Data-Driven Planning of Plug-in Hybrid Electric Taxi Charging Stations in Urban Environments: A Case in the Central Area of Beijing
| Autor: | Yinghao Jia, Zuo-Jun Max Shen, Huimiao Chen, Zechun Hu, Guanglei Wu |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Service (systems architecture)
Operations research business.industry Computer science 020209 energy Taxis 02 engineering and technology Demand forecasting Data-driven Beijing Optimization and Control (math.OC) Public transport 0202 electrical engineering electronic engineering information engineering Global Positioning System FOS: Mathematics business Mathematics - Optimization and Control Integer programming |
| Zdroj: | ISGT Europe |
| DOI: | 10.48550/arxiv.1707.07117 |
| Popis: | Plug-in electric vehicles (PEVs) can contribute to the improvement of energy and environmental issues. Among different types of PEVs, plug-in hybrid electric taxis (PHETs) go in advance. In this study, we provide a spatial and temporal PHET charging demand forecasting method based on one-month global positioning system (GPS)-based taxi travel data in Beijing. Then, using the charging demand forecasting results, a mixed integer linear programming (MILP) model is formulated to plan PHET charging stations in the central area of Beijing. The model minimizes both investment and operation costs of all the PHET charging stations and takes into account the service radius of charging stations, charging demand satisfaction and rational occupation rates of chargers. At last, the test of the planning method is carried out numerically through simulations and the analysis is complemented according to the results. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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