Cooling Devices in Demand Response: A Comparison of Control Methods

Wai, Chon Hou; Beaudin, Marc; Zareipour, Hamidreza; Schellenberg, A.; Liu, Ning

doi:10.1109/tsg.2014.2358579

Cited by 67 publications

(51 citation statements)

References 20 publications

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“…In [20] and [25], parameters such as appliance's thermal conductance, thermal mass, power consumption, coefficient of performance were used to determine the values l, q g (Q g ) of (14).…”

Section: Aggregation Methodology and Heterogeneitymentioning

confidence: 99%

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Human in the loop heterogeneous modelling of thermostatically controlled loads for demand side management studies

Kleidaras

Kiprakis

Thompson

2018

Energy

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Index Terms:Demand side management Demand response Thermostatically controlled loads Markov models a b s t r a c t Demand Response (DR) is a Smart Grid technology aiming to provide demand regulation for dynamic pricing and ancillary services to the grid. Thermostatically controlled loads (TCLs) are among those with the highest potential for DR. Some of the challenges in modelling TCLs is the various factors that affect their duty cycle, mainly human behaviour and external conditions, as well as heterogeneity of TCLs (load parameters). These add an element of stochasticity, with detrimental impact on the aggregated level. Most models developed so far use Wiener processes to represent this behaviour, which in aggregated models, such as those based on Coupled Fokker-Planck Equations (CFPE), have a negligible effect as "white noise". One of the main challenges is modelling the effect of external factors on the state of TCLs' aggregated population and their impact in heterogeneity during operation. Here we show the importance of those factors as well as their detrimental effect in heterogeneity using cold loads as a case study. A bottom up detailed model has been developed starting from thermal modelling to include these factors, real world data was used as input for realistic results. Based on those we found that the duty cycle of some TCLs in the population can change significantly and thus the state of the TCLs' population as a whole. Subsequently, the accuracy of aggregation models assuming relative homogeneity and based on small stochasticity (i.e. Wiener process with typical variance 0.01) is questionable. We anticipate similar realistic models to be used for real world applications and aggregation methods based on them, especially for cold loads and similar TCLs, where external factors and heterogeneity in time are significant. DR control frameworks for TCLs should also be designed with that behaviour in mind and the developed bottom up model can be used to evaluate their accuracy.

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“…In [20] and [25], parameters such as appliance's thermal conductance, thermal mass, power consumption, coefficient of performance were used to determine the values l, q g (Q g ) of (14).…”

Section: Aggregation Methodology and Heterogeneitymentioning

confidence: 99%

“…A comparison of the main methods in summarized in Ref. [25]. It is important to note, that the above mention TCL model originates from Mortensen and Haggerty's work [26]; in general models described by Stochastic Partial Deferential Equations (S-PDE).…”

Section: Introductionmentioning

confidence: 99%

Human in the loop heterogeneous modelling of thermostatically controlled loads for demand side management studies

Kleidaras

Kiprakis

Thompson

2018

Energy

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“…A number of load types are considered as candidates for load shifting. In particular, thermal-electric loads such as building heating and cooling [10], [20], water heating [21], and refrigeration [17]- [19], are considered ideal candidates due to their ability to alter their power consumption while maintaining an acceptable temperature range. These thermal loads share two key characteristics, namely, saturation and rebound.…”

Section: Demand Response Resource Modelmentioning

confidence: 99%

“…A comparative study evaluates the demand response resource when described as a fully observable and controllable system, using a time-series model. The flexible load considered in these case studies is supermarket refrigeration, which has with significant potential for load shifting demand response [17]- [19].…”

Section: Introductionmentioning

confidence: 99%

Economic Dispatch of Demand Response Balancing Through Asymmetric Block Offers

O׳Connell

Madsen

O’Malley

2016

IEEE Trans. Power Syst.

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This paper proposes a method of describing the load shifting ability of flexible electrical loads in a manner suitable for existing power system dispatch frameworks. The concept of an asymmetric block offer for flexible loads is introduced. This offer structure describes the ability of a flexible load to provide a response to the power system and the subsequent need to recover. The conventional system dispatch algorithm is altered to facilitate the dispatch of demand response units alongside generating units using the proposed offer structure. The value of demand response is assessed through case studies that dispatch flexible supermarket refrigeration loads for the provision of regulating power. The demand resource is described by a set of asymmetric blocks, and a set of four blocks offers is shown to offer cost savings for the procurement of regulating power in excess of 20%. For comparative purposes, the cost savings achievable with a fully observable and controllable demand response resource are evaluated, using a time series model of the refrigeration loads. The fully modeled resource offers greater savings; however the difference is small and potentially insufficient to justify the investment required to fully model and control individual flexible loads.Index Terms-Demand-side management, electricity markets, mixed-integer linear programming, refrigeration, time-series analysis. 0885-8950

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“…Most of the theory can be applied to any type of TCL, and simulations have covered many different possible TCL technologies. A variety of control schemes have been proposed, many of which are discussed and compared in [10,19,35]. There are two main classes into which these types of TCL control schemes can be divided: centralised and decentralised control (with a spectrum in between).…”

Section: Introductionmentioning

confidence: 99%

A Stability Analysis of Thermostatically Controlled Loads for Power System Frequency Control

Webborn

MacKay

2017

Complexity

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Thermostatically controlled loads (TCLs) are a flexible demand resource with the potential to play a significant role in supporting electricity grid operation. We model a large number of identical TCLs acting autonomously according to a deterministic control scheme to provide frequency response as a population of coupled oscillators. We perform stability analysis to explore the danger of the TCL temperature cycles synchronising: an emergent phenomenon often found in populations of coupled oscillators and predicted in this type of demand response scheme. We take identical TCLs as it can be assumed to be the worst case. We find that the uniform equilibrium is stable and the fully synchronised periodic cycle is unstable, suggesting that synchronisation might not be as serious a danger as feared. Then detailed simulations are performed to study the effects of a population of frequency-sensitive TCLs acting under real system conditions using historic system data. The potential reduction in frequency response services required from other providers is determined, for both homogeneous and heterogeneous populations. For homogeneous populations, we find significant synchronisation, but very minimal diversity removes the synchronisation effects. In summary, we combine dynamical systems stability analysis with large-scale simulations to offer new insights into TCL switching behaviour.

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Cooling Devices in Demand Response: A Comparison of Control Methods

Cited by 67 publications

References 20 publications

Human in the loop heterogeneous modelling of thermostatically controlled loads for demand side management studies

Human in the loop heterogeneous modelling of thermostatically controlled loads for demand side management studies

Economic Dispatch of Demand Response Balancing Through Asymmetric Block Offers

A Stability Analysis of Thermostatically Controlled Loads for Power System Frequency Control

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