Abstract
In order to effectively improve the utilization rate of solar energy resources and to develop sustainable urban efficiency, an integrated system of electric vehicle charging station (EVCS), small-scale photovoltaic (PV) system, and battery energy storage system (BESS) has been proposed and implemented in many cities around the world. This paper proposes an optimization model for grid-connected photovoltaic/battery energy storage/electric vehicle charging station (PBES) to size PV, BESS, and determine the charging/discharging pattern of BESS. The multi-agent particle swarm optimization (MAPSO) algorithm solves this model is solved, which combines multi-agent system (MAS) and the mechanism of particle swarm optimization (PSO). In this model, a load simulation model is presented to simulate EV charging patterns and to calculate the EV charging demand at each time interval. Finally, a case in Shanghai, China is conducted and three scenarios are analyzed to prove the effectiveness of the proposed model. A comparative analysis is also performed to show the superiority of MAPSO algorithm.
Highlights
In order to verify the economy of photovoltaic/battery energy storage/EVCS system (PBES), the other two cases are analyzed in this paper, as follows
In this scenario, the decision variables are the number of batteries, In the proposed model, the objective function is the minimum of cost of electricity (COE), and the decision variables are the number of PV cells and battery energy storage system (BESS) and hourly power of grid electricity purchasing/selling
The mechanism of the particle swarm optimization (PSO) algorithm can promote the rapid transmission of information between agents
Summary
Large-scale penetration of electric vehicles (EV) gives rise to the great need for charging facilities. Electric vehicle charging stations (EVCS) have always been faced with the problem of insufficient land resources or power grid access. PBES solves the problem of distribution network in limited land resources, but it realizes the basic balance between local energy production and energy consumption through energy storage and optimal allocation. It can interact with the utility grid if needed and use battery energy storage system (BESS) to charge EVs, so as to alleviate the impact of charging load on the main grid and improve the energy conversion efficiency. In China, PBES has been rapidly developed in recent years and some pioneering PBES programs were implemented in many cities, such as Shanghai, Nanjing, and Jinzhong, etc
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