Optimal allocation of energy storage capacity for photovoltaic energy storage charging stations considering EV user behavior and photovoltaic uncertainty

Abstract

In the context of the “dual carbon” goals， photovoltaic energy storage charging stations （PSCSs） are gradually emerging as the mainstream form of electric vehicle （EV） charging stations. To address the uncertainty associated with photovoltaic （PV） generation and user charging behavior， while ensuring the profitability of PSCSs， the paper proposes a method for optimal allocation of energy storage capacity for PSCSs that takes account of EV user behavior and PV uncertainty. Firstly， an improved K-means algorithm is employed to cluster PV output data， establishing typical PV output scenarios and their rules of probability distribution. Secondly， the charging behavior characteristics of EVs are analyzed， incorporating the impact of environmental temperature variations on EV power consumption to develop an EV charging load model. Lastly， considering demand response， an economic operational model is formulated with the objective functions including purchasing cost， carbon emission cost， and electricity sales revenue. Case study results demonstrate that incorporating PV output uncertainty and demand response during energy storage capacity configuration of PSCSs can reduce carbon emissions and ensure the economic viability of PSCSs.

Keywords

• ev
• pscs
• demand response
• carbon emission
• energy storage capacity allocation