Opportunity Cost Quantification for Ancillary Services Provided by Heating, Ventilating, and Air-Conditioning Systems

Blum, D.; Žakula, Tea; Norford, Leslie K.

doi:10.1109/tsg.2016.2582207

Cited by 30 publications

(15 citation statements)

References 19 publications

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“…The optimal control schedule used as reference or to fulfil the DTU instructions is intuitive and uses minimal effort to satisfy the temperature and power constraints. Consistent with studies such as [11,12], we find that the level of participation in the ancillary service is affected by the dynamics and constraints for the internal temperature, and how well the building manager is remunerated. Figure 1 shows that the building's capacity for DTU depends crucially on the benefit-cost ratio R P , where R is the utilization payment for DTU and P is the night-time price of electricity.…”

Section: Summary and Recommendationssupporting

confidence: 85%

Optimal control of a commercial building's thermostatic load for off-peak demand response

Martyr

Moriarty

Beck

2018

Journal of Building Performance Simulation

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This paper studies the optimal control of a commercial building's thermostatic load during off-peak hours as an ancillary service to the transmission system operator of a power grid. It provides an algorithmic framework which commercial buildings can implement to cost-effectively increase their electricity demand at night while they are unoccupied, instead of using standard inflexible setpoint control. Consequently, there is minimal or no impact on user comfort, while the building manager gains an additional income stream from providing the ancillary service, and can benefit further by pre-conditioning the building for later periods. The framework helps determine the amount of flexibility that should be offered for the service, and cost optimized profiles for electricity usage when delivering the service. Numerical results show that there can be an economic incentive to participate even if the payment rate for the ancillary service is less than the price of electricity.

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Section: Summary and Recommendationssupporting

confidence: 85%

Optimal control of a commercial building's thermostatic load for off-peak demand response

Martyr

Moriarty

Beck

2018

Journal of Building Performance Simulation

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“…This is because the system must create headroom to provide symmetric frequency reserves in either direction, and so the system cannot operate at its temperature that minimizes statedependent losses within a comfortable temperature range. This efficiency penalty has been discussed in other literature as an opportunity cost of providing reserves [17], but is not present in any of the other studies and so is not discussed as an inefficiency mechanism above.…”

Section: A Testing Conditions Assumptions and Resultsmentioning

confidence: 93%

“…Recent work has focused on incremental energy costs in buildings providing DR, with a focus on heating, ventilation and air conditioning (HVAC) systems in commercial buildings. Some papers have identified the additional energy consumption caused by a system diverging from an energy optimal demand schedule to hold reserve capacity [15]- [17], while others focus on the additional energy consumption caused by responding to grid control signals [15], [16], [18]- [23]. This latter group of work employs an analogy between thermal storage in HVAC systems and chemical storage in batteries to evaluate round-trip efficiency (RTE), or the ratio of discharging to charging energy.…”

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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“…A opportunity cost model was given in Ref. [103] that provides a rational goal for optimizing energy consumption, benefit, and ancillary service provision.…”

Section: Economicalmentioning

confidence: 99%

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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Opportunity Cost Quantification for Ancillary Services Provided by Heating, Ventilating, and Air-Conditioning Systems

Cited by 30 publications

References 19 publications

Optimal control of a commercial building's thermostatic load for off-peak demand response

Optimal control of a commercial building's thermostatic load for off-peak demand response

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

Providing Grid Services With Heat Pumps: A Review

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