This study proposes a multi-objective optimal allocation method of photovoltaic storage charging station (PSCS) considering sufficiency to improve the carrying capacity of the distribution network for a high proportion of new energy and EV loads by integrating the photovoltaic (PV) capacity planning, ESS and charging facilities. The traditional charging station's reliance on grid power exacerbates the peak-to-valley difference and overload risk of the grid, while the PV synergistic configuration. Energy storage systems (ESS) can alleviate the problems of new energy consumption and load fluctuation. The upper layer of the optimization model optimizes the PSCS site selection and equipment capacity with the objectives of economic cost and grid sufficiency. The lower layer optimizes the energy flow state with the objectives of operation cost and voltage stability and realizes multi-objective collaborative decision-making through information feedback. A pre-siting strategy integrating node connectivity importance index and static voltage stability index is proposed. The multi-objective whale migration algorithm (MOWMA) is proposed for the nonlinear characteristics of multi-objective optimization, which introduces the good point set, chaotic mapping, Lévy flight strategy, and double congestion non-dominated sorting mechanism to improve the convergence and the uniformity of the distribution om solution set. Experimental results demonstrate that compared to single-configuration schemes, the proposed method effectively reduces operational costs and net load fluctuations. In 70 % of the test functions, the MOWMA algorithm exhibits optimal performance.