考虑风光功率短期预测的电力系统调度  

Power System Dispatch Considering Short-Term Forecast of Wind and Solar Power

作　　者：彭颖 丁家会 张财宝 高泽呈 PENG Ying;DING Jiahui;ZHANG Caibao;GAO Zecheng(Energy Internet Research Institute of Nanjing Normal University Zhongbei College,Danyang 212300,China)

机构地区：[1]南京师范大学中北学院能源互联网研究所,江苏丹阳212300

出　　处：《通信电源技术》2023年第1期66-68,共3页Telecom Power Technology

摘　　要：考虑到我国主动配电网具有多级管控的特点,为保证电网安全,短期功率的精准预测具有重要意义,但配电网上集成的可控资源具有随机性和波动性,因此精确预测短期功率的难度较大.通过比较各类全局寻优算法,最终发现应用遗传算法(Genetic Algorithms,GA)优化BP神经网络能够明显提高短期功率的预测精度,降低成本.Considering that my country's active distribution network has the characteristics of multi-level control,accurate short-term power prediction is of great significance to ensure the security of the power grid.However,the controllable resources integrated in the distribution network are random and fluctuating,so short-term power prediction cannot be guaranteed.In this paper,by comparing various global optimization algorithms,it is finally found that the application of Genetic Algorithms(GA)-BP neural network can significantly improve the short-term power prediction accuracy and reduce costs.

关 键 词：短期功率预测 遗传算法(GA)优化BP神经网络 辐照强度和温度 电力系统 

分 类 号：TM615[电气工程—电力系统及自动化]