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In this Paper, Unit commitment integration with vehicle-to-grid and Renewable Energy Resources (UC-V2G-RES) is developed. The aim of this study is to provide a cost-emission reduction solution to the smart grid. The proposed solution comprised of four steps: data clustering, economic load dispatching, sources’ variables optimization and cost-emission values calculation. The Optimization is done using Genetic Algorithm (GA) to fulfill a large number of practical constraints, meet the forecast load demand calculated in advance, plus spinning reserve requirements at every time interval such that the total cost and emissions are minimum. It includes intelligently scheduling on/off states of existing generating units and large number of gridable vehicles with V2G technology in addition to time varying RESs during a full day (24 Hours). The results obtained validated to a reasonable extent the effectiveness of integrating V2G and RESs with the smart grid. The analysis and results are presented and discussed.

Combining both Plug-in Vehicles and Renewable Energy Resources for Unit Commitment studies in Smart Grid