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Characterisation and Quantification of Data Centre Flexibility for Power System Support

Mehmet Turker Takci, James Day, Meysam Qadrdan

TL;DR

This paper tackles the problem of data centres (DCs) becoming grid-friendly by quantifying and exploiting their inherent flexibility. It introduces an integrated whole-facility optimization that co-optimises IT workload scheduling, UPS energy storage, and cooling with thermal energy storage under day-ahead price signals to obtain a cost-optimal baseline while simultaneously assessing the facility's dynamic flexibility. The authors present a duration-aware flexibility assessment that computes, for any start time and required power deviation, the maximum feasible duration the DC can sustain the deviation without violating operational, thermal, or recovery constraints, yielding a detailed flexibility envelope. Key findings include a measured 10.02% reduction in operating costs in the cost-minimisation scenario and a rich, heatmap-like representation of flexibility duration across start times and magnitudes, with clear asymmetries between upward and downward flexibility. The work demonstrates how DCs can act as grid-prosumer assets for reserves, frequency response, and price-responsive demand, while offering practical guidance for value stacking and market participation.

Abstract

The rapid growth of data centres poses an evolving challenge for power systems with high variable renewable energy. Traditionally operated as passive electrical loads, data centres, have the potential to become active participants that provide flexibility to the grid. However, quantifying and utilising this flexibility have not yet been fully explored. This paper presents an integrated, whole facility optimisation model to investigate the least cost operating schedule of data centres and characterise the aggregate flexibility available from data centres to the power system. The model accounts for IT workload shifting, UPS energy storage, and cooling system. Motivated by the need to alleviate the increasing strain on power systems while leveraging their untapped flexibility potential, this study makes two primary contributions: (i) an operational optimisation model that integrates IT scheduling, UPS operation, and cooling dynamics to establish a cost optimal baseline operation, and (ii) a duration-aware flexibility assessment that, for any given start time and power deviation, computes the maximum feasible duration from this baseline while respecting all operational, thermal, and recovery constraints. This method characterises the aggregate flexibility envelope. Results reveal a clear temporal structure and a notable asymmetry in flexibility provision: upward flexibility (electricity load reduction) is driven by deferring IT workload, which allows for a secondary reduction in cooling power. Downward flexibility (electricity load increase) relies on increasing power consumption of the cooling system, supported by the TES buffer, and charging the UPS. This framework translates abstract flexibility potential into quantified flexibility magnitude and duration that system operators could investigate for use in services such as reserve, frequency response, and price responsive demand.

Characterisation and Quantification of Data Centre Flexibility for Power System Support

TL;DR

This paper tackles the problem of data centres (DCs) becoming grid-friendly by quantifying and exploiting their inherent flexibility. It introduces an integrated whole-facility optimization that co-optimises IT workload scheduling, UPS energy storage, and cooling with thermal energy storage under day-ahead price signals to obtain a cost-optimal baseline while simultaneously assessing the facility's dynamic flexibility. The authors present a duration-aware flexibility assessment that computes, for any start time and required power deviation, the maximum feasible duration the DC can sustain the deviation without violating operational, thermal, or recovery constraints, yielding a detailed flexibility envelope. Key findings include a measured 10.02% reduction in operating costs in the cost-minimisation scenario and a rich, heatmap-like representation of flexibility duration across start times and magnitudes, with clear asymmetries between upward and downward flexibility. The work demonstrates how DCs can act as grid-prosumer assets for reserves, frequency response, and price-responsive demand, while offering practical guidance for value stacking and market participation.

Abstract

The rapid growth of data centres poses an evolving challenge for power systems with high variable renewable energy. Traditionally operated as passive electrical loads, data centres, have the potential to become active participants that provide flexibility to the grid. However, quantifying and utilising this flexibility have not yet been fully explored. This paper presents an integrated, whole facility optimisation model to investigate the least cost operating schedule of data centres and characterise the aggregate flexibility available from data centres to the power system. The model accounts for IT workload shifting, UPS energy storage, and cooling system. Motivated by the need to alleviate the increasing strain on power systems while leveraging their untapped flexibility potential, this study makes two primary contributions: (i) an operational optimisation model that integrates IT scheduling, UPS operation, and cooling dynamics to establish a cost optimal baseline operation, and (ii) a duration-aware flexibility assessment that, for any given start time and power deviation, computes the maximum feasible duration from this baseline while respecting all operational, thermal, and recovery constraints. This method characterises the aggregate flexibility envelope. Results reveal a clear temporal structure and a notable asymmetry in flexibility provision: upward flexibility (electricity load reduction) is driven by deferring IT workload, which allows for a secondary reduction in cooling power. Downward flexibility (electricity load increase) relies on increasing power consumption of the cooling system, supported by the TES buffer, and charging the UPS. This framework translates abstract flexibility potential into quantified flexibility magnitude and duration that system operators could investigate for use in services such as reserve, frequency response, and price responsive demand.

Paper Structure

This paper contains 18 sections, 9 equations, 8 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Data Centre Architecture
  3. IT Workload Background
  4. Literature Review
  5. Methodology
  6. IT Workload Methodology
  7. IT Power Consumption Model
  8. IT Workload Formulation
  9. UPS ESS Mathematical Model and Constraints
  10. Cooling System Model
  11. Case Studies: Integrated DC Model
  12. Scenario 1: Base Cost Calculation
  13. Scenario 2: Cost Minimisation
  14. Scenario 3: Flexibility Duration Calculation
  15. Results
  16. ...and 3 more sections

Figures (8)

  • Figure 1: Data Centre Layout
  • Figure 2: Stacked Proposed Workload Ratios Over 24 Hours
  • Figure 3: Constant Computational Demand ($R$) with Varying CPU Utilisation and Duration
  • Figure 4: (a) Power consumption profile and energy prices over the monitored period. (b) The corresponding IT workload distribution, shown as a stacked bar chart.
  • Figure 5: Optimised DC Component Power Consumption
  • ...and 3 more figures