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  • Optimization of Unit Commitment and Economic Dispatch in Microgrids Based on Genetic Algorithm and Mixed Integer Linear Programming

Optimization of Unit Commitment and Economic Dispatch in Microgrids Based on Genetic Algorithm and Mixed Integer Linear Programming

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Energy Management System (EMS) applications of modern power networks like microgrids have to respond to a number of stringent challenges due to current energy revolution. Optimal resource dispatch tasks must be handled with specific regard to the addition of new resource types and the adoption of novel modeling considerations. In addition, due to the comprehensive changes concerning the multi cell grid structure, new policies should be fulfilled via microgrids' EMS. At the same time achieving a variety of conflicting goals in different microgrids requires a universal and a multi criteria optimization tool. In this work two dispatch-optimizers based on genetic algorithm and mixed integer linear programming for a centralized EMS are introduced which can schedule the unit commitment and economic dispatch of microgrid units. In the proposed methods, different network restrictions like voltages and equipment loadings and unit constraints have been considered.
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