ABSTRACT
Datacenter demand response is envisioned as a promising approach for mitigating operational instability faced by smart grids. It enables significant potentials in peak load shedding and facilitates the incorporation of distributed generation and intermittent energy sources. This work considers two key aspects towards realtime electricity pricing for eliciting demand response: (i) Two-way electricity flow between smart grids and large datacenters with hybrid green generation capabilities. (ii) The geo-distributed nature of large cloud systems, and hence the potential competition among smart grids that serve different datacenters of the cloud. We propose a pricing scheme tailored for geo-distributed green datacenters, from a multi-leader single-follower game point of view. At the cloud side, in quest for performance, scalability and robustness, the energy cost is minimized in a distributed manner, based on the technique of alternating direction of multipliers (ADMM). At the smart grid side, a practical equilibrium of the pricing game is desired. To this end, we employ mathematical programming with equilibrium constraints (MPEC), equilibrium problem with equilibrium constraints (EPEC) and exact linearization, to transform the multi-leader single-follower pricing game into a mixed integer linear program (MILP) that can be readily solved. The effectiveness of the proposed solutions is evaluated based on trace-driven simulations.
- S. A. Gabriel, A. J. Conejo, J. D. Fuller, B. F. Hobbs, and C. Ruiz. Complementarity modeling in energy markets. International Series in Operations Research and Management Science, 180:1--629, 2012. Google ScholarDigital Library
- F. Kong, X. Liu, and L. Rao. GreenPlanning: Optimal Energy Source Selection and Capacity Planning for Green Datacenters. In Proc. of ACM SIGMETRICS, 2014. Google ScholarDigital Library
- Z. Liu, I. Liu, S. Low, and A. Wierman. Pricing Data Center Demand Response. In Proc. of ACM SIGMETRICS, 2014. Google ScholarDigital Library
- Z. Zhou, F. Liu, B. Li, B. Li, H. Jin, R. Zou, and Z. Liu. Fuel Cell Generation in Geo-Distributed Cloud Services: A Quantitative Study. In Proc. of IEEE ICDCS, 2014. Google ScholarDigital Library
- Z. Zhou, F. Liu, Z. Li, and H. Jin. When Smart Grid Meets Geo-distributed Cloud: An Auction Approach to Datacenter Demand Response. In Proc. of IEEE INFOCOM, 2015.Google ScholarCross Ref
Index Terms
- Pricing Bilateral Electricity Trade between Smart Grids and Hybrid Green Datacenters
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