Abstract
Many countries or regions are committed to reducing emissions in response to global climate issues. As an industry with a large proportion of emissions, power generation companies are facing increasing pressure to reduce emissions. Based on the Membrane Search Algorithm (MSA) designed by us, this paper proposes a multi-objective problem-solving algorithm, denoted as multi-objective MSA (MOMSA), in which the constrain-handling rules are designed to solve the Combined Heat and Power Economic Emission Dispatch (CHPEED) problem in a nonconvex and nonlinear space. The proposed method obtains the Pareto front of CHPEED 5-unit and 7-unit systems, and the recommended compromise solution has fewer emissions for the same fuel cost. In addition, the extremely challenging ultra large scale Combined Economic Emission Dispatch (CEED)problem is also studied, and the fuel cost and emissions of the compromise solution are more competitive. The research results show that MOMSA has excellent space exploration ability and can provide better emission reduction dispatching for CEED and CHPEED problems without complex parameter optimization.
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