Characterizing Capacity of Flexible Loads for Providing Grid Support

Coffman, Austin R.; Guo, Zhong; Barooah, Prabir

doi:10.1109/tpwrs.2020.3033380

Cited by 23 publications

(8 citation statements)

References 24 publications

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“…Feasible means that no TCL needs to violate local constraints in order for the collection to track the reference. The topic is sometimes described as "flexibility capacity" and has been examined in many recent works, with various defi-nitions of flexibility [15,25,13,10]. A unified treatment of reference design and coordination algorithm design that would provide a complete framework is lacking.…”

Section: Literature Review and Contributionmentioning

confidence: 99%

“…Since the reference r k (= γ E, * k ) from ( 44) is the best the TCLs can do to help the BA without any TCL having to violate its QoS, Problem (44) therefore also provides an answer to the "aggregate flexibility" question: how much can a collection of TCLs vary their demand while maintaining their local QoS constraints. This question has been investigated by many works [25,13,10,15].…”

Section: Grid Support Policy Designmentioning

confidence: 99%

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A unified framework for coordination of thermostatically controlled loads

Coffman¹,

Bušíć²,

Barooah³

2021

Preprint

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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.

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Section: Literature Review and Contributionmentioning

confidence: 99%

Section: Grid Support Policy Designmentioning

confidence: 99%

A unified framework for coordination of thermostatically controlled loads

Coffman¹,

Bušíć²,

Barooah³

2021

Preprint

Self Cite

View full text Add to dashboard Cite

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“…In addition to [17], [18], there are many works that advocate for the specification of loads' abilities [5], [19] and for resource allocation spectrally [20]. The results of real world VES experiments also suggest that specifying the Fig.…”

Section: Introductionmentioning

confidence: 99%

“…Motivated by the advantages of working in the frequency domain we extend the work in [17], [18] and characterize the capacity through the SD of the reference signal, for an entire collection of flexible loads, based on the QoS requirements of each flexible load. The QoS constraints considered here are quite general and encapsulate operating constraints for: (i) Commercial HVAC systems, (ii) batteries, and (iii) Thermostatically Controlled Loads (TCLs).…”

Section: Introductionmentioning

confidence: 99%

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Characterizing capacity of flexible loads for providing grid support

Coffman¹,

Zhang²,

Barooah³

2020

Preprint

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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.

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

2021

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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.

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Characterizing Capacity of Flexible Loads for Providing Grid Support

Cited by 23 publications

References 24 publications

A unified framework for coordination of thermostatically controlled loads

A unified framework for coordination of thermostatically controlled loads

Characterizing capacity of flexible loads for providing grid support

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

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