基于碱性电解槽宽功率适应模型的风光氢热虚拟电厂 容量配置与调度优化

为提高能源利用效率，降低碳排放水平，改善虚拟电厂运行效益，构建了基于碱性电解槽宽功率适应模型的风光氢热虚拟电厂(Virtual Power Plant, VPP)模型。将制氢电解槽、氢燃料电池、储氢罐构成氢能系统，代替传统虚拟电厂中的蓄电池，并提出碱性电解槽宽功率适应模型，提高电解槽在不同输入功率条件下的适应性。利用氢能系统运行时产生热量对系统负荷实行热电联供，并将电解槽产生氧气出售。在此基础上，使用改进多路无网格光线寻优算法对各设备出力调度与设备容量配置进行优化。仿真结果表明，该算法在计算精度和速度上有一定提高。基于碱性电解槽宽功率适应模型的风光氢热VPP，在降低系统运行成本的同时可以有效应对风、光出力波动，提高风、光消纳水平，减少碳排放。

Capacity configuration and optimal scheduling of a wind-photovoltaic-hydrogen-thermal virtual power plant based on a wide range power adaptation strategy for an alkaline electrolyzer

To improve energy efficiency, reduce carbon emissions, and improve the operating efficiency of virtual power plants (VPP), this paper constructs a wind-photovoltaic-hydrogen-thermal VPP model based on a wide range power adaptation strategy for alkaline electrolyzers. The hydrogen production electrolyzer, hydrogen fuel cell, and hydrogen storage tank constitute a hydrogen energy system to replace the battery in the traditional VPP, and we propose a wide range power adaptation strategy for the alkaline electrolyzer to improve the adaptability of the electrolyzer under different input power conditions. The heat generated during the operation of the hydrogen energy system is used to implement combined heat and power supply to the system load, and at the same time the oxygen produced by the electrolytic cell is sold. On this basis, an improved multi-channel meshless light optimization algorithm is used to optimize the operation scheduling and equipment capacity configuration of each device. The simulation results show that the algorithm offers an improvement in calculation accuracy and speed. The wind-photovoltaic-hydrogen-thermal VPP based on the wide range power adaptation strategy can effectively cope with the fluctuation of wind and photovoltaic output while reducing the operating cost of the system. It can also improve the level of wind and solar consumption and reduce carbon dioxide emissions. This work is supported by the National Natural Science Foundation of China (No. 51767023).