Providing Grid Services With Heat Pumps: A Review

Lee, Zachary E.; Sun, Qiao; Ma, Zhao; MacDonald, Jason; Zhang, K. Max

doi:10.1115/1.4045819

Cited by 20 publications

(20 citation statements)

References 86 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The question remains how to trigger the higher power deviations promised by capacity bounds (5), (6). Indeed, not a high switching rate itself causes peak load deviations, but its derivative or rate of change achieves it by skewing the TSP slopes and thereby distorting the on-to-off fractions, as shown in Figure 6.…”

Section: Stationary and Zero-order Boundsmentioning

confidence: 99%

“…Therefore, the main target of flexible HVAC is short-term demand response (DR).Working examples now exist in many parts of the world including Europe, the USA, and China. [2][3][4][5][6] Large commercial buildings have been providing dynamic regulation services on USA energy markets since 2011 and get payed for performance (Pennsylvania-New Jersey-Maryland [PJM] [7] ). Many small residential systems pooled together, especially thermostatically controlled loads (TCLs), can provide similarly good load balancing services.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Characterization of Aggregated Building Heating, Ventilation, and Air Conditioning Load as a Flexibility Service Using Gray‐Box Modeling

2021

View full text Add to dashboard Cite

Integrating large amounts of volatile renewable power into the electricity grid requires ancillary services (ASs) from multiple providers including flexible demand. These should be comparable by uniform and efficiently evaluable performance criteria. The objective is to characterize the technical flexibility of aggregated building heating, ventilation, and air conditioning (HVAC) under different operating conditions. New bounds of flexible power and holding durations, accordingly pay‐back power and recovery times, and ramping rates are derived, using a new gray‐box model of stochastically actuated aggregations of thermostatically controlled loads (TCLs) that can serve as well for load control. New closed formulas of the expected switching temperatures are derived using survival processes and hazard functions. This ex‐ante characterization enables fast decision tools for AS feasibility testing and planning by demand aggregators, as it neither relies on simulation or optimization, nor on the identification and clustering of unit‐level parameters. The estimates are explored in a sensitivity study of urban‐level heat pump heating with respect to six key input factors. A case study using dynamic regulation signals from Pennsylvania–New Jersey–Maryland (PJM) demonstrates the benefit, in terms of tracking precision, of the refined energy measures over pure energy or power capacity bounds.

show abstract

Section: Stationary and Zero-order Boundsmentioning

confidence: 99%

mentioning

confidence: 99%

Characterization of Aggregated Building Heating, Ventilation, and Air Conditioning Load as a Flexibility Service Using Gray‐Box Modeling

2021

View full text Add to dashboard Cite

show abstract

“…Remark 6. From the individual TCL's perspective, implementing grid support randomized policies of the form (31)-(32) is straightforward: (i) the TCL measures its current temperature and on/off status, (ii) the TCL "bins" this temperature value according to (18) and (iii) the TCL flips a coin to decide its next on/off state according to the probabilities given in (31)-(32). Note that the thermostat policy is a special case of the grid support control policy, and both policies enforce the temperature constraint.…”

Section: Ba Control Command = Policymentioning

confidence: 99%

“…Thermostatically controlled loads (TCLs) -such as residential air conditioners, heat pumps, and water heaters -are recognized to be valuable sources of flexible demand [4,6,23,18]. For an air conditioner or a heat pump, baseline demand is largely dictated by ambient weather conditions.…”

mentioning

confidence: 99%

A unified framework for coordination of thermostatically controlled loads

Coffman¹,

Bušíć²,

Barooah³

2021

Preprint

View full text Add to dashboard Cite

A collection of thermostatically controlled loads (TCLs) -such as air conditioners and water heaters -can vary their power consumption within limits to help the balancing authority of a power grid maintain demand supply balance. Doing so requires loads to coordinate their on/off decisions so that the aggregate power consumption profile tracks a grid-supplied reference. At the same time, each consumer's quality of service (QoS) must be maintained. While there is a large body of work on TCL coordination, there are several limitations. One is that they do not provide guarantees on the reference tracking performance and QoS maintenance. A second limitation of past work is that they do not provide a means to compute a suitable reference signal for power demand of a collection of TCLs. In this work we provide a framework that addresses these weaknesses. The framework enables coordination of an arbitrary number of TCLs that: (i) is computationally efficient, (ii) is implementable at the TCLs with local feedback and low communication, and (iii) enables reference tracking by the collection while ensuring that temperature and cycling constraints are satisfied at every TCL at all times. The framework is based on a Markov model obtained by discretizing a pair of Fokker-Planck equations derived in earlier work by Malhame and Chong [21]. We then use this model to design randomized policies for TCLs. The balancing authority broadcasts the same policy to all TCLs, and each TCL implements this policy which requires only local measurement to make on/off decisions. Simulation results are provided to support these claims.

show abstract

“…VES from flexible loads can be less expensive than energy storage from batteries [2]. Some examples of flexible loads include residential air conditioners [3], water heaters [4], refrigerators, commercial HVAC systems [5], pumps for irrigation [6], pool cleaning [7] or heating [8].…”

Section: Introductionmentioning

confidence: 99%

Characterizing capacity of flexible loads for providing grid support

Coffman¹,

Zhang²,

Barooah³

2020

Preprint

View full text Add to dashboard Cite

Flexible loads are a resource for the Balancing Authority (BA) of the future to aid in the balance of supply and demand in the power grid. Consequently, it is of interest for a BA to know how much flexibility a collection of loads has, so to successfully incorporate flexible loads into grid level resource allocation. Loads' flexibility is limited by all their Quality of Service (QoS) requirements. In this work we present a characterization of capacity for a collection of flexible loads. This characterization is in terms of the Power Spectral Density (PSD) of the reference signal. Two advantages of our characterization are: (i) it easily allows for a BA to use the characterization for resource allocation of flexible loads and (ii) it allows for precise definitions of the power and energy capacity for a collection of flexible loads.

show abstract

Providing Grid Services With Heat Pumps: A Review

Cited by 20 publications

References 86 publications

Characterization of Aggregated Building Heating, Ventilation, and Air Conditioning Load as a Flexibility Service Using Gray‐Box Modeling

Characterization of Aggregated Building Heating, Ventilation, and Air Conditioning Load as a Flexibility Service Using Gray‐Box Modeling

A unified framework for coordination of thermostatically controlled loads

Characterizing capacity of flexible loads for providing grid support

Contact Info

Product

Resources

About