Coordinated Control of PV Generation and EVs Charging Based on Improved DECell Algorithm

Abstract

Recently, the coordination of EVs’ charging and renewable energy has become a hot research all around the globe. Considering the requirements of EV owner and the influence of the PV output fluctuation on the power grid, a three-objective optimization model was established by controlling the EVs charging power during charging process. By integrating the meshing method into differential evolution cellular (DECell) genetic algorithm, an improved differential evolution cellular (IDECell) genetic algorithm was presented to solve the multiobjective optimization model. Compared to the NSGA-II and DECell, the IDECell algorithm showed better performance in the convergence and uniform distribution. Furthermore, the IDECell algorithm was applied to obtain the Pareto front of nondominated solutions. Followed by the normalized sorting of the nondominated solutions, the optimal solution was chosen to arrive at the optimized coordinated control strategy of PV generation and EVs charging. Compared to typical charging pattern, the optimized charging pattern could reduce the fluctuations of PV generation output power, satisfy the demand of EVs charging quantity, and save the total charging cost.

A Study on Coordinated Optimization of Electric Vehicle Charging and Charging Pile Selection

“…Constraint (12) indicates that if and only if there is one type of charging piles configured for each EV. Constraint (13) indicates that the charging power of each EV does not exceed the allowable value during different periods, and that the charging process is uninterrupted. Constraint (14) indicates the exact charging demands for all EVs, and ∆Q i denotes the charging demands of EV i. Constraint Energies 2018, 11, 1350 6 of 16 (15) indicates that the total charging power of group X during different periods should not exceed the allocated transformer available capacity, which is calculated as shown in Equation (16):…”

“…Currently, the most typical method for EV slow charging is the two-stage charging method that alternates between constant current and constant voltage [13]. Throughout the entire charging process, since constant current charging is used for most of the time, its charging power does not vary greatly but only shows a significant increase at the end of constant…”

“…Xia et al [12] introduced the concept of the distribution network's power supply capability and proposed an EV optimal charging method that could reduce the charging costs for the users and the impacts on the power grid. Zhao et al [13] comprehensively investigated the photovoltaic output and EV stoppage features, and an optimal charging method was proposed to coordinate the EVs and photovoltaic output under the time-of-use price. Through segmentally optimizing the charging power of EVs, it managed to stabilize the load fluctuation of the power grid, lower the users' charging costs, and maximize the consumption of new energy.…”

“…In terms of EV charging optimization, researches tend to assume that when the charging facilities are given and the demands for EV charging are met, effective control of the EV charging process, such as the initial charging time and staged charging power [13], can reduce the charging costs for the users and the impacts on the power grid. In terms of charging facility planning, based on the given charging method, while meeting the demands for EV charging, researchers tend to minimize the investment cost on the charging facilities [24], without considering the impacts on EV charging.…”

A Study on Price-Based Charging Strategy for Electric Vehicles on Expressways

“…During the whole charging process, most of the charging time would be the first stage in which the charging power has little change. As a result, EV battery could be considered as a constant power load so that the constant-voltage charging process could be ignored [14]. Based on the constant charging power, the charging time of the EV k r at the CS i r is calculated as:…”