研究目的
To optimize the capacity of the CCHP microgrid to be more economical, safe and reliable, and have more environmental friendliness and energy conservation.
研究成果
The proposed IABC algorithm presents the best performance in both convergence speed and accuracy among the IABC, ABC, WOA, and PSO algorithms under four scheduling strategies. The capacity optimization model comprehensively considers the influence of economy, energy, and environment, and the AHP algorithm integrated with the proposed model can find the appropriate weight values of a multi-objective function successfully.
研究不足
The study focuses on the optimization of capacity allocation in the CCHP microgrid but does not address the potential challenges in real-world implementation such as the variability of renewable energy sources and the complexity of integrating multiple energy systems.
1：Experimental Design and Method Selection:
The study establishes a mathematical model using a multi-objective optimization mechanism for resolving the influence of economy and energy allocation in the mixed photovoltaic type CCHP microgrid. It is based on analytic hierarchy process (AHP) to determine the individual weight of objective function optimization for the multi-objective power capacity allocation. The improved artificial bee colony (IABC) based on the whale search and dynamic selection probability is used to achieve an optimization solution.
2：Sample Selection and Data Sources:
Large hotels in 16 commercial reference buildings published by the U.S. Department of Energy (DOE) were selected as the research carrier to test the operation state of the microgrid system.
3：List of Experimental Equipment and Materials:
The study involves photovoltaic power generation system, micro-gas turbine, battery, thermal storage tank, gas boiler, electric chiller, and adsorption chiller.
4：Experimental Procedures and Operational Workflow:
The proposed IABC algorithm was used to solve the multi-objective optimization model under four different scheduling strategies (FEL, FHL, IFEL, IFHL).
5：Data Analysis Methods:
The performance of the proposed algorithm was compared with WOA, ABC, and PSO algorithms in terms of convergence speed and accuracy.
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