基于改进郊狼算法的新能源制氢能量优化调度

针对离网风光互补发电波动性较大及使用氢能进行电能消纳时带来的电网稳定性较差等问题。以建立典型的离网微电网系统框架模型为基础，采取寻优性能高效的改进郊狼优化算法，以微电网功率过剩和不足最小为目标函数，对磷酸铁锂电池组和质子交换膜(proton exchange membrane, PEM)电解槽功率进行合理调度优化。针对算法在模型求解时收敛速度缓慢、易陷入局部最优等不足进行改进，引入一种可变分散概率的郊狼成长和受全局影响的种群间个体交换方法。在提高收敛速度的同时，降低陷入局部最优解的可能。算例分析显示，改进后的郊狼优化算法寻优能力更强，收敛速度更快，可以有效解决微电网中能量调度优化问题。

Energy Optimal Scheduling of New Energy Hydrogen Production Based on Improved Coyote Algorithm

In view of comparatively large fluctuation of off-grid wind-PV hybrid generation and the poor grid stability brought by using hydrogen energy for electric energy accommodation, based on establishing the frame model of typical off-grid microgrid system, an improved coyote optimization algorithm with high efficient searching performance was adopted, and taking minimum surplus and deficiency of microgrid power as objective function, the power of lithium iron phosphate battery pack and proton exchange membrane (abbr. PEM) electrolyzer were reasonably scheduled and optimized. In order to improve the deficiency of slow convergence speed and easy to fall into local optimum during solving the established model, a coyote growth method with variable dispersion probability and a globally influenced individual exchange method among populations were led in, so, while the convergence rate was increased the possibility of falling into local optimal solution was decreased. Results of calculating example show that the improved coyote algorithm possesses stronger optimization ability and its convergence rate is faster, thus, the energy scheduling optimization in microgrid can be effectively implemented and it has a good application prospect.