Title :
Optimal Dispatch of Electric Vehicles and Wind Power Using Enhanced Particle Swarm Optimization
Author :
Zhao, JunHua ; Wen, Fushuan ; Dong, Zhao Yang ; Xue, Yusheng ; Wong, Kit Po
Author_Institution :
Electr. Eng., Zhejiang Univ., Hangzhou, China
Abstract :
In this paper, an economic dispatch model, which can take into account the uncertainties of plug-in electric vehicles (PEVs) and wind generators, is developed. A simulation based approach is first employed to study the probability distributions of the charge/discharge behaviors of PEVs. The probability distribution of wind power is also derived based on the assumption that the wind speed follows the Rayleigh distribution. The mathematical expectations of the generation costs of wind power and V2G (vehicle to grid) power are then derived analytically. An optimization algorithm is developed based on the well-established particle swarm optimization (PSO) and interior point method to solve the economic dispatch model. The proposed approach is demonstrated by the IEEE 118-bus test system.
Keywords :
electric vehicles; particle swarm optimisation; power generation dispatch; power generation economics; statistical distributions; IEEE 118-bus test system; PEV charge behaviors; PEV discharge behaviors; PSO; Rayleigh distribution; V2G power; economic dispatch model; electric vehicle optimal dispatch; interior point method; particle swarm optimization; plug-in electric vehicle uncertainties; probability distributions; simulation based approach; vehicle-to-grid power; wind power generation costs; wind speed; Discharges; Economics; Generators; Power systems; Uncertainty; Wind power generation; Wind speed; Economic dispatch; particle swarm optimization; plug-in electric vehicle; wind power;
Journal_Title :
Industrial Informatics, IEEE Transactions on
DOI :
10.1109/TII.2012.2205398