摘要
源荷预测是虚拟电厂(virtual power plant,VPP)制定未来调度计划的重要依据。提出一种基于多频组合短期源荷预测的VPP发电侧和用户侧协同优化调度方法。首先对时间序列的负荷数据进行集合经验模态分解(ensemble empirical mode decomposition,EEMD),并将其重构为高低2种频率,使用图卷积神经网络(graph convolution network,GCN)和长短期记忆网络(long short-term memory,LSTM)相结合的GCN-LSTM算法进行预测,并将多频模型得出的预测结果聚合形成不确定模糊集合。考虑需求响应,建立VPP双层优化调度模型。上层以用户利益最大化为目标,综合利用需求响应调度作用,基于制定的分时电价优化多类型可控负荷。下层以分布式电源出力成本最小为目标,同时兼顾供需两侧利益,实现VPP内部资源的优化,并运用改进列约生成算法将上述模型分解为主、子问题进行求解。通过算例分析对所构建的模型进行经济性、鲁棒性和有效性验证。
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(GCNLSTM)fusion algorithm.The prediction results obtained from the multi-frequency model are aggregated into an uncertain fuzzy set.Considering the demand response,the VPP dayahead 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.
作者
吕小红
刘维
刘克恒
蒋婧
LYU Xiaohong;LIU Wei;LIU Keheng;JIANG Jing(State Grid Chongqing Electric Power Company,Yuzhong district,Chongqing 400015,China)
出处
《全球能源互联网》
CSCD
北大核心
2024年第4期431-442,共12页
Journal of Global Energy Interconnection
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
multi-frequency combination
source load prediction
virtual power plant
scheduling optimization
long short-term memory
modal decomposition
