Multi-objective optimal operation of micro-grid with plug-in electric vehicles

Abstract

A multi-objective operational scheduling model with plug-in electric vehicles (PEVs) is proposed to minimize the operation cost and to improve the load characteristic of Microgrid. In this model, the PEVs charging power and the distribute generations (DGs) output power of each time period are selected as decision variables, the driving behavior of PEVs is also taken into account. Multi-objective evolution algorithm NSGA-II is utilized to solve the multi-objective model and fuzzy clustering method is introduced to help obtaining the best Pareto front. The presented model is tested on the IEEE 34-node test feeder, the results obtained demonstrate the effectiveness of the proposed dispatching approach.

Optimal operation of hybrid AC/DC microgrids under uncertainty of renewable energy resources: A comprehensive review

“…Reference [103] analyzes the optimal operation of a microgrid in the presence of Plug-in Electric Vehicle (PEV), using NSGA-II algorithm. The addition of PEVs to the microgrid brings new challenges and opportunities to the microgrid operation.…”

“…Table 11 illustrates a summary of the presented literature review. Weighted majority algorithm [93] GWO [94] Genetic Optimization/ Generating sets search algorithm [95] Dynamic programming [96] Imperialist competitive/ Monte Carlo Simulation [97] Multi-objective genetic algorithm [98] Multi-objective genetic algorithm [99] Smart microgrid Particle swarm optimization/ Q-learning [100] Smart microgrid Mixed Integer nonlinear programming [101] IBM ILOG CPLEX [102] Cuckoo search/ Bat algorithm [103] NSGA II/ fuzzy clustering [104] Stochastic programming/ CPLEX [105] Matlab/ Simulink…”