Study of an Optimized Micro-Grid’s Operation with Electrical Vehicle-Based Hybridized Sustainable Algorithm

Recently, the expansion of energy communities has been aided by lowering cost storage technologies and appearance mechanisms for exchanging that is driven economics. An amalgamation different renewable sources, including solar, wind, geothermal, tidal, etc., necessary to offer sustainable smart cities. Furthermore, considering induction large-scale electric vehicles connected regional micro-grid, causes increase in randomness uncertainty load a certain area, solution meets community demands electricity, heating, cooling, transportation while using needed. This paper aims define impact on operation management microgrid hybridized algorithm. First, with use natural attributes such as flexible loads, vehicle response dispatch model constructed. Second, three factors micro-grid operation, management, environmental pollution control costs fluctuation variance are discussed. Third, hybrid gravitational search algorithm random forest regression (GSA-RFR) approach proposed confirm method’s authenticity reliability. The constructed significantly improves smoothness after reduces entire grid. optimization method was solved within 296.7 s, time taken users charge from discharge which economy realizes effective load. weight coefficients ?1 ?2 were found at 0.589 0.421, respectively. study provides key findings suggestions can be useful scholars decisionmakers.