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Biomass energy has extensive application foreground in power generation because of its economic and social benefits. Aiming at selecting the best biomass fuel procurement and storage modes in Jilin province, this paper proposes an evaluation model with linguistic hesitant fuzzy sets (LHFSs), which is good at expressing the hesitancy, inconsistency and uncertainty of subjective evaluation information. Based on cloud model and three entropy principle, the transformation between linguistic hesitant fuzzy sets and comprehensive cloud model is realized. In order to eliminate interdependency among criterion, a new Choquet integral aggregation operator based on the Sigmoid function is proposed. According to the expectation values, the ranking result of aggregated LHFSs is obtained. At last, an illustrative example of modes evaluation in Jilin province is taken in the present study to make the proposed method comprehensible. The result shows that mode 3: farmer + middleman + third-party logistics + power plant, is the most reasonable mode for Jilin biomass energy development. From the perspective of supply chain, middlemen and third party logistics can reduce the procurement and transportation cost in the supply chain, which are two bigger influential factors of fuel cost. Middlemen are not only a bridge between plants and farmers, but also the operator in the supply chain. Through the analysis of the result, suggestions from the perspective of power plants and the government are given. • Linguistic hesitant fuzzy sets are used for evaluating biomass power generation fuel procurement and storage modes. • A multi-criteria decision-making method based on cloud model and Choquet integral is proposed. • A new linguistic hesitant fuzzy aggregation operator based on Choquet integral and the Sigmoid function is presented. • "farmer, middleman, third-party logistics and power plant" is the best mode for Jilin biomass power development. [ABSTRACT FROM AUTHOR]

The distributed energy system (DES) has been regarded as a socio-technical innovation that can improve energy efficiency and reduce carbon emission. Based on the construction and planning of a DES project in Henan Province, this paper aims to develop a comprehensive decision-making framework for selecting the most appropriate DES composition schemes with multi-source heterogeneous data. Thus, a new multi-criteria decision-making method based on fuzzy preference relations and improved Choquet integral is generated. Firstly, an evaluation criteria system is established from economic, technical, environmental and social dimensions, and 10 secondary criteria are presented. Secondly, based on the interval fuzzy preference relations of criteria given by experts, the iteration of weights of criteria is continued until the group consistency degree reaches the threshold. Thirdly, the deviation degree is used to transform the initial data, which include crisp values, interval numbers and linguistic terms to isomorphism data. Thereafter, the fuzzy measures are calculated using Mobius transformation coefficients and the final scores of the alternatives are obtained by means of Choquet integral, which can eliminate the overlap information between criteria. Finally, a real case is given to illustrate the effectiveness of the proposed evaluation criteria and technique. The result shows the multi energy complementary system as the most appropriate alternative for the project, followed by the solar-air source heat pump system, fuel cell system, natural gas system, internal combustion engine system and traditional system. Conclusively, the discussion, comparative analysis and some policy implications to promote the development of distributed energy industry are given. This study not only can assist stakeholders to obtain greater benefits of the DES, but also can serve as a reference for the government towards the development of more robust regulations and policies. • Six different distributed energy system (DES) composition schemes are analyzed. • The fuzzy preference relations are developed with the requirement of consistency degree. • A new decision-making method with multi-source heterogeneous data is proposed. [ABSTRACT FROM AUTHOR]