Energy storage technologies can reduce grid fluctuations through peak shaving and valley filling and effectively solve the problems of renewable energy storage and consumption. The application of energy storage technologies is aimed at storing energy and supplying energy when needed according to the storage requirements. The existing research focuses on ranking technologies and selecting the best technologies, while ignoring storage requirements. Here, we propose a multi-criteria decision-making (MCDM) framework for selecting a suitable technology based on certain storage requirements. Specifically, we consider nine criteria in four aspects: technological, economic, environmental, and social. The interval number, crisp number, and linguist terms can be transformed into a probabilistic dual hesitant fuzzy set (PDHFS) through the transformation and fusion method we proposed, and a suitable technology can be selected through distance measurements. Subsequently, the proposed method is applied in a representative case study for energy storage technology selection in Shanxi Province, and a sensitivity analysis gives different scenarios for elaboration. The results show that the optimal selection of energy storage technology is different under different storage requirement scenarios. The decision-making model presented herein is considered to be versatile and adjustable, and thus, it can help decision makers to select a suitable energy storage technology based on the requirements of any given use case.

Based on the logistics service supply chain, there are many fuzzy factors in the real market competition environment, and the relationship between them is complicated, in order to make the research more in line with the actual situation. In this paper, the supply capacity of logistics service providers and the demand for logistics service capacity are set as fuzzy variables, and the problem of order allocation of logistics service supply chain under fuzzy environment is studied. Firstly, the problem is described, and the multi-objective logistics service order allocation model with fuzzy parameters is established. Secondly, the credibility theory is used to fuzzed. Finally, the feasibility of the calculation model is verified by a specific example, and the logistics service integrator is used. The order allocation decision provides a theoretical basis.