Distributed foresighted energy management in smart-grid-powered cellular networks
journal contributionposted on 22.02.2019 by Xinruo Zhang, Mohammad R. Nakhai, Gan Zheng, Sangarapillai Lambotharan, Jonathon Chambers
Any type of content formally published in an academic journal, usually following a peer-review process.
This paper studies energy management in a smart grid-powered cellular network consisting of an independent system operator (ISO) and multiple geographically distributed aggregators. The aggregators have energy storage devices and can purchase energy from the electric grid via the ISO to serve their users. To account for the uncertainty of the renewable energy supply as well as the impacts of multiple aggregators on the electric grid and energy prices, a foresighted strategy combined with the adaptive ϵ -greedy method is developed for the aggregators to distributively and adaptively minimize the long-term overall cost of the system based on the ahead-of-time decision making of the storage pre-charging amount. Simulation results validate that the proposed strategy surpasses a recent learning-based storage management design and a myopic design.
This work was supported in part by the UK EPSRC under Grant EP/N007840/1 and in part by the Leverhulme Trust under Grant RPG-2017-129.
- Mechanical, Electrical and Manufacturing Engineering