Multi-objective Fuzzy Optimization of a Combined Heating and Power Microgrid Based on Parallel Membrane Computing

In order to address the conflict between operating cost and environmental impact, this paper proposes a parallel membrane computing-based and fuzzy multi-objective optimization approach for solving the dynamic economic dispatch problem in a combined heat and power plant with wind power (CHPEED). By defining membership functions for the generation cost and pollutant gas emissions, the multi-objective problem is fuzzified and transformed into a single-objective nonlinear optimization problem using the maximum fuzzy satisfaction method. The parallel membrane computing strategy is applied to improve the traditional multi-objective optimization approach. To validate the effectiveness of this optimization method, the approach is applied to a 7-unit test system, and simulation results show that considering pollutant gas emissions in the dispatch model can achieve a balanced optimization of economic and emission reduction objectives compared to CHPED without considering environmental factors.