Optimal Scheduling of CHP-Based Industrial Microgrid

Abstract

Environmental and economic limitations of the conventional power system could be overcome using cutting-edge technologies, such as microgrid. Recently, combined heat and power (CHP) co-generation units in microgrids have widely attracted attention due to the cost effectiveness and pollution reduction. This work presents a non-dominated sorting genetic algorithm (NSGA-II) to solve electricity and heat generation dispatch problem of CHP–based industrial microgrid (IMG) over a 24-hour period. This multi-objective optimization algorithm aims to minimize the overall system cost and pollutant emission simultaneously, with considering network security and photovoltaic (PV) storages constraints. To demonstrate the performance of optimization process, two scenarios are analyzed. The microgrid isolated mode without using PV and the connected mode with using PVs and PV storages are assessed which the later one indicated more enhanced environmental and economic solutions.