Optimal economic/emission power scheduling of renewable energy resources in microgrids with uncertainty

This study proposes a framework for economic–emission dispatch problem (EEDP) in microgrids (MGs). The problem of EEDP aims at finding the optimal scheduling of renewable energy resources (RERs) in isolated and grid-connected MGs. The EEDP is formulated as a non-linear constrained multi-objective optimisation problem. It minimises the total cost and emission simultaneously. Simulation results in nine different cases are conducted to emulate the complexity of the EEDP. Also, the proposed scheduling procedure is tested under abnormal operation of MGs considering unexpected increase in power demand, shortage of battery storage and partial shedding of photovoltaic units. These cases reveal the capability of the proposed method. A multi-objective function is employed to increase the economic benefits and minimise emission issues. In this line, the simulation results are obtained using an enhanced moth-flame optimisation (EMFO) algorithm. The obtained results verified the effectiveness, robustness and global convergence for minimising emission and generation costs. These results are compared with several well-known techniques in the literature. Notable economic and environmental benefits are achieved using the EMFO that lead to flexible scheduling of RERs for MG operation under uncertainty.