典型电力需求侧资源并网出力预测方法研究  

Research on Forecasting Methods of Typical Power Demand-Side Resources Connected to the Grid

作　　者：张林 殷啸秋 李翔[3] ZHANG Lin;YIN Xiaoqiu;LI Xiang(Henan Shidu Engineering Management Consulting Co.,Ltd.,Zhengzhou 450000,China;University of Edinburgh,57 George Square,Edinburgh EH89JU,U.K;Nanjing University of Posts and Telecommunications,Nanjing 210023,China)

机构地区：[1]河南识途工程管理咨询有限公司,河南郑州450000 [2]The University of Edinburgh,57 George Square,Edinburgh,EH89JU,U.K [3]南京邮电大学,江苏南京210023

出　　处：《电工技术》2021年第20期114-118,122,共6页Electric Engineering

基　　金：国家自然科技基金项目“电动汽车充电过程车桩故障预警分析与运维服务”(编号52077107)。

摘　　要：我国电力形势发生显著变化,局部地区电力负荷峰谷差持续增大。以典型电力需求侧资源为研究对象,建立分布式电源、电动汽车并网模型,研究其并网出力情况。通过分析相空间重构法及蒙特卡罗模拟法的基本原理,在智能算法的全局优化基础上,对典型电力需求侧资源并网功率进行预测。借助某风力发电站的550组风力发电历史数据进行出力预测,以及对2022年某日电动汽车充电功率进行预测,验证了所提模型和算法的可靠性和实用性。The power situation in China has changed significantly,and the peak-valley difference of power load in local areas continues to increase.Taking typical power demand side resources as the research object,the grid-connection models of distributed power generation and electric vehicles are established to study their grid-connection output.By analyzing the basic principles of phase space reconstruction method and Monte Carlo simulation method,based on the global optimization of intelligent algorithm,the grid-connected power of typical power demand side resources is forecasted.The reliability and practicability of the proposed model and algorithm are verified by the output prediction of 550 sets of historical data of wind power generation of a wind power plant and the prediction of charging power of electric vehicles on a certain date in 2022.

关 键 词：需求侧资源 相空间重构法 蒙特卡罗模拟法 出力预测 

分 类 号：TM732[电气工程—电力系统及自动化]