Aggregate capacity for TCLs providing virtual energy storage with cycling constraints

Coffman, Austin R.; Bušíć, Ana; Barooah, Prabir

doi:10.1109/cdc40024.2019.9028939

Cited by 8 publications

(5 citation statements)

References 27 publications

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“…Since all of these systems can be modeled as a negative load during the steady-state operation, the proposed formulation in this article can be easily extended to include different types of LERs with their operational models and constraints. Similarly, this article can be expanded to include the cycling, and energy quality of service (QoS) constraints of thermostatically controlled loads (TCLs) [30]. Furthermore, the formulation can be easily adapted to include time-shiftable loads such as EVs.…”

Section: ) Contract With Dr-capable Local Energy Resources (Lers)mentioning

confidence: 99%

Demand-Side Participation via Economic Bidding of Responsive Loads and Local Energy Resources

Ostadijafari

Jha

Dubey

2021

IEEE Open J. Power Energy

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The active participation of demand response (DR) resources into the wholesale market price formation and load dispatch process has the potential to stimulate demand-side flexibility. However, it is challenging for a market entity to utilize the DR resources for practical use. This is because day-ahead wholesale market-clearing prices are uncertain, and DR resources are heterogeneous. Furthermore, DR participation may lead to violations of the distribution system's operational constraints. In this article, we propose an approach for an aggregator/load-serving entity (LSE) to profitably bid aggregated DR resources into the day-ahead wholesale market. The LSE requires an optimal bidding strategy that reflects the price elasticity of the aggregated retail loads to participate in the wholesale market operations. In the proposed approach, the LSE executes load curtailment and load shifting contracts with DR resources, where DR resources are remunerated for their participation at pre-contracted incentive prices. Then, the LSE aggregates the DR flexibility and optimally bids it in the day-ahead wholesale market. The proposed approach is validated using the IEEE-123-bus test system. It is demonstrated that the LSE can successfully generate economic bids for its participation in the day-ahead market by optimal management of DR resources and without violating the network's operating constraints.

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Section: ) Contract With Dr-capable Local Energy Resources (Lers)mentioning

confidence: 99%

Demand-Side Participation via Economic Bidding of Responsive Loads and Local Energy Resources

Ostadijafari

Jha

Dubey

2021

IEEE Open J. Power Energy

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“…Other service types, e.g., contingency-type reserve actions that include the precharging of energy storage and the reconnection after service, have been analyzed in the study by Abiri-Jahromi and Bouffard. [40] Coffman et al [41,42] study lockout constraints as well but pursue a different goal named reference planning. A grid balancing authority successively extracts and assigns suitably shaped portions from a residual load signal to those flexible resources that can best handle these according to their capacities.…”

Section: Related Workmentioning

confidence: 99%

“…By supplying capacity bounds as static constraints, TBs support planning and optimization tasks such as the economic dispatch of load and generation units. [35,41] To control and characterize load aggregations dynamically, TCL in fact lend themselves as a model and need no detour via TB or polytope descriptions, because the Fokker-Planck partial differential equation (FPE-PDE) raises their descriptive power to aggregations. [45][46][47][48] The FPE governs the evolution of temperature densities in time.…”

Section: Related Workmentioning

confidence: 99%

“…Roughly speaking, two avenues exist to characterize the flexibility of TCL load aggregates: TBs using geometric aggregation (TB [15,[33][34][35][36][37][38][39][40][41] ), and dynamic analysis of temperature densities or histograms based on the Fokker-Planck equations (FPE, [8,9,[24][25][26][27][45][46][47][48][49][50][51][52]56] ). While the TB approach captures only few criteria, the more versatile FPE requires a costly ex post analysis through simulation or optimization.…”

Section: Summary Of Knowledge Gapsmentioning

confidence: 99%

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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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“…That is, the transition matrix of the state process is a point wise product of two controlled transition matrices. In an optimal control setting, computation of the BA's control command, ζ(t), for reference tracking is a non-convex optimization problem [11]. The probability of turning on when temperature exceeds the upper limit, or off when temperature dips below the lower limit, is set to 1 by design.…”

Section: Literature Review and Contributionmentioning

confidence: 99%

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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Aggregate capacity for TCLs providing virtual energy storage with cycling constraints

Cited by 8 publications

References 27 publications

Demand-Side Participation via Economic Bidding of Responsive Loads and Local Energy Resources

Demand-Side Participation via Economic Bidding of Responsive Loads and Local Energy Resources

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

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