Multi-objective optimization of dynamic load balance on smart grid based on economic dispatch
Li Xin1, Liang Tian1
COMPUTER MODELLING & NEW TECHNOLOGIES 2014 18(12C) 1276-1283
1Shandong Agriculture and Engineering University, Jinan City, Shandong Province, China, 250100
In this paper, hybrid electric vehicles and renewable energy resources are combined to consider as optimization objective to reduce the remission of greenhouse gas. Electric vehicles can provide assistance to the power grid abbreviated as V2G, which changes single interests of power suppliers under the traditional economic operation mode. The intermittence of renewable energy generation and random charging behaviour of electric vehicles owners needs stronger power grid regulation ability. In this paper, we design a dynamic economic dispatch model for smart grid, which contains the plug-in hybrid electric vehicles and renewable energy power resource. By minimizing of power generation costs including V2G service cost, the lowest charging cost of PHEV owners, least air pollution, and maximizing synthetic load ratio, the model contains four optimization objectives. To solve the multi-objective problem, NSGA-II as a popular method to deal with multi-objectives optimizations is employed. Under the premise of keeping up with the demand of power, dynamically adjust the charging/discharging time and power of plug-in hybrid electric vehicles to match the fluctuations of loads and renewable energy generation. In simulations, we applied this model and methods on a 10-generating-unit system. The simulation results show the rationality and validity of the proposed model.