Abstract
As an important component of the smart grid, electric vehicles (EVs) could be a good measure against energy shortages and environmental pollution. A main way of energy supply to EVs is to swap battery from the swap station. Based on the characteristics of EV battery swap station, the coordinated charging optimal control strategy is investigated to smooth the load fluctuation. Shuffled frog leaping algorithm (SFLA) is an optimization method inspired by the memetic evolution of a group of frogs when seeking food. An improved shuffled frog leaping algorithm (ISFLA) with the reflecting method to deal with the boundary constraint is proposed to obtain the solution of the optimal control strategy for coordinated charging. Based on the daily load of a certain area, the numerical simulations including the comparison of PSO and ISFLA are carried out and the results show that the presented ISFLA can effectively lower the peak-valley difference and smooth the load profile with the faster convergence rate and higher convergence precision.
Highlights
Over the past decades, many issues, such as energy shortages, serious environmental pollution, and global warming, have increasingly become worldwide concerns
Based on the daily load of a certain area, the numerical simulations including the comparison of particle swarm optimization (PSO) and improved shuffled frog leaping algorithm (ISFLA) are carried out and the results show that the presented ISFLA can effectively lower the peak-valley difference and smooth the load profile with the faster convergence rate and higher convergence precision
Many domestic and foreign scholars have carried out researches on the impact of electric vehicles (EVs) on power distribution system [2,3,4,5,6,7], which mainly focus on the coordinated charging of EVs but rarely involve the optimal control strategy for the coordinated charging of EV battery swap station
Summary
Many issues, such as energy shortages, serious environmental pollution, and global warming, have increasingly become worldwide concerns. Compared with internal combustion engine vehicles (ICEVs), which burn fossil fuels, EVs are driven by electricity. They demonstrate considerable advantages in solving the energy crisis and reducing the emissions of carbon dioxide, as well as in providing a means to drastically reduce the man-made pollution. The SFLA draws its formulation from two other search techniques: the local search of the “particle swarm optimization” technique and the competitiveness mixing of information of the “shuffled complex evolution” technique It locates a global optimum by combining global information exchange and local search, simulating the process of a group of frogs’ population-based cooperative seeking food. The comparison of PSO and ISFLA shows that the presented ISFLA can lower the peak-valley difference and smooth the load profile with the faster convergence rate and higher convergence precision
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