The current work introduces a meta-heuristic solution of an emission constrained optimal generation scheduling problem on the Distributed Energy Resources (DERs). The Combined Economic Emission Dispatch (CEED) problem reflects the environmental effects from the gaseous pollutants from fossil-fueled power generating plants. The CEED is a method for scheduling the generation considering both emission and generation cost meeting the needs of satisfying all operational constraints and load demand as well. The CEED problem has been formulated as a multi-objective problem and that later has been converted into a single objective function using price penalty factor. A comparatively new meta-heuristic nature-inspired global optimization method, Adaptive Wind Driven Optimization (AWDO), has been proposed to solve the CEED problem solution. The key objective is to solve the CEED problem with the proposed algorithm and analyze its effectiveness of with the help of the simulation results which later have been compared with other existing algorithms for two test systems (10 thermal units and 40 thermal units) and AWDO has proved to be the best and most powerful amongst them.
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