Multi-objective optimization and improvement of multi-energy combined cooling, heating and power system based on system simplification

The multi-objective optimization of combined cooling, heating, and power (CCHP) systems typically focuses on optimizing objective functions that consider energy, environmental, and economic factors. However, the implementation of optimization solutions, which is related to decision variables, is often overlooked. This paper proposes a novel improved optimization method based on system simplification by reorganizing, re-optimizing and re-selecting the initial optimized population to improve decision variables. And created algorithm pseudocode. The improved algorithm is adopted to perform multi-objective optimization on the established multi-energy CCHP system. The hypervolume of the improved/original algorithm is 0.9770/0.9887, with only a 1.18% difference. The optimization results of the improved algorithm and the original algorithm are equal in the minimum values of the net present value (NPV) and fossil energy consumption (FEC), which are 2.26 x 10(7)$ and 1.21 x 10(5)GJ, respectively. There is only 1.4% difference in the carbon dioxide emissions (CDE). The number of equipment types corresponding to the decision variables of the improved algorithm is reduced from 8 to 4, significantly simplifying the systems. The proposed improved optimization method can harness the local energy-saving potential and comprehensively analyze optimization solutions in terms of energy, economy, and environment. It also obtains simplified systems to promote the implementation of the project.

Automated summary

This study proposes an improved optimization method that improves decision variables by reorganizing, re-optimizing, and re-selecting the initial optimized population. The method comprehensively analyzes optimization solutions in terms of energy, economy, and environment and obtains simplified systems to promote project implementation.