The optimal configuration of distributed generators for CCHP micro-grid based on double-layer operation strategy and improved NSGA-III algorithm

The micro-grid with combined cooling, heating, and power supply system (CCHP) is a complex integration that assembles various distributed generators (DGs). The motivation of this paper is to select a reasonable configuration of DGs for a CCHP-MG by means of uncertainties models, improved operation strategy and algorithm. The DGs in a CCHP-MG are composed of wind turbine (WT), photovoltaic (PV), battery energy storage (BES) system, biomass gasification (BG), Stirling engine, heat exchanger, absorption chiller, electric heater and cooler. In terms of uncertainties models, the uncertainties of variations in wind speed, solar irradiance, temperature, and load demand are considered with 8760 h of a whole year. The paper proposes a multi-objective optimization model for the CCHP-MG system under three objectives associated with the minimized system cost, greenhouse gas (GHG) emissions and power waste. In this study, the double-layer operation strategy is raised for replacing the conventional objective of loss of energy supply probability (LESP) in the CCHP-MG system. Based on the non-dominated sorting genetic III (NSGA-III) algorithm, methods of 1/8 unit sphere and angular distance are proposed for an improved NSGA-III algorithm (INSGA-III) to increase computational efficiency and avoid local convergence. Finally, the multiple analysis and comparisons demonstrate that the cooperation of the double-layer operation strategy and INSGA-III has better performance with superiorities of economy and reliability. The results in the case study show that the system cost, GHG emission, and energy waste of the selected CCHP-MG system respectively reached 85.23, 72446.7, and 7690.46. The study confirms that the improved operation strategy, INSGA-III algorithm, and multiple analysis framework can be extended to design CCHP-MG system in other places.