The invention discloses an integrated online strategy matching and collaborative optimization method based on big data analysis. Starting from the practical application of collaborative optimization of solar energy and storage, comprehensively considering seasons, weather, and load conditions and combining peak and valley electricity price policies, reasonable adjustment of storage The charging and discharging working state of energy can be fully utilized, and the characteristics of high energy storage timeliness and fast charging and discharging speed can be fully utilized. Through the analysis and clustering of historical load big data, five control plans are formulated, and combined with online real-time matching strategies, real-time adjustments are made to the plans that do not meet the actual situation. The invention not only alleviates the negative impact caused by the randomness and uncertainty of photovoltaic power generation, but also improves the synergy level of the photovoltaic storage system, taking into account the stability and economy of the system, and provides a more reliable method for researching photovoltaic storage synergy optimization.