多站融合场景下微能源网多目标需求响应联合优化模型

Joint Optimization Model of Multi-objective Demand Response of Micro Energy Network in Multi-station Fusion Scenario

为了优化配置多种分布式能源,研究多站融合场景下微能源网多目标需求响应联合优化模型设计方法。以状态目标的最佳位置为前提选择“时差—时差”定位方式,在多站融合场景协同下建立源支路与节点的关联矩阵,通过定点能量平衡方程建立调度目标联合优化模型。引入雷达检测技术,转换能源多目标需求响应数据。实验结果表明:在不同阶段进行削峰填谷的优化配置,能促使每种负荷总量下降:通过对春秋季节内电负荷的峰谷值控制,可将最大峰值500 kW优化至180 kW;夏季节冷负荷的峰值为1200 kW,优化后峰值为300 kW;冬季热负荷的峰值为1400 kW,优化后峰值为400 kW;能够保证电、热、气、冷等多种能源的灵活交互。

In order to optimize the configuration of a variety of distributed energy,the joint optimization model design method of multi-objective demand response of micro energy network under the scenario of multi-station fusion is studied.On the premise of the best position of the state target,the“TDOA—TDOA”positioning method is selected.Under the cooperation of multi-station fusion scenario,the correlation matrix between the source branch and the node is established,and a joint optimization model of the scheduling target is established through the fixed-point energy balance equation.Radar detection technology is introduced to convert energy multi-target demand response data.The experimental results show that optimizing the configuration of peak shaving and valley filling at different stages can reduce the total amount of each load.By controlling the peak and valley values of electric load in spring and autumn,the maximum peak value of 500 kW can be optimized to 180 kW.The peak value of the cooling load in summer is 1200 kW,and the peak value after optimization is 300 kW.The peak value of heat load in winter is 1400 kW,and the peak value after optimization is 400 kW.It ensures the flexible interaction of various energy sources such as electricity,heat,gas and cooling.