基于光伏发电量预测的含氢储能微网分段优化调度

针对多储能微网如何高效、经济运行，搭建了基于光伏发电的含氢储能、蓄电池储能的微网系统，采用一种日前预测调度与日内实时调度相结合的分段调度策略。在日前预测调度阶段，采用基于麻雀搜索算法优化支持向量机模型提高对日前的光伏发电量和负荷预测的精度，以微网最小使用成本为目标，考虑系统运行的可靠性，采用改进粒子群算法制定微网的日前最优调度策略。在日内调度阶段，考虑氢储能系统的响应延迟特性，以蓄电池为灵活补充元件，制定实时调整微网运行策略，消除预测误差带来的影响。最后，结合实际算例分析，验证了分段优化调度的可行性。结果表明，提出的方法能够有效预测数据，减少微网调度的响应时间，提高系统运行的经济性和稳定性。

Sectional optimal dispatching of hydrogen storage microgrid based on photovoltaic generation prediction

The continuous development of microgrid technology has led to the increasing diversification of microgrid energy storage systems. In view of how the multi energy storage systems operate efficiently and economically, has built a microgrid system based on photovoltaic power generation, including hydrogen energy storage and battery energy storage, and proposed a microgrid scheduling strategy combining day ahead scheduling and day-to-day real-time scheduling. In the day ahead scheduling stage, in order to improve the timeliness of the microgrid, using the sparrow search algorithm based support vector machine model (SSA-SVM) to predict the day ahead photovoltaic power generation. Taking the minimum use cost of the microgrid as the goal and considering the reliability of the system operation, the multi- objective sparrow search algorithm is used to formulate the day ahead optimal scheduling strategy of the microgrid. In the intra day dispatching stage, the microgrid operation strategy is adjusted in real time according to the actual power generation to eliminate the impact of prediction error. Finally, the feasibility of the prediction algorithm and scheduling strategy is verified by a practical example. The results show that the proposed method can effectively predict the data, reduce the response time of microgrid scheduling, and improve the economy and stability of system operation.