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Distributionally Robust Co-optimization of Transmission Network Expansion Planning and Penetration Level of Renewable Generation 被引量:3
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作者 Jingwei Hu Xiaoyuan Xu +1 位作者 Hongyan Ma Zheng Yan 《Journal of Modern Power Systems and Clean Energy》 SCIE EI CSCD 2022年第3期577-587,共11页
Transmission network expansion can significantly improve the penetration level of renewable generation.However,existing studies have not explicitly revealed and quantified the trade-off between the investment cost and... Transmission network expansion can significantly improve the penetration level of renewable generation.However,existing studies have not explicitly revealed and quantified the trade-off between the investment cost and penetration level of renewable generation.This paper proposes a distributionally robust optimization model to minimize the cost of transmission network expansion under uncertainty and maximize the penetration level of renewable generation.The proposed model includes distributionally robust joint chance constraints,which maximize the minimum expectation of the renewable utilization probability among a set of certain probability distributions within an ambiguity set.The proposed formulation yields a twostage robust optimization model with variable bounds of the uncertain sets,which is hard to solve.By applying the affine decision rule,second-order conic reformulation,and duality,we reformulate it into a single-stage standard robust optimization model and solve it efficiently via commercial solvers.Case studies are carried on the Garver 6-bus and IEEE 118-bus systems to illustrate the validity of the proposed method. 展开更多
关键词 affine decision rule distributionally robust optimization joint chance constraint renewable generation transmission network expansion planning
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