基于分层次DBSCAN-VBSO算法的区域综合能源系统两阶段调度优化

构建了一种面向园区级区域综合能源系统的日前-实时两阶段经济性调度优化模型。建立了综合考虑系统各类运行成本的日前经济性调度模型;在日前调度基础上通过修正各个微源机组、储能的运行状态并考虑柔性负荷的需求响应,构建了实时调度优化模型;为求解上述调度优化模型,提出了一种分层次密度聚类的变异头脑风暴优化(DBSCAN-VBSO)算法,通过保持种群多样性以增强算法的优化性能和计算效率;对综合能源系统两阶段调度模型和求解算法进行仿真计算。算例结果表明:采用两阶段调度优化模型能够有效提高可再生能源利用率,降低系统运行成本。并且算例结果验证了分层次DBSCAN-VBSO算法在求解此类优化问题时的有效性和优越性。

Two-stage dispatching optimization of regional integrated energy system based on hierarchical DBSCAN-VBSO algorithm

A day-ahead and real-time two-stage economic dispatching optimization model for the community-scale integrated energy system is constructed. Firstly, the day-ahead economic dispatching model considering all kinds of system operating costs is established. Secondly, on the basis of day-ahead dispatching, the real-time dispatching optimization model is constructed by correcting the operating state of each micro-source unit and energy storage, and considering the demand response of flexible load. Thirdly, in order to solve the above dispatching optimization model, a hierarchical DBSCAN-VBSO(Density-Based Spatial Clustering of Applications with Noise-Variant Brain Storm Optimization) algorithm is proposed, to enhance the optimization performance and computational efficiency of the algorithm by maintaining the diversity of the population. Finally, the simulation of the two-stage dispatching model and algorithm for integrated energy system is carried on. Simulative results show that the two-stage dispatching optimization model can effectively improve the utilization rate of renewable energy and reduce the operating cost of system. And the results verify the effectiveness and superiority of hierarchical DBSCAN-VBSO in solving such optimization problems.