Evaluating demand response opportunities for data centers

Data center demand response is a solution to a problem that is just recently emerging: Today's energy system is undergoing major transformations due to the increasing shares of intermittent renewable power sources as solar and wind. As the power grid physically requires balancing power feed-in and power draw at all times, traditionally, power generation plants with short ramp-up times were activated to avoid grid imbalances. Additionally, through demand response schemes power consumers can be incentivized to manipulate their planned power profile in order to activate hidden sources of flexibility. The data center industry has been identified as a suitable candidate for demand response as it is continuously growing and relies on highly automated processes. Technically, data centers can provide flexibility by, amongst others, temporally or geographically shifting their workload or shutting down servers. There is a large body of work that analyses the potential of data center demand response. Most of these, however, deal with very specific data center set-ups in very specific power flexibility markets, so that the external validity is limited. The presented thesis exceeds the related work creating a framework for modeling data center demand response on a high level of abstraction that allows subsuming a great variety of specific models in the area: Based on a generic architecture of demand response enabled data centers this is formalized through a micro-economics inspired optimization framework by generating technical power flex functions and an associated cost and market skeleton. As part of a two-step-evaluation an architectural framework for simulating demand response is created. Subsequently, a simulation instance of this high-level architecture is developed for a specific HPC data center in Germany implementing two power management strategies, namely temporally shifting workload and manipulating CPU frequency. The flexibility extracted is then monetized on the secondary reserve market and on the EPEX day ahead market in Germany. As a result, in 2014 this data center might have achieved the largest benefit gain by changing from static electricity pricing to dynamic EPEX prices without changing their power profile. Through demand response they might have created an additional gross benefit of 4 of the power bill on the secondary reserve market. In a sensitivity analysis, however, it could be shown that these results are largely dependent on specific parameters as service level agreements and job heterogeneity. The results show that even though concrete simulations help at understanding demand response with individual data centers, the modeling framework is needed to understand their relevance from a system-wide viewpoint

Impact of incentives for greener battery electric vehicle charging - A field experiment

Battery electric vehicles generate a significant share of their greenhouse gas emissions during production and later, when in use, through the energy used for charging. A shift in charging behavior could substantially reduce emissions if aligned with the fluctuating availability of renewable energy. Financial incentives and environmental appeals have been discussed as potential means to achieve this. We report evidence from a randomized controlled trial in which cost-free and “green” charging was advertised via email notifications to customers of a charging service provider. Emails invited to charge during midday hours (11:00 to 15:00) of days with high predicted shares of renewable energy. Results show a significant increase in the number of charging processes in the critical time, and in the amount of energy charged (kWh), despite only marginal monetary savings of 5€ on average. A further increase in kWh charged was observed on weekends. Under the assumption that these charging processes replaced regular overnight charging at home, this represents reduction in CO2 emissions of over 50%

Sim2Win: How simulation can help data centers to benefit from controlling their power profile

To support the grid and integrate renewables, demand response schemes reward the power flexibility of energy consumers. Data centers can profit from this by using power management techniques on all levels of data center architecture: infrastructure, hardware, workload, applications. Even though lately, demand response with data centers has been well researched, most works focus on just one or two techniques and one or two valorization options. This leaves data centers stranded that are not represented by the specific combinations of assumptions and techniques presented in research, and thus a huge potential remains barely touched. To address this challenge, the goal of the presented work is to provide data centers with a framework that can be flexibly instantiated by each data center to assess its individual demand response potential. To achieve this goal, this work presents Sim2Win, a data center simulation framework that can replay any set of different power management strategies in the face of any set of markets for power flexibility. A part of the framework is then instantiated and applied to the workload of a real high-performance data center. It uses workload shifting and frequency scaling in order to market their flexibility on the EPEX spot market and the secondary reserve market in Germany. The results show that by using the inherent flexibility of their power profile on the EPEX spot market the considered data center in 2014 could have earned savings of 7.3% of their power bill

Making data centres fit for demand response: introducing GreenSDA and GreenSLA contracts

The power grid has become a critical infrastructure, which modern society cannot do without. It has always been a challenge to keep power supply and demand in balance; the more so with the recent rise of intermittent renewable energy sources. Demand response schemes are one of the counter measures, traditionally employed with large industrial plants. This paper suggests to consider data centres as candidates for demand response as they are large energy consumers and as they are able to adapt their power profile sufficiently well. To unlock this potential, we suggest a system of contracts that regulate collaboration and economic incentives between the data centre and its energy supplier (GreenSDA) as well as between the data centre and its customers (GreenSLA). Several presented use cases serve to validate the suitability of data centers for demand response schemes.Peer ReviewedPostprint (author's final draft

A Generic Architecture For Demand Response: The ALL4Green Approach

Demand Response is a mechanism used in power grids to manage customers’ power consumption during critical situations (e.g. power shortage). Data centres are good candidates to participate in Demand Response programs due to their high energy use. In this paper, we present a generic architecture to enable Demand Response between Energy Provider and Data Centres realised in All4Green. To this end, we show our three-level concept and then illustrate the building blocks of All4Green’s architectural design. Furthermore, we introduce the novel aspects of GreenSDA and GreenSLA for Energy Provider–Data centre sub-ecosystem as well as Data centre–IT Client sub-ecosystem respectively. In order to further reduce energy consumption and CO2 emission, the notion of data centre federation is introduced: savings can be expected if data centres start to collaborate by exchanging workload. Also, we specify the technological solutions necessary to implement our proposed architectural approach. Finally, we present preliminary proof-of-concept experiments, conducted both on traditional and cloud computing data centres, which show relatively encouraging results