Stability (learning theory)

Physics

Sociology

Automotive engineering

Population

Mathematics

Economic growth

Algorithm

Mathematical optimization

Machine learning

Demography

Engineering

Artificial intelligence

Economics

Power (physics)

Electric vehicle

Selection algorithm

Convergence (economics)

Charging station

Computer science

Quantum mechanics

Simulation

Selection (genetic algorithm)

Energies

To solve the problem of layout design of charging stations in the early stage of the electric vehicle industry, the user’s satisfaction and the charging convenience are considered. An electric vehicle charging station site-selection model is established based on the kernel density analysis of the urban population. The goal of this model is maximum electric vehicle user satisfaction and the highest charging convenience. Then, according to model characteristics, the immune algorithm is designed and optimized to solve the model. The optimization of the immune algorithm includes two aspects. On the one aspect, judging that the stop condition is added in the mutation link. On the other aspect, two mutation operators are designed in the optimized immune algorithm. Finally, the simulation example is determined by a three-step method in Jinan City. The results show that the electric vehicle charging station site-selection model in this paper can better meet user needs compared with traditional models. Compared with the traditional immune algorithm, the convergence speed of the optimized immune algorithm is improved, and the proposed algorithm is superior to the traditional immune algorithm in terms of stability and accuracy.

Optimal Planning of Electric Vehicle Charging Stations Considering User Satisfaction and Charging Convenience