Multi-objective Parallel Particle Swarm Optimization for Day-ahead Vehicle-To-Grid Scheduling


Autoria(s): Soares, João; Vale, Zita; Canizes, Bruno; Morais, Hugo
Data(s)

04/05/2015

04/05/2015

01/04/2013

Resumo

This paper presents a methodology for multi-objective day-ahead energy resource scheduling for smart grids considering intensive use of distributed generation and Vehicle- To-Grid (V2G). The main focus is the application of weighted Pareto to a multi-objective parallel particle swarm approach aiming to solve the dual-objective V2G scheduling: minimizing total operation costs and maximizing V2G income. A realistic mathematical formulation, considering the network constraints and V2G charging and discharging efficiencies is presented and parallel computing is applied to the Pareto weights. AC power flow calculation is included in the metaheuristics approach 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.

Identificador

http://hdl.handle.net/10400.22/5898

10.1109/CIASG.2013.6611510

Idioma(s)

eng

Publicador

IEEE

Relação

CIASG;2013

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6611510&queryText%3DMulti-objective+parallel+particle+swarm+optimization+for+day-ahead+Vehicle-to-Grid+scheduling

Direitos

closedAccess

Palavras-Chave #Multi-objective #Pareto front #Particle swarm optimization #Scheduling #Vehicle-to-grid
Tipo

conferenceObject