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Load management of data centers as regulation capacity in Denmark
Replacing the traditional fossil-based electricity generation with clean renewable energy is critical to address carbon emissions and climate change in particular. Denmark has a particularly aggressive strategy for renewable energy generation. By 2020 50% of electricity production is to be wind based and by 2050 the goal is to have an energy production based entirely on renewable energy. Renewable energy such as solar and wind is subject to variations due to changing weather conditions. This requires additional balancing capacity and ancillary services in order to balance the grid for transmission system operators and distribution system operators and balance errors in forecasts made by balance responsible parties. By enabling the demand-side to adapt consumption to match power generation, we can address this in a cost-effective and environmental sound way. In this context, data centers are of special interest as they account for 500 GWh of consumption in Denmark or nearly 2% of the total electricity consumption. This paper performs an analysis on load management capabilities of data centers in Denmark based on the experiences in the U.S. We characterize the load management capabilities of the data centers based on their types, technology, and their application as grid management resources. Further, we identify demand-side entry barriers towards market participation. Our findings suggest that groups of data centers can offer dynamic load flexibility as virtual power plants, and thereby support the evolution of the Danish energy systems towards its 2020 and 2050 goals.
- University of Southern Denmark Denmark
- Lawrence Berkeley National Laboratory United States
- Lawrence Berkeley National Laboratory United States
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).11 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
