基于改进旗鱼算法的综合能源系统能量管理

综合能源系统在实现可再生能源利用中具有重要价值。为使系统中各设备出力得到进一步优化，将生物质能与综合能源系统相结合，并且将各个时刻的柔性负荷纳入能量调度，构建了一种沼气发电系统、光伏发电系统与微型燃气轮机驱动下的源-储-荷协同多目标能量管理模型。以系统与主电网的交互及燃料费用、惩罚费用和设备投资及运行费用为优化目标，以用户综合用能满意度、新能源利用率和电能自治程度为评价指标，求解模型最优配置。利用非线性攻击方式、差分变异策略、哈里斯鹰算法中的软包围策略及防止算法停滞策略来改善旗鱼算法的全局搜索能力。通过算例对比分析表明，所提出的改进算法和能量管理模型在不同场景下均有效地提高了经济效益和环保效益，并且改进旗鱼算法在全局寻优和搜索精度等方面具有优势。

Energy management of an integrated energy system based on an improved sailed fish optimizer algorithm

An integrated energy system is important in the utilization of renewable energy. Combining biomass energy with an integrated energy system and incorporating flexible loads at various moments into energy dispatch, a source-storage-load multi-objective energy management model driven by the synergy of biogas and photovoltaic power generation systems and a micro gas turbine is constructed. This is to further optimize the output of each part of the system. The optimal configuration of the model is established, taking the internal interaction of the system and fuel costs, penalty costs, equipment investment and operating costs as the optimization goals, and taking the user''s comprehensive energy satisfaction, new energy utilization rate and electric energy autonomy as evaluation indicators. Non-linear attack methods, differential mutation, soft encirclement in the Harris hawk optimization algorithm and the algorithm stagnation prevention strategies are used to improve the global search ability of the sailed fish optimizer algorithm (SFO). Comparative analysis of calculation examples shows that the proposed improved algorithm and energy management model effectively improve economic and environmental benefits in different scenarios, and the ISFO algorithm has advantages in global optimization and search accuracy. This work is supported by the Natural Science Foundation of Tianjin (No. 19JCZDJC32100).