A shared energy storage business model for data center clusters considering renewable energy uncertainties. (January 2023)

• Record Type: Journal Article
• Authors: Han, Ouzhu; Ding, Tao; Zhang, Xiaosheng; Mu, Chenggang; He, Xinran; Zhang, Hongji; Jia, Wenhao; Ma, Zhoujun
• Is Part Of: Renewable energy. Volume 202(2023)
• Page Start: 1273
• Page End: 1290
• Publication Date: 2023-01
• Subjects: Shared energy storage business model -- Data center cluster -- Renewable energy uncertainty -- Chance-constrained goal programming; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2022.12.013
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: The energy consumption of data centers (DCs) is on a sharp upward trend in recent years. DCs are playing an increasingly important role in demand response (DR) programs. However, the reassignment of computing tasks among DCs leads to different energy demands of different DCs. Given that the investment cost of energy storage is high, this work proposes a shared energy storage business model for the DC cluster (DCC) to improve economic benefits and promote renewable energy accommodation. Besides, an internal energy balance mechanism is set up to make full use of the complementary energy consumption characteristics of different DCs. Considering the renewable energy uncertainty, an optimization model is proposed based on the chance-constrained goal programming (CCGP). Finally, simulation results prove that the proposed energy storage business model has a positive effect on improving the economic benefits of the DCC. It also proves that for a DCC adopting the proposed internal energy balance mechanism, its total renting power can be effectively reduced and renewable energy consumption can be greatly promoted.