全球能源互联网2024，Vol.7Issue(4)：431-442,12.DOI:10.19705/j.cnki.issn2096-5125.2024.04.008
虚拟电厂供需侧双层协调自适应鲁棒优化调度
Two-layer Coordinated Adaptive Robust Optimal Scheduling on Supply and Demand Side of Virtual Power Plant
吕小红 1刘维 1刘克恒 1蒋婧1
作者信息
- 1. 国网重庆市电力公司,重庆市 渝中区 400015
- 折叠
摘要
Abstract
Source and load prediction is an important basis for virtual power plant(VPP)to make future dispatching plans.A collaborative optimization scheduling method of VPP generation side and user side based on multi-frequency combination short-term source load prediction is proposed.First of all,ensemble empirical mode decomposition(EEMD)is performed on the load data of the time series and reconstructed into two kinds of frequency,which is then predicted by the graph convolution network and long short-term memory(GCN-LSTM)fusion algorithm.The prediction results obtained from the multi-frequency model are aggregated into an uncertain fuzzy set.Considering the demand response,the VPP day-ahead two-layer optimal scheduling model is established.The upper layer takes the user benefit maximization as the goal,comprehensively utilizes the scheduling function of demand response,and optimizes multiple types of controllable loads based on the established time-of-use price.The lower layer aims to minimize the output cost of distributed power supply and take into account the interests of both sides of supply and demand,so as to optimize the internal resources of VPP.The above model is decomposed into main and sub-problems for solving by using the improved column reduction generation algorithm.The economy,robustness,and effectiveness of the proposed model are verified by a case analysis.关键词
多频组合/源荷预测/虚拟电厂/调度优化/长短时记忆/模态分解Key words
multi-frequency combination/source load prediction/virtual power plant/scheduling optimization/long short-term memory/modal decomposition分类
信息技术与安全科学引用本文复制引用
吕小红,刘维,刘克恒,蒋婧..虚拟电厂供需侧双层协调自适应鲁棒优化调度[J].全球能源互联网,2024,7(4):431-442,12.
