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

João Soares, Zita Valle, Hugo Morais

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Abstract

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-ahead
scheduling 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.
Original languageEnglish
Title of host publication7th International Conference on Intelligent System Applications to Power Systems
Number of pages6
PublisherIEEE
Publication date2013
Publication statusPublished - 2013
Event17th International Conference on Intelligent Systems Application to Power Systems - Tokyo, Japan
Duration: 1 Jul 20134 Jul 2013
http://www.isc.meiji.ac.jp/~hmori/isap2013/

Conference

Conference17th International Conference on Intelligent Systems Application to Power Systems
CountryJapan
CityTokyo
Period01/07/201304/07/2013
Internet address

Keywords

  • Hybrid technique
  • Mixed-integer linear programming
  • Optimal scheduling
  • Particle Swarm Optimization
  • Vehicle-to-grid

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