Data sharing in energy systems

Autor: Jianxiao Wang, Feng Gao, Yangze Zhou, Qinglai Guo, Chin-Woo Tan, Jie Song, Yi Wang
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Advances in Applied Energy, Vol 10, Iss , Pp 100132- (2023)
Druh dokumentu: article
ISSN: 2666-7924
DOI: 10.1016/j.adapen.2023.100132
Popis: Big data has been advocated as a dominant driving force to unleash the great waves of the next-generation industrial revolution. While the ever-increasing proliferation of heterogeneous data contributes to a more sustainable energy system, considerable challenges remain for breaking down the barrier of data sharing across monopolistic sectors and fully exploiting data asset value in a trustworthy environment. Here, we focus on a global aspiration and interest regarding the challenges, techniques, and prospects of data sharing in energy systems. In this paper, a conceptual framework for data sharing is designed, in which we introduce the commodity attribute of data assets and explain the bottlenecks of data trading. Two critical issues, i.e., right confirmation and privacy protection, are then systematically reviewed, which provide a fundamental guarantee for credible data openness. A detailed data market is conceived by elaborating on market bids, data asset valuation and pricing strategy, and game-based clearing. Finally, we conduct a discussion about some low-hanging fruit of data sharing in energy systems.
Databáze: Directory of Open Access Journals