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.

The Yangtze River Delta Urban Agglomeration (YRDUA) is the core area for the development of China’s digital economy. This paper constructed a five-dimensional evaluation index system and measured the digital economy development level of the YRDUA. A modified gravity model social network analysis was applied to analyze the structure of the digital economy network. The results show that (1) the level of digital economy in the YRDUA has increased during 2011–2021, with Hangzhou having the highest digital economy development level of 0.513 in 2021. (2) The digital economy network density of the YRDUA increased from 0.155 in 2011 to 0.158 in 2016, and then decreased to 0.151 in 2021, showing an “inverted U-shaped” trend of first increasing and then decreasing. (3) Shanghai, Suzhou, Nanjing, Hangzhou, and Wuxi play the role of “bridge” in the digital economy network, and the pattern of linkage development of neighboring cities driven by the central cities of Shanghai, Nanjing, Suzhou, Hangzhou, Ningbo, and Hefei has basically formed. These findings of the study provide data support and reference for the coordinated development of the digital economy in the YRDUA and are of theoretical and practical significance for the synergistic development of cities.

Low-carbon urban transformation is considered the path to green economic growth in dual-carbon contexts. The low-carbon city pilot policy (LCCP) in China has vast potential to enhance the integrated development of the economy, energy, and environment (3Es). Taking 240 cities in China from 2005 to 2019 as research samples, this paper investigated the impact of LCCP on the integrated development level of the 3Es using the progressive difference-in-differences model and analyzed the mechanisms of influence. In addition, the implementation effects on different cities were analyzed using the triple difference model. The findings show that implementing the LCCP policy significantly improves the 3Es integrated development level in the sample cities, and a variety of robustness tests were used to validate this conclusion. The influence mechanism analysis shows that the primary avenues for pilot programs to contribute and successfully advance the enhancement of the low-carbon city 3Es integrated development level are technological innovation and financial development. Moreover, the heterogeneity analysis of resource endowment and geographical location shows that LCCP is beneficial to the 3Es integrated development in non-resource-based cities and eastern cities. Consequently, policy recommendations include the continuation of low-carbon pilot city expansion, joint promotion of regional 3Es integration, improving the level of technological innovation and financial development, and tailoring of policy to local circumstances. This study provides theoretical support for the evaluation of China’s LCCP and, to a certain extent, proves that the measures taken by China in the process of exploring green economic growth and realizing the dual-carbon goal are correct.