基于简化粒子群优化算法的可再生微电网随机优化调度策略研究
Study on Stochastic Optimal Scheduling Strategy for Renewable Microgrid Based on Simplified Particle Swarm Optimization Algorithm
陈喆 1杜龙 1陈愈芳 1滕伟业 1陆展辉2
作者信息
- 1. 广州电力交易中心有限责任公司,广东广州 510180
- 2. 中国能源建设集团广东电力设计研究院有限公司,广东广州 510530
- 折叠
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.
Abstract
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.
关键词
微电网/可再生能源/粒子群优化(PSO)/优化调度策略Key words
microgrid/renewable energy/particle swarm optimization(PSO)/optimal scheduling strategy引用本文复制引用
出版年
2024
NETL
NSTL
万方数据