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Decision support tool for Virtual Power Players: Hybrid Particle Swarm Optimization applied to Day-ahead Vehicle-To-Grid Scheduling

机译:用于虚拟电力运营商的决策支持工具:混合粒子群优化应用于日前车辆到电网调度

摘要

This paper presents a decision support Tool methodology to help virtual power players (VPPs) in the Smart Grid (SGs) context to solve the day-ahead energy ressource scheduling considering the intensive use of Distributed Generation (DG) and Vehicle-To-Grid (V2G). The main focus is the application of a new hybrid method combing a particle swarm approach and a deterministic technique based on mixedinteger linear programming (MILP) to solve the day-aheadscheduling minimizing total operation costs from the aggregator point of view. A realistic mathematical formulation, considering the electric network constraints and V2G charging and discharging efficiencies is presented. Full AC power flow calculation is included in the hybrid method to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance of the proposed method.
机译:本文提出了一种决策支持工具方法,该方法可帮助智能电网(SG)上下文中的虚拟电源参与者(VPP)解决考虑大量使用分布式发电(DG)和车辆到电网( V2G)。主要焦点是应用新的混合方法,该方法结合了粒子群方法和基于混合整数线性规划(MILP)的确定性技术,可以解决日前调度问题,从而从聚合器的角度将总运营成本降至最低。提出了考虑电网约束和V2G充放电效率的现实数学公式。混合方法中包括完整的交流潮流计算,以考虑网络约束。以33总线配电网络和1800 V2G资源为例,说明了该方法的性能。

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