Optimum operation management of microgrids with cost and environment pollution reduction approach considering uncertainty using multi‐objective NSGAII algorithm

Generating electricity near the consumption can provide more flexibility to supply various services consumers as well reduce system losses. The limited fossil fuels and air pollution are among main incentives for expansion of this technology. One perspectives proposed effective increase in these resources’ involvement is combine resources with objectives visibility relationship between distributed generation power network, control efficiently. methods combining sources a new concept called micro grid; topic that great importance regard proper management grid aimed costs generating polluting environment. resource completely non-linear top-order problem. In paper, optimum programming has been studied considering capacities available market. order realize this, cost simultaneously, NSGAII multi-objective genetic algorithm used. Studies have conducted form three scenarios on sample consisting solar, wind, turbine, fuel cell battery resources, uncertainty load solar wind generations. probabilistic distribution function (PDF) Roulette Wheel were used create variables uncertainty. first scenario objective was by PSO, GA, ABC algorithms’ optimization. second scenario, reduced studies repeated using algorithms. Finally, third there simultaneous reduction algorithms, taking into account weight coefficients algorithm.