Do commercial buildings become less efficient when they provide grid ancillary services?

Keskar, Aditya; Anderson, David E.; Johnson, Jeremiah X.; Hiskens, Ian A.; Mathieu, Johanna L.

doi:10.1007/s12053-019-09787-x

Cited by 20 publications

(18 citation statements)

References 19 publications

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“…Relatively low RTEs were also found in Ref. [98], where experimentally controlled VAV HVAC systems showed RTEs ranging from 34% to 81%. Both experimental studies relied on open-loop global temperature setpoint control mechanisms, in contrast to the MPC approaches previously discussed.…”

Section: Performance Capacity and Economicssupporting

confidence: 57%

Providing Grid Services With Heat Pumps: A Review

Lee

Sun

et al. 2020

ASME Journal of Engineering for Sustainable Buildings and Cities

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The integration of variable and intermittent renewable energy generation into the power system is a grand challenge to our efforts to achieve a sustainable future. Flexible demand is one solution to this challenge, where the demand can be controlled to follow energy supply, rather than the conventional way of controlling energy supply to follow demand. Recent research has shown that electric building climate control systems like heat pumps can provide this demand flexibility by effectively storing energy as heat in the thermal mass of the building. While some forms of heat pump demand flexibility have been implemented in the form of peak pricing and utility demand response programs, controlling heat pumps to provide ancillary services like frequency regulation, load following, and reserve have yet to be widely implemented. In this paper, we review the recent advances and remaining challenges in controlling heat pumps to provide these grid services. This analysis includes heat pump and building modeling, control methods both for isolated heat pumps and heat pumps in aggregate, and the potential implications that this concept has on the power system.

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Section: Performance Capacity and Economicssupporting

confidence: 57%

Providing Grid Services With Heat Pumps: A Review

Lee

Sun

et al. 2020

ASME Journal of Engineering for Sustainable Buildings and Cities

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“…A "building centric" perspective is to measure a building's total energy consumption over a demand response period, including transient consumption after the requested service is provided, and compare this directly to an estimate of what the building would have consumed in the absence of the service (i.e., a baseline). The difference, defined as Additional Energy Consumption (AEC) in Keskar et al [20], will be positive and large for inefficient building impact. The ratio of AEC to baseline energy consumption provides a normalized efficiency penalty of the DR service.…”

Section: Efficiency Measuresmentioning

confidence: 99%

“…In [18] an illustrative square wave DR event was used to calculate the round trip efficiency, and versions of this service were reproduced in a number of followon studies. These studies -which include both experiments and simulations -report widely varying results, from below 50% RTE [18], [20] to results near 100% or better [16], [19], [21]. The apparent lack of agreement between these works on the efficiency of demand response makes interpretation difficult.…”

Section: Introductionmentioning

confidence: 99%

A Critical Exploration of the Efficiency Impacts of Demand Response From HVAC in Commercial Buildings

MacDonald

Vrettos²,

Callaway

2020

Proc. IEEE

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Increasing quantities of renewable energy generation has yielded a need for greater energy storage capacity in power systems. Thermal storage in variable air volume (VAV) heating, ventilation, and air conditioning (HVAC) in commercial buildings has been identified as a possibly inexpensive source of grid storage, but the true costs are not known. Recent literature explores the inefficiency associated with providing grid services from these HVAC-based demand response resources by employing a battery analogy to calculate round-trip efficiency (RTE). Results vary significantly across studies, and in some cases reported efficiencies are strikingly low. This paper has three objectives to address these prior results. First, we synthesize and expand on insights in existing literature through systematically exploring the potential causes for the discrepancies in results. We reinforce previous work indicating baseline modeling may drive differences across studies, and deduce that control accuracy plays a role in the major differences between experiments and simulation. Second, we discuss why the RTE metric is problematic for demand response applications, discuss another proposed metric, additional energy consumption (AEC), and propose an extension, which we call uninstructed energy consumption (UEC), to evaluate demand response performance. Finally, we explore the merits of different metrics using experimental data and highlight UEC's reduced sensitivity to the characteristics of the demand response signal than previously proposed metrics.

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“…The impacts of VRE, energy storage technologies, and transportation electrification, however, suggest DR may be valuable more frequently at shorter time frames for additional services such as load shifting and ancillary services (Alstone et al, 2017). Importantly, some of this value may be captured through overall increases in electricity consumption to absorb periods of excess VRE or DG (Satchwell et al, 2019;Vrettos et al, 2018) or to maximize value in the case of preconditioning for load shifting and/or modulation (Beil et al, 2015Hammerstrom et al, 2007Keskar et al, 2019).…”

Section: Frameworkmentioning

confidence: 99%

“…The incremental addition of controls enables extended modulation and contingency services, DF, and more consistent participation and overall DR response (Hammerstrom et al, 2007). While efficiency should improve, if participating in utility services more frequently or for longer durations, there may be an overall increase in electricity use due to round-trip losses during pre-conditioning events (e.g., Cole et al [2014] found a ratio of input energy to output energy of 0.61) or frequency regulation events (Keskar et al [2019] found a wide range of round trip efficiencies between 0.34 and 0.81, and Beil et al, [2015] experiments yielded a similar average of 0.46).…”

Section: Appendix a Measure Descriptionsmentioning

confidence: 99%

A Conceptual Framework to Describe Energy Efficiency and Demand Response Interactions

Satchwell

Cappers

Deason

et al. 2020

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Energy efficiency (EE) and demand response (DR) resources provide important utility system and ratepayer benefits. At the same time, the rapid change in the amount and type of variable renewable energy, like solar and wind, is reshaping the role and economic value of EE and DR, and will likely affect time-dependent valuation of EE and DR measures. Utilities are increasingly interested in integrating EE and DR measures and technologies (as well as other distributed energy resources) as a strategic approach to improve their collective cost-effectiveness and performance. However, the specific EE and DR features that may be best integrated, the interplay between changing EE and DR resource potential, and the resulting utility system impacts, are not well understood.

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Do commercial buildings become less efficient when they provide grid ancillary services?

Cited by 20 publications

References 19 publications

Providing Grid Services With Heat Pumps: A Review

Providing Grid Services With Heat Pumps: A Review

A Critical Exploration of the Efficiency Impacts of Demand Response From HVAC in Commercial Buildings

A Conceptual Framework to Describe Energy Efficiency and Demand Response Interactions

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