Maximizing Coverage and Reliability: Optimal EV Charging Station and DG Placement in Distribution Networks

marwah alee hammad

Abstract


Distributed generation (DG) and rapid growth in electric vehicles (EVs) necessitate the need for coordinated planning of the charging infrastructure and distributed energy resources (DERs) within distribution networks. Most of the existing studies focus on optimizing the placement of EV charging stations or optimization of DG allocation separately, and some studies have focused on losses of cost or power without jointly considering losses of services coverage and network reliability. Furthermore, the one network topology assessment may not be sufficient to represent radial, meshed and mixed distribution systems. This study suggests a constrained multi-objective framework for simultaneous placement of EV charging stations (EVCSs) and DG units to overcome these drawbacks. The model minimizes total deployment cost, while maximizing the geographical service coverage and network reliability. We use 50 particles and 100 generations of Differential Evolution (DE) using the mutation strategy DE/rand/1, binomial crossover and greedy selection. Geographical siting limits, facility-count constraint, voltage limits, line-loading limits, DG generation limits, EV charging capacity, and power-demand requirements are considered in evaluating candidate solutions. The framework is validated on a 25-node distribution network in radial, mesh and mixed topologies and contrasted to base case and randomly generated deployment solutions. The chosen compromise solution is 75.0% service coverage, 92.0% network reliability with an overall investment cost of US$660,000, comprised of three EV charging stations and two DG units. The objective value achieved was best 0.3940 and 92.0% success rate was reported. The results show the feasibility of coordinated EVCS–DG planning to achieve economic, service and reliability goals in various network configurations.

Keywords


coverage optimization; differential evolution; distributed generation; distribution networks; electric vehicle charging stations; infrastructure planning; multi-objective optimization; reliability analysis; smart grid

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References


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DOI: https://doi.org/10.32520/stmsi.v15i9.6795

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