Abstract
Current research about the application of large scale electric vehicles (EVs) is carried out in two fields: (1) From the aspect of the traffic system, charging navigation technologies were proposed, to improve traffic efficiency and charging convenience of the EV driver. (2) From the aspect of the distribution system, the “smart” charging strategies were developed to optimize charging profile, where power loss of distribution system, voltage limits and load variance were taken into account. However, few studies focused on simultaneous improvement of EV owner’s convenience, traffic system performance, charging station performance and distribution system performance after the application of large scale EVs. In this paper, a multi-objective function considering the performance indices of traffic system and distribution system including road travel speed, traffic flow, charging waiting time, power loss of distribution system and voltage of distribution node is developed to schedule large scale EVs’ charging behaviour and obtain optimal performance of the whole system. Constraints including load capacity of charging stations, charging requirements and endurance mileage of EVs are overall considered, and a method for determining weights of the multi-objective function is discussed. A simulation system is built for verifying the effectiveness of proposed strategy. Simulation results shows that, compared with the usual charging scheduling strategy, average heavy congestion ratio of the district around the charging station in the evening rush hours is reduced from 0.52 to 0.48, the percentage of EVs waiting for charging is reduced from 7.5% to 0.5%, the maximal power loss rate of distribution system is decreased by 3.5%, and the maximal voltage deviation of distribution system is decreased by 3.4% due to the proposed strategy.
Highlights
With the increase of population and development of economy, the consumption of fossil energies increases, and environment worsens
Simulation results shows that, compared with the usual charging scheduling strategy, average heavy congestion ratio of the district around the charging station in the evening rush hours is reduced from 0.52 to 0.48, the percentage of electric vehicles (EVs) waiting for charging is reduced from 7.5% to 0.5%, the maximal power loss rate of distribution system is decreased by 3.5%, and the maximal voltage deviation of distribution system is decreased by 3.4% due to the proposed strategy
Our work provides elementary conclusions that charging scheduling are necessary for both the traffic system and the distribution system with application of large scale EVs, and optimization of the two systems should be performed simultaneously for performance improvement of the whole system
Summary
With the increase of population and development of economy, the consumption of fossil energies increases, and environment worsens. Charging path planning technologies that merely considered EVs’ drivers’ convenience might result in local traffic congestion around the charging stations as well as severe power loss and voltage deviation of distribution system. A distinguished charging scheduling strategy is proposed for large scale EVs, which can improve traffic efficiency, reduce the charging waiting time of the driver, and reduce power loss and voltage deviation of distribution system. Indices such as road travel speed, traffic flow, charging waiting time, power loss of distribution system and voltage of distribution node are calculated for real-time estimation of performance of the traffic system and distribution system On this basis, a multiobjective optimization function is developed to schedule large scale EVs’ charging behaviour, constraints including load capacity of charging stations, charging requirements and endurance mileage of EVs are considered.
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