基于IGDT的光储EV混合系统鲁棒优化调度

卫帅兵; 王佳伟; 姚方; 文福拴

doi:10.16513/j.2096-2185.DE.2007004

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分布式能源 ›› 2020, Vol. 5 ›› Issue (5) : 1-7. DOI: 10.16513/j.2096-2185.DE.2007004

学术研究

基于IGDT的光储EV混合系统鲁棒优化调度

卫帅兵 ¹ ,
王佳伟 ² ,
姚方 ¹ ,
文福拴 ³

作者信息 +

IGDT-Based Robust Optimization Scheduling Model of Photovoltaic Energy Storage-EV Hybrid System

Author information +

文章历史 +

摘要

为减弱光伏发电出力的不确定性给光伏并网带来的影响，研究了光储电动汽车(electric vehicle，EV)混合系统优化调度。光储电站运营商以充电补贴的方式引导部分电动汽车改变其原始充电习惯，在光伏发电出力较高时段结合储能系统消纳过剩光伏，并以运营商收益最大化为目标建立光储EV混合系统日前优化调度模型；同时考虑到光伏预测值与实际值之间的偏差，利用信息差距决策理论(information gap decision theory, IGDT)模拟其偏差，得到不同预期目标下的决策解，为运营商提供决策支持，并结合算例进行分析，验证模型的合理性。

Abstract

In order to reduce the influence of the uncertainty of photovoltaic power generation output on photovoltaic grid connection, the optimal scheduling of electric vehicle (EV) hybrid system was studied. Operators of photovoltaic storage power stations use charging electricity price subsidies to guide some electric vehicles to change their original charging habits, combine energy storage systems to absorb excess photovoltaics during periods of higher photovoltaic power generation, and maximize operator profits. At the same time, considering the deviation between the photovoltaic predicted value and the actual value, information gap decision theory (IGDT) is used to simulate the deviation, and the decision solution under different expected goals is obtained, which provides decision support for the operator and is analyzed in conjunction with calculation examples to verify the rationality of the model.

导出引用

卫帅兵, 王佳伟, 姚方, 等. 基于IGDT的光储EV混合系统鲁棒优化调度[J]. 分布式能源. 2020, 5(5): 1-7 https://doi.org/10.16513/j.2096-2185.DE.2007004

Shuaibing WEI, Jiawei WANG, Fang YAO, et al. IGDT-Based Robust Optimization Scheduling Model of Photovoltaic Energy Storage-EV Hybrid System[J]. Distributed Energy Resources. 2020, 5(5): 1-7 https://doi.org/10.16513/j.2096-2185.DE.2007004

中图分类号： TK519; U469.72

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