Integrated Multi-Criteria Model for Long-Term Placement of Electric Vehicle Chargers

Based on the global greenhouse gas (GHG) emissions targets, governments all over world are speeding up adoption of electric vehicles (EVs). However, one key challenges in designing novel EV system is to forecast accurate time for replacement conventional and optimization charging vehicles. Designing infrastructure EVs has many impacts such as stress power network, increase traffic flow, change driving behaviors. Therefore, optimal placement stations most important issues address use In this regard, purpose study present an method choosing locations car Campus long-term planning. The charger problem formulated a complex Multi-Criteria Decision Making (MCDM) which combines spatial analysis techniques, network load flow models, constrained procedures. Analytic Hierarchy Process (AHP) approach used determine weights criteria, while mean distinct each criterion using AHP terms accessibility, environmental effect, indices, impacts. To evaluate effectiveness proposed method, it applied real case Qatar University with collected certain attributes data relevant decision makers inputs linguistic assessments MCDM model. Ranking done by aggregating four techniques: Simple Additive Weighting Method (SAW, Technique Order Preference Similarity Ideal Solution (TOPSIS), Grey Relational Analysis (GRA), Organization Enrichment Evaluations (PROMETHEE-II). A impact secondary output that allows decision-makers their policy findings demonstrate framework can locate station sites. These could also help administrators policymakers make effective choices future planning strategy.