Electric vehicle orderly charging method based on improved NSGA-II algorithm

Abstract

The invention relates to an electric vehicle orderly charging method based on an improved NSGA-II algorithm, wherein the method comprises the steps: taking each electric vehicle charging station as anode, building a power distribution network, taking the safe and stable operation of a power distribution network and the charging electric quantity of an electric vehicle as constraint conditions, and building a multi-objective optimization model with the minimum network loss of the power distribution network and the minimum charging cost of unit electric quantity; the electric vehicle dispatching center firstly acquires electric vehicle charging requirements of each charging station, basic loads of the charging stations and real-time electricity price data of each charging station; then an initial population is randomly generated by taking the total charging power of the electric vehicles in each time period as a variable, and the established multi-objective optimization model is solvedby adopting the improved NSGAII algorithm to obtain an orderly charging scheme of the electric vehicle. According to the method, a traditional genetic algorithm is improved, the convergence speed andconvergence precision of the algorithm are improved, and the charging cost of unit electric quantity can be effectively reduced; active loss of the power distribution network is reduced and power gridoperation efficiency is increased.

Description

technical field [0001] The invention relates to the technical field of charging electric vehicles, in particular to an orderly charging method for electric vehicles based on an improved NSGA-II (multi-objective genetic) algorithm. Background technique [0002] As the use of traditional energy is becoming more and more serious, the exhaust emissions of fuel vehicles are more and more harmful to the environment, and new energy has gradually entered the field of vision of mankind. As a representative of new energy technology, electric vehicles are clean, low-noise and Advantages such as zero emissions are supported and promoted by governments of various countries. Under the existing power grid structure, the randomness of a large number of electric vehicle charging loads poses a serious threat to the security, stability and economic operation of the power grid. Reasonable and effective strategies can guide electric vehicles to charge in an orderly manner and reduce the randomne...

AI Technical Summary

Problems solved by technology

Among them, the NSAG-II algorithm is currently the most popular and one of the most commonly used multi-objective optimization algorithms, but the cross-mutation operator of this algorithm is fixed and simplified, and the cross-mutation operator cannot be dynamically adjusted according to the pros and cons of the individual population. To a certain extent, the convergence speed and convergence accuracy of the algorithm are reduced, which in turn affects the formulation of the optimal charging scheme for electric vehicles

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