feasible solutions and tight lower bounds of the true operation cost within a much shorter time frame than the scenario-based counterpart.
Keyword:
Chance constrained optimization
Stochastic programming
Approximation algorithms
Unit commitment
Renewable energy
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4.3
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6.5K
被引数:
1.8W
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引用论文
A Chance-Constrained Two-Stage Stochastic Program for Unit Commitment With Uncertain Wind Power Output具有不确定风电出力的机组组合的机会约束两阶段随机规划
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