Controllability and stability of primary frequency control from thermostatic loads with delays

Ziras, Charalampos; Vrettos, Evangelos; You, Shi

doi:10.1007/s40565-016-0262-z

Cited by 16 publications

(7 citation statements)

References 19 publications

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“…In reality, due to the delays distribution, the aggregation will respond more smoothly and with a smaller delay. For this reason we believe that an accurate representation of the dynamics is required, especially when conducting power system stability studies, since it has been shown that relatively small delays combined with fast responses from loads offering PFC can lead to instability [20].…”

Section: Simulation Resultsmentioning

confidence: 99%

Modelling the aggregated dynamic response of electric vehicles

Ziras

You

et al. 2017

2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)

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There is an increasing interest in the use of electric vehicles (EVs) for providing fast frequency reserves due to their large installed capacity and their very fast response. Most works focus on scheduling and optimization and usually neglect their aggregated dynamic response, which is particularly important from the power system perspective when EVs offer significant shares of such services. We present a literature review on the aggregated modelling of EVs and derive analytical expressions for the representation of EV populations based on the probability distributions of their parameters. Such approximations can be used in power system studies, in order to capture the dynamics of an EV population more accurately. Finally, we compare our approach to the most widely used in the literature, i.e. the averaging method where all EVs are represented with the population's average values, and discuss the key differences of the two approaches. Index Terms-Aggregated dynamic response, electric vehicles aggregation, electric vehicles dynamics. C. Ziras, Y. Shi and H.W. Bindner would like to acknowledge the financial support of the EUDP project, Ecogrid 2.0, No 64015-0082.

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Section: Simulation Resultsmentioning

confidence: 99%

Modelling the aggregated dynamic response of electric vehicles

Ziras

You

et al. 2017

2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)

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“…Several performance criteria have been assessed in this framework, e.g., granularity, ramping speed, or payback/recovery needs. [ 9,28,49–52 ] These results often characterize a specific load control algorithm developed and analyzed concomitantly (d), as discussed in the following text.…”

Section: Problem Definition Related Work and Contributionsmentioning

confidence: 91%

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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“…Recent investigations show how power to heat loads could participate in classical frequency regulation markets. The potential of flexible loads, such as refrigerators, to provide primary frequency control (PFC), which requires very fast actuation and response (<30 seconds), has been investigated by serveral authors (e.g., [11], [12]. However, power to heat systems are usually slow and are not able to respond on such short notice, making them more suitable for secondary frequency control (SFC) and tertiary frequency control, depending on the technology used.…”

Section: B Literature Reviewmentioning

confidence: 99%

Use of Model Predictive Control for Short-Term Operating Reserve Using Commercial Buildings in the United Kingdom Context

Bittel

Jones

Parisio

2018

2018 IEEE Conference on Decision and Control (CDC)

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Flexibility, particularly in terms of reserve services, is an essential requirement of power systems with high penetration of renewable electrical generation, which can reduce undesirable curtailment and enable higher integration of clean electrical power from renewable generation. Reserve services are related to additional active power sources available to the grid operator in the form of either increased generation or demand reduction. There is increasing evidence that commercial buildings can provide such reserves. In this paper we present a Model Predictive Control approach to optimization of flexibility afforded by commercial buildings for the provision of reserve services, in particular for Short-Term Operating Reserve from the National Grid in the United Kingdom. This reserve scheme is only required during selected hours of the day and involves turning down consumption for a few hours at the request of the National Grid with a slow response time (≤ 5 minutes). Commercial buildings equipped with heat pumps and backup gas boilers are considered. The proposed robust Model Predictive Control framework enables commercial buildings to provide Short-Term Operating Reserve without compromising the comfort of the occupants. Simulation are performed with a high-fidelity building model derived from Energy Plus through the software OpenBuild including real market data. Results show that a commercial building can provide Short-Term Operating Reserve and yield an economic benefit in a robust manner, without violating the indoor comfort of occupants. CONFIDENTIAL. Limited circulation. For review only.

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Controllability and stability of primary frequency control from thermostatic loads with delays

Cited by 16 publications

References 19 publications

Modelling the aggregated dynamic response of electric vehicles

Modelling the aggregated dynamic response of electric vehicles

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

Use of Model Predictive Control for Short-Term Operating Reserve Using Commercial Buildings in the United Kingdom Context

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