摘要
为合理通过需求响应资源改善电力供需形势,提出了一种基于异构负荷特征解析预测的虚拟电厂双层优化调度模型。考虑多类型负荷的响应特征差异,通过使用动态场景生成和Kmeans++聚类的用户基线负荷曲线预测方法,构建了多类型负荷的需求响应模型;建立考虑负荷聚合商和需求响应的虚拟电厂双层优化调度模型,上层以虚拟电厂运营净收益最大化为目标进行优化调度,下层以负荷聚合商净利润最大化为目标进行市场出清模拟。仿真实验结果表明:充分发挥可调节资源的灵活性,虚拟电厂经济效益提升4.58%,验证了所提优化模型的有效性。
To improve the electricity supply-demand situation by rationally utilizing demand response resources,a two-layer optimal scheduling model for virtual power plants(VPPs)based on the analysis and forecasting of heterogeneous load characteristics was proposed.With the differences in response characteristics of multi-type loads considered,a demand response model for multi-type loads was constructed by using a customer baseline load(CBL)curve forecasting method that integrated dynamic scenario generation and K-means++clustering.A two-layer optimal scheduling model for VPPs that incorporated load aggregators and demand response was established.In this model,the upper layer conducted optimal scheduling targeting maximizing the net operating profit of VPPs,while the lower layer simulated market clearing aimed at maximizing the net profit of load aggregators.The simulation experimental results indicate an improvement of 4.58%in the economic benefit of VPPs through the full utilization of the flexibility of adjustable resources,which validates the effectiveness of the proposed optimal model.
作者
张润昭
陈艳波
黄涛
田昊欣
强涂奔
张智
Zhang Runzhao;Chen Yanbo;Huang Tao;Tian Haoxin;Qiang Tuben;Zhang Zhi(State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(North China Electric Power University),Beijing 102206,China)
出处
《系统仿真学报》
北大核心
2025年第12期2994-3006,共13页
Journal of System Simulation
基金
国家自然科学基金(U24B2083)
中国博士后科学基金面上项目(2024M750893)
国家博士后研究人员计划(GZC20240463)。
关键词
虚拟电厂
多元负荷聚合商
用户基线负荷预测
需求响应
优化调度
virtual power plant(VPP)
multi-type load aggregator
customer baseline load(CBL)forecasting
demand response
optimal scheduling
