基于人工鱼群算法的水风光联合调峰优化模型
Peak Shaving Optimization Model for Wind-Photovoltaic-Hydro Joint Scheduling based on Artificial Fish Swarm Optimization
黄娟 1赵鹏 2王聚博 2凌宇龙 2苏洋 2赵闻音2
作者信息
- 1. 国家电投集团江西电力有限公司,江西 南昌 330000
- 2. 国家电投集团科学技术研究院有限公司,北京 102200
- 折叠
摘要
本文提出基于多Agent人工鱼群算法(MAAFAS)的,以剩余负荷均方差最小为目标函数的梯级水风光短期调峰优化调度模型.该模型充分结合了Agent算法的自主性和人工鱼群算法的全局寻优性,降低了约束的复杂性,易于获得复杂问题求解下的最优解.并以我国南方地区某流域的6 座水电站,11 座风电场,4 座光伏电站组成的风光水电源互补系统为研究对象,从不同来水场景下(汛期、枯期)进行实例分析.结果表明:该模型可以有效地利用水电能源的调峰能力,平均提高负荷峰谷差降幅率到44.65%,缩小原始负荷峰谷差3 300 MW,剩余负荷趋于平稳,便于风光能源的更好消纳,是一种实用性较强的水风光短期调峰优化方法.
Abstract
With the problem of wind and light loss,this paper proposes an artificial fish swarm algorithm based on multi-agent(MAAFAS),and constructs a short-term peak shaving optimization dispatching model of cascade water and scenery with the minimum residual load mean square error as the objective function.This model fully combines the autonomy of multi-agent algorithm and the global optimization of artificial fish swarm algorithm,reducing the complexity of constraints and making it easy to obtain the op-timal solution for complex problem solving.Taking the wind power and water power complementary sys-tem composed of 6 hydropower stations,11 wind farms and 4 photovoltaic power stations in a certain ba-sin in Southwest China as the research object,the case analysis is carried out under different water inflow scenarios(flood season and dry season).The results show that the model can effectively utilize the peak shaving capacity of hydropower energy,significantly increase the average reduction rate of load peak val-ley difference to 44.65%,reduce the original load peak valley difference of 3 300 MW,and stabilize the residual load,facilitating better consumption of wind and solar energy.It is an effective algorithm with strong practicability to solve the short-term joint optimization of peak shaving scheduling of wind-solar complementary power generation system.
关键词
梯级水风光互补发电系统/短期优化调度/多Agent人工鱼群算法/调峰/梯级水电站Key words
wind-photovoltaic-hydro hybrid power system/short-term optimal operation/multi-a-gent artificial fish swarm optimization/peak shaving/cascade hydropower plants引用本文复制引用
出版年
2024
NETL
NSTL
万方数据