基于GCTMSA的梯级水火风光蓄储联合调度

为发展新型电力系统调度理论与方法,构建了一个含梯级水风光蓄一体出力(the integration of cascade hydro-wind-photovoltaic-pumped storage, CHWPPS)的水火风光蓄储联合调度模型。同时,针对传统求解方法在求解水火风光蓄储联合调度系统时易陷入局部最优、难以在满意时间内得出可行解等问题,提出了一种基于贪婪策略、自适应交叉算子和自适应t分布变异的改进飞蛾搜索算法(greedy strategy, adaptive crossover operator and adaptive t-distribution variation based moth search algorithm, GCTMSA)。GCTMSA将自适应交叉算子与Lévy飞行策略相结合,在直线飞行策略中引入自适应t分布变异,并利用贪婪策略仅接收更优个体,以提高全局搜索能力和搜索速度。算例分析在一个修改的IEEE 6机30节点系统和一个省域简化电力系统中展开。结果表明,与飞蛾搜索算法、遗传算法、粒子群算法和生物地理算法相比,GCTMSA具有更强的搜索能力和稳定性。同时,分析了CHWPPS和电池储能对系统的影响。相关讨论与结论可为水火风光蓄储联合调度等多能互补技术发展提供参考。

Dispatch of a cascade hydro-thermal-wind-photovoltaic-storage complementary system based on GCTMSA

To develop novel theories and methods of power system dispatch, this paper constructs a hydro-thermal-wind- photovoltaic-storage coupled dispatching system, one that integrates cascade hydro-wind-photovoltaic-pumped storage (CHWPPS). When analysing such a coupled dispatching system, it is easy for the traditional solution method to fall into a local optimum and it is challenging to arrive at a feasible solution within a satisfactory time. This paper proposes a greedy strategy, adaptive crossover operator and adaptive t-distribution variation-based moth search algorithm (GCTMSA) to overcome these shortcomings. GCTMSA combines the adaptive crossover operator with the Lévy flight strategy, introduces an adaptive t-distribution variation in flight straight strategy, and uses the greedy strategy to enhance the global search capability and speed. The case studies conducted on a modified IEEE 6-machine and 30-bus system and a provincial simplified power system show that the GCTMSA has more substantial search capability and stability than the traditional moth search, genetic or particle swarm algorithms, as well as biogeography-based optimization. The impact of CHWPPS and battery storage on the system is analyzed. The related discussion and conclusion can provide a reference for developing multi-energy complementary technologies such as dispatching hydro-thermal-wind-photovoltaic-storage coupled systems.This work is supported by the National Natural Science Foundation of China (No. 51967004).