发电技术2023，Vol.44Issue(6)：790-799,10.DOI:10.12096/j.2096-4528.pgt.23094
气候变化条件下基于智能预测模型的虚拟电厂不确定性运行优化研究
Study on Uncertainty Operation Optimization of Virtual Power Plant Based on Intelligent Prediction Model Under Climate Change
摘要
Abstract
In order to effectively cope with climate change and promote the healthy development of virtual power plant,an uncertainty operation optimization model of virtual power plant(VPP)adapted to climate change was proposed based on the providing regional climate for impact studies(PRECIS),BP neural network prediction model and interval optimization algorithm.PRECIS was used to simulate the changes in meteorological factors such as temperature,wind speed and radiation under different carbon emission scenarios in 2025.The BP neural network model was used to predict the power generation of photovoltaic power plants based on the simulation results of PRICES.The interval optimization algorithm was coupled with the power generation prediction results to reduce the impact caused by the influence of photovoltaic power generation uncertainty on the simulation results of the optimization model.The results show that the model can not only generate the optimal operation strategy of VPP under climate change,but also reduce operating costs and improve economic benefits.关键词
虚拟电厂(VPP)/区域气候模型(PRECIS)/BP神经网络/不确定性优化/气候变化Key words
virtual power plant(VPP)/providing regional climate for impact studies(PRECIS)/BP neural network/uncertainty optimization/climate change分类
能源与动力引用本文复制引用
贾晓强,杨永标,杜姣,甘海庆,杨楠..气候变化条件下基于智能预测模型的虚拟电厂不确定性运行优化研究[J].发电技术,2023,44(6):790-799,10.基金项目
国家电网公司总部科技项目(5100-202118566A-0-5-SF). Project Supported by Science and Technology Projects of State Grid Corporation of China(5100-202118566A-0-5-SF). （5100-202118566A-0-5-SF）
