摘要
高比例可再生能源微电网的优化调度对于推动新型电力系统的绿色转型具有重要意义。针对微电网因天气条件等环境因素而具有的不确定性和随机性问题,提出了一种基于简化粒子群优化算法,以微电网运行成本最小化为目标的可再生微电网随机优化调度策略。首先,建立了风力发电机、光伏系统、燃料电池、微型涡轮机等动力装置的数学模型,并对其性能进行了说明;其次,设计了简化粒子群优化算法模型及其执行流程;最后,利用以上建立的四种微源模型的每小时预测输出功率来优化微电网的运营成本,得到了适应度值为23,微电网运营成本得到有效控制的最佳适应度解。本研究通过考虑负载需求,对微电网可再生能源的优化管理做出决策,提供了更加稳健的解决方案。
Optimal scheduling of high-percentage renewable energy microgrids is of great significance in promoting the green transition of new power systems.Aiming at the problem of uncertainty and stochasticity of microgrids due to environmental factors such as weather conditions,this paper proposes a stochastic optimal scheduling strategy for renewable microgrids based on a simplified particle swarm optimization algorithm with the goal of minimizing the operating cost of microgrids.Firstly,mathematical models of power devices such as wind turbine,photovoltaic system,fuel cell and microturbine are established and their performances are explained.Secondly,the simplified particle swarm optimization algorithm model and its execution process are designed.Finally,the hourly predicted output power of the four microsource models established above is used to optimize the operating cost of the microgrid,and the optimal fitness solution with a fitness value of 23 and an effective control of the operating cost of the microgrid is obtained.This study provides a more robust solution by considering the load demand and making decisions on the optimal management of renewable energy in microgrids.
作者
陈喆
杜龙
陈愈芳
滕伟业
陆展辉
CHEN Zhe;DU Long;CHEN Yu-fang;TENG Wei-ye;LU Zhan-hui(Guangzhou Power Trading Center limited liability company,Guangzhou 510180,China;China Energy Construction Group Guangdong Electric Power Design and Research Institute Co.LTD,Guangzhou 510530,China)
出处
《光学与光电技术》
2024年第3期135-141,148,共8页
Optics & Optoelectronic Technology
