Solar Integrated DSTATCOM Based Charging-Stations Planning for EVs Addressing Sustainable Development Goals: Techno-Economic and Environmental

The prompt growth of EVs and their deployment with remarkable greeting in humanity enforced the power system to enlarge because of the surge in demand for power during EV charging and its uncertain charging nature. The incorporation of Solar-Renewable Energy has increased to meet this increased demand. Hence, owing to the inappropriate incorporation of Solar-RE based Distributed Generations (DGs), the system becomes disturbed with increased losses, voltage profile imbalance, poor fault tolerance capability, and reliability issues. Also, it is terrible to fulfill the increased reactive demand of the Distribution Network (DN) by these DGs. Therefore, in this work, to address these issues, the appropriate planning of Solar-RE Integrated DSTATCOM based Charging Stations for EVs with ZIP Load Model is offered in view of the Sustainable Development Goals: Techno-Economic and Environmental challenges. The presented work's effectiveness is established on a 33-bus IEEE DN using PSO and TLBO by optimizing the TEE. The considered techno parameters of the DN are Active Loss (DNP<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</sub>), Reactive Loss (DNQ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</sub>), Voltage Deviation (DNV<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</sub>), Level of Line Short-Circuit/Fault Current (DNLL<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FC</sub>), and Service Reliability (DNS<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub>) which makes up the Multiple-Objective Fitness Problem (MO<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FP</sub>). Similarly, the economic and environmental parameters are the Cost for Fixed Capital Recovery (C<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FCR</sub>), Cost for Energy Lost (C<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EL</sub>), Cost for Energy Not Delivered/Supplied (C<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ENS</sub>), and Environmental Particle Emission (EPE). The planning of SID based CSEV by addressing the SDG concerns is the presented work's unique contribution and novelty. Hence, the result analysis reveals that the proposed Scenario Study-4 (SS4) is superior to SS1, SS2, and SS3 for all LM cases and other existing literature work from SDG challenges viewpoints.