Abstract
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.
Highlights
Traditional fossil fuels such as coal, oil, and natural gas are the most prominent sources of energy in the 21st century
Some are difficult to express with a specific value, such as storage capacity, which indicates the maximum amount of electricity that the energy storage technology can store
In the approach proposed in this study, experts provided storage requirements information associated with the development of renewable energy for the given use case
Summary
Traditional fossil fuels such as coal, oil, and natural gas are the most prominent sources of energy in the 21st century. The use of traditional fossil energy has promoted global economic development; it has caused serious environmental problems. The development of renewable energy is fundamental to reduce carbon dioxide emissions and solve environmental problems, and it is an important strategy recognized by countries all over the world to deal with atmospheric pollution and resource depletion. Renewable energy-based energy generation depends on the availability of natural resources, which is volatile and intermittent. These characteristics make it difficult to adjust and control power generation, and affect the safe and stable operation of the power grid. Machine learning toward advanced energy storage devices and systems. Machine Learning Based Optimal Energy Storage Devices Selection Assistance for Vehicle Propulsion
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