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Pricing Bilateral Electricity Trade between Smart Grids and Hybrid Green Datacenters

机译:智能电网和混合绿色数据中心之间的双边电力交易定价

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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.
机译:数据中心需求响应被认为是缓解智能电网所面临的操作不稳定的一种有前途的方法。它在降低峰值负荷方面具有显着的潜力,并有助于整合分布式发电和间歇性能源。这项工作考虑了实时电价以引起需求响应的两个关键方面:(ⅰ)智能电网和具有混合绿色发电功能的大型数据中心之间的双向电流流动。 (ⅱ)大型云系统的地理分布性质,因此服务于云的不同数据中心的智能网格之间的潜在竞争。从多领导者单追随者的角度来看,我们提出了一种针对地理分布的绿色数据中心量身定制的定价方案。在云方面,基于乘法器交替方向(ADMM)的技术,为了追求性能,可伸缩性和鲁棒性,以分布式方式将能源成本降至最低。在智能电网方面,需要定价游戏的实际平衡。为此,我们采用具有均衡约束(MPEC),带有均衡约束(EPEC)和精确线性化的均衡问题的数学编程,将多头单追随者定价博弈转换为可以满足以下条件的混合整数线性程序(MILP):轻松解决。基于跟踪驱动的仿真评估了所提出解决方案的有效性。

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