The dynamic assessment method of urban electric vehicle service network's service capability

• Published in: 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2) pp. 1 - 6
• Main Authors: Wang Yang, Zhang Yu, Jin Xiaoling, Li Yixin, Yang Jun, Long Xuemei
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2017
• Subjects: analytic hierarchy process; Charging stations; cloud model comprehensive evaluation method; energy efficiency maximization principle; Estimation; Forecasting; Indexes; support vector machine; Support vector machines; urban electric vehicle service network; Vehicle dynamics
• DOI: 10.1109/EI2.2017.8245317

The urban electric vehicle service network is the basic support system to provide energy for electric vehicle (EV). Evaluation of the service capability of urban EV service network is of great importance to the rational construction of EV service network and the large-scale promotion and the popularization of EVs. This paper, based on the cloud model comprehensive evaluation method and analytic hierarchy process, the three-level nine-index charging station service capability margin index system and the three-level six-index urban charging station weight estimation index system are established. The service capability evaluation of the EV service network is evaluated according to the evaluation result of typical charging station and the weight of the typical charging station in the service network. In order to realize the dynamic evaluation of service network service capability, it is necessary to update the evaluation system parameters in real time according to the development of electric vehicle and the change of charging demand. This paper proposes an EV demand growth model based on the improved grey forecasting method and the support vector machine to predict the number of EVs. Energy efficiency maximization principle is used to predict the charging load of charging stations. According to the charging forecast results of charging stations, the quantitative parameters of the charging piles needed in charging station in the evaluation system are update in real time to form the dynamic assessment system of EVs service network's service capability.