A three-stage geospatial multi-criteria optimization model for location identification of integrated energy service stations from macro market to micro site

Abstract

With the proposal and promotion of the carbon neutrality goal, the number of new energy vehicle (NEV) in China is increasing. However, the lack of supporting infrastructure hinders the rapid development of NEV industry. Policy orientation and construction cost show that it is the most realistic initiative to deploy and build integrated energy service stations (IESS) in existing oil–gas stations. The optimal deployment location of IESS is crucial, which is the strategic decision-making issue of its sustainable development. Therefore, a three-stage geospatial multi-criteria model is proposed to solve the site optimization problem of IESS for the first time. The model realizes the quantitative analysis from macro scale (market demand) to micro scale (specific site). Firstly, various analysis elements involved in the three-stage model are identified, including economy, society, population, market, natural environment, geographical conditions, traffic elements, technical impact. Secondly, the sub-models corresponding to the three stages are described in detail: regional traffic attraction sub-model (stage 1), spatial suitability analysis sub-model (stage 2) and alternative multi-criteria decision analysis (MCDA) sub-model (stage 3). Then, taking Beijing as the layout city, an empirical study is carried out to verify the proposed model. The results show that Haidian, Chaoyang and Fengtai District in Beijing have outstanding traffic attraction, and these three districts are determined as the macro areas giving priority to the layout of IESS. The results of suitability analysis identified 13 oil–gas station sites with suitability exceeding the threshold as alternatives. The results of MCDA show that the station sites B1 and B4 in Chaoyang District and A1 and A2 in Haidian District have the highest layout priority. Finally, the results of layout planning under different decision scenarios are given in the discussion part; Sensitivity analysis and comparative analysis prove the stability and reliability of the model. This study not only provides a practical model for the location optimization of IESS, but also provides a technical reference for transportation departments and decision-makers to layout IESS in the city.