Transactive Operational Framework for Internet Data Centers in Geo-Distributed Local Energy Markets

Internet data centers (IDCs), which can regulate the spatial and temporal load distribution, and manage on-site energy resources, are promising candidates to enhance the connected distribution network's operation. The recent emergence of local energy trading provides a new opportunity for IDCs to trade energy with end energy customers in low-voltage distribution networks and enhance their operational energy efficiency, and this has not been well investigated in the literature. Motivated by this, this paper proposes a two-stage transactive operation framework for a group of geo-distributed IDCs to engage in local energy markets. In the first stage, an ex-ante bidding model is proposed, which optimally schedules the IDCs' cyber-energy resources (computing requests and on-site battery energy storage system) and determines energy trading prices in the local energy markets. The bidding model aims to minimize the cloud service provider (CSP)'s total cost. In the second stage, a real-time energy balancing model is proposed to adjust the IDCs' energy volumes and faciliate them to offer energy balancing services to the power distribution networks in terms of alleviating energy supply-demand imbalances. The coupling relationship among the IDCs' operation strategies, energy trading prices, and energy balancing signals are modeled in the framework. Extensive numerical case studies are implemented to demonstrate the effectiveness of the proposed framework. The simulation results show that the framework can reduce a considerable proportion of total operation cost for networked IDCs and can facilitate the CSP to effectively assist power distribution networks in balancing the energy supply and demand in real-time operation.

Automated summary

This paper proposes a two-stage transactive operation framework for a group of geo-distributed IDCs to engage in local energy markets. In the first stage, an ex-ante bidding model is proposed to optimize the IDCs' cyber-energy resources and determine energy trading prices. In the second stage, a real-time energy balancing model is proposed to adjust the IDCs' energy volumes and offer energy balancing services to power distribution networks.