针对光伏充换电站内电动汽车无序补电以及电池无序充放的现象，为保障用户补电最优性、光伏充换电站经济性及区域电网稳定性，提出了一种综合多模式补电与电池调控的多方需求协同优化策略，引导站内用户补电决策及电池调度。首先，根据电量焦虑及时间冗余原则分群，基于补电激励及时间焦虑建立价格感知激励模型，并考虑需求价格弹性和价格感知激励构建用户需求补电量，进一步基于后悔定理建立补电决策模型。其次，基于电网负荷水平及电池电量引导，考虑电池充放状态建立电池调控模型。最后，建立多方需求优化调度模型，以充换电站经济效益最大化和区域电网总负荷波动最小化对补电激励及电池充放状态进行优化。仿真验证结果表明，所提策略显著提高了多方需求满足程度，用户花费降低了8.3 %，光伏充换电站经济效益提高了16.5 %，区域电网负荷波动降低了41.7 %。

In response to the phenomenon of the negative effects of disorderly charging and discharging of electric vehicles and batteries in photovoltaic battery charging and swapping station(BCSS), a multi-party collaborative optimization strategy integrating multi-mode power replenishment and battery regulation is proposed to ensure user power replenishment optimality, BCSS economy, and regional power grid stability, guiding users′ replenishment decisions and battery scheduling within the station. Firstly, based on the principles of power anxiety and time redundancy, a price perception incentive model is established based on power replenishment incentives and time anxiety, and user demand for power replenishment is constructed considering demand price elasticity and price perception incentives. Furthermore, a power replenishment decision model is established based on the regret theorem. Secondly, based on the load level of the power grid and the guidance of battery capacity, a battery regulation model is established considering the charging and discharging status of the battery. Finally, a multi-party demand optimization scheduling model is established to maximize the economic benefits of charging and swapping stations and minimize regional power grid load fluctuations. Simulation results demonstrate the effectiveness of the proposed strategy, with reducing user expenses by 8.3 %, increasing economic benefits of BCSS by 16.5 %, and reducing regional grid load fluctuations by 41.7 %.