Optimization of a Multi-Energy Complementary Distributed Energy System Based on Comparisons of Two Genetic Optimization Algorithms

Abstract

The development and utilization of low-carbon energy systems has become a hot topic of energy research in the international community. The construction of a multi-energy complementary distributed energy system (MCDES) is researched in this paper. Based on the multi-objective optimization theory, the planning optimization of an MCDES is studied, and a three-dimensional objective-optimization model is constructed by considering the constraints of the objective function and decision variables. Aiming at the optimization problem of building terminals for the MCDES studied in the paper, two genetic optimization algorithms—Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and Non-Dominated Sorting Genetic Algorithm III (NSGA-III)—are used for calculation based on an example analysis. The constraint conditions of practical problems were added to the existing algorithms. Combined with the comparison of the solution quality and the optimal compromise solution of the two algorithms, a multi-decision method is proposed to obtain the optimal solution based on the Pareto optimal frontier of the two algorithms. Finally, the optimal decision scheme of the example is determined and the effectiveness and reliability of the optimization model are verified. Under the application of the MCDES optimization model studied in this paper, the iteration speed and hypervolume index of NSGA-III are found to be better than those of NSGA-II. The values of the life cycle cost and life cycle carbon emission objectives after the optimization of NSGA-III are indicated as 2% and 14% lower, respectively, than those of NSGA-II. The primary energy efficiency of NSGA-III is shown to be 20% higher than that of NSGA-II. According to the optimal decision, the energy operation strategies of the example MCDES with each typical day in the four seasons indicate that good integrated energy application and low-carbon operation performance are shown during the four-seasons operation process. The consumption of renewable energy is significant, which effectively reduces the application of high-grade energy. Thus, the theoretical guidance and engineering application reference are provided for MCDES design planning and operation optimization.