Evaluating the energy-exergy-economy-environment performance of the biomass-photovoltaic-hydrogen integrated energy system based on hybrid multi-criterion decision-making model.

Integrating biomass, photovoltaic, and other renewable energy sources for hydrogen production can form a biomass-photovoltaic-hydrogen integrated energy system (BPH-IES). The system features multi-energy storage and joint supply, as well as cascaded utilization, is a promising co-generation way to meet the system's electricity, heat and hydrogen needs, and has significant energy-exergy-economy-environment (4E) performance. Therefore, scientific and effective evaluation of the BPH-IES is an important prerequisite for promoting its development. Firstly, by analyzing the structure of the BPH-IES system, this paper constructs a comprehensive performance evaluation index system of the system from the 4E dimensions. Secondly, a hybrid multi-criterion decision making (MCDM) framework for the 4E comprehensive performance evaluation of the BPH-IES is constructed, in which the anti-entropy weighting method is used to determine the objective weights, the subjective weights are determined by the decision making trial and evaluation laboratory method improved by intuitionistic fuzzy sets, and the final combined weighting results are obtained based on a game-theoretic method that the objective and subjective weights' heterogeneity can be fully minimized. The grey-relation-analysis-based measurement alternatives and ranking according to the compromise solution method is proposed to determine the ranking of alternatives. This paper selected 8 typical BPH-IES cases for 4E evaluation analysis. The results showed that energy performance is the core dimension that reflects the 4E performance of the system, and system's economy indicators such as energy supply income and energy supply cost will also significantly affect the system's 4E performance. Therefore, the 4E performance of BPH-IES can be effectively improved by expanding the system's demand and supply scale and increasing the system's installed proportion of clean energy and hydrogen penetration. Finally, the ranking consistency test, Leave-One-Out analysis and sample separation test demonstrate that the developed hybrid MCDM can ensure robustness meanwhile improve the decision efficiency. [ABSTRACT FROM AUTHOR]