Location planning of electric vehicle charging stations based on a multi-objective three-level optimization model

The construction of electric vehicle (EV) charging stations (CSs) plays an important role in promoting the adoption of EVs. This paper mainly solves EVs' charging station location planning problem (CSLP). The CSLP involves various optimization objectives, such as waiting time, driving distance, station construction costs, profits, etc. Currently, most papers select one or two optimization objectives to model and optimize. We formulate the CSLP problem as a multi-objective three-level optimization problem that simultaneously optimizes user waiting time, annual investor profit, user driving distance, and expense. It involves three sub-problems: user-directed decision level (lower level), charging piles number decision level (middle level), and CS location decision level (upper level). The upper-level optimization problem is optimized by using a decomposition-based evolutionary algorithm and the other-level optimization problems are optimized by a greedy algorithm. Simulation results demonstrated that this approach can provide effective solutions to the location of CS quickly and effectively.

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Location planning of electric vehicle charging stations based on a multi-objective three-level optimization model

Semantic Scholar · Engineering · 2022

Abstract

The construction of electric vehicle (EV) charging stations (CSs) plays an important role in promoting the adoption of EVs. This paper mainly solves EVs' charging station location planning problem (CSLP). The CSLP involves various optimization objectives, such as waiting time, driving distance, station construction costs, profits, etc. Currently, most papers select one or two optimization objectives to model and optimize. We formulate the CSLP problem as a multi-objective three-level optimization problem that simultaneously optimizes user waiting time, annual investor profit, user driving distance, and expense. It involves three sub-problems: user-directed decision level (lower level), charging piles number decision level (middle level), and CS location decision level (upper level). The upper-level optimization problem is optimized by using a decomposition-based evolutionary algorithm and the other-level optimization problems are optimized by a greedy algorithm. Simulation results demonstrated that this approach can provide effective solutions to the location of CS quickly and effectively.

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