摘要
由于太阳能、风能等分布式能源具有随机性,负荷需求曲线也有很大的波动性,若直接用分布式能源给电网或者负荷供电,将会带来一定的冲击或者供需不匹配。文章引入蓄电池储能系统,基于粒子群算法建立优化模型,通过蓄电池在不同时间的充放电来减小电源功率波动,达到削峰填谷的目的。并且通过贵州省某区实验室的光伏和储能设备获取光伏出力数据,结合典型日负荷曲线来验证该模型的实际效果。
Due to the randomness of distributed energy such as solar energy and wind energy, load demand curve also has great volatility. If the distributed energy is used to supply power to the power grid or load directly, it will bring a certain impact or mismatch between supply and demand.The battery energy storage system was introduced, and an optimization model was established based on the particle swarm optimization algorithm, which reduced the power supply fluctuations by charging and discharging the battery at different times to achieve the purpose of peak and valley filling.The photovoltaic output data was obtained through the photovoltaic and energy storage equipment of a certain laboratory in Guizhou Province.The actual effect of the model was verifiedcombined with the typical daily load curve.
作者
徐紫东
许志阳
燕智超
钟淼
XU Zidong;XU Zhiyang;YAN Zhichao;ZHONG Miao(School of Electrical Engineering of GuizhouUniversity,Guiyang 550000,China)
出处
《电工技术》
2020年第14期13-15,共3页
Electric Engineering
基金
贵州大学srt项目资助。
关键词
分布式能源
削峰填谷
粒子群算法
distributed energy
peak load clipping
particle swarm optimization
