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

Shuaibing WEI; Jiawei WANG; Fang YAO; Fushuang WEN

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

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Distributed Energy ›› 2020, Vol. 5 ›› Issue (5) : 1-7. DOI: 10.16513/j.2096-2185.DE.2007004

Basic Research

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

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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.

Key words

photovoltaic energy storage / electric vehicle (EV) / information gap decision theory (IGDT) / deviation / decision solution

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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

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