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dc.contributor.author
Perfumo, Cristian  
dc.contributor.author
Kofman, Ernesto Javier  
dc.contributor.author
Braslavsky, Julio H.  
dc.contributor.author
Ward, John K.  
dc.date.available
2017-04-11T22:00:14Z  
dc.date.issued
2012-03  
dc.identifier.citation
Perfumo, Cristian; Kofman, Ernesto Javier; Braslavsky, Julio H.; Ward, John K.; Load management: Model-based control of aggregate power for populations of thermostatically controlled loads; Elsevier; Energy Conservation And Management; 55; 3-2012; 36-48  
dc.identifier.issn
0196-8904  
dc.identifier.uri
http://hdl.handle.net/11336/15199  
dc.description.abstract
Large groups of electrical loads can be controlled as a single entity to reduce their aggregate power demand in the electricity network. This approach, known as load management (LM) or demand response, offers an alternative to the traditional paradigm in the electricity market, where matching supply and demand is achieved solely by regulating how much generation is dispatched. Thermostatically controlled loads (TCLs), such as air conditioners (ACs) and fridges, are particularly suitable for LM, which can be implemented using feedback control techniques to regulate their aggregate power. To achieve high performance, such feedback control techniques require an accurate mathematical model of the TCL aggregate dynamics. Although such models have been developed, they appear too complex to be effectively used in control design. In this paper we develop a mathematical model aimed at the design of a model-based feedback control strategy. The proposed model analytically characterises the aggregate power response of a population of ACs to a simultaneous step change in temperature set points. Based on this model, we then derive, and completely parametrise in terms of the ACs ensemble properties, a reduced-order mathematical model to design an internal-model controller that regulates aggregate power by broadcasting temperature set-point offset changes. The proposed controller achieves high LM performance provided the ACs are equipped with high resolution thermostats. With coarser resolution thermostats, which are typical in present commercial and residential ACs, performance deteriorates significantly. This limitation is overcome by subdividing the population into clusters of ACs that receive a coarse-grained, cluster-dependent control signal. The proposed clustering technique recovers the performance achieved with high resolution thermostats at the expense of some additional comfort penalty, which can be quantified using the controller output.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Elsevier  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/  
dc.subject
Demand Side Management  
dc.subject
Load Management  
dc.subject
Air Conditioning  
dc.subject
Internal Model Control  
dc.subject
Load Aggregation  
dc.subject
Control Signal Quantization  
dc.subject.classification
Ingeniería Eléctrica y Electrónica  
dc.subject.classification
Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información  
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS  
dc.title
Load management: Model-based control of aggregate power for populations of thermostatically controlled loads  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2017-04-11T17:42:24Z  
dc.journal.volume
55  
dc.journal.pagination
36-48  
dc.journal.pais
Países Bajos  
dc.journal.ciudad
Amsterdam  
dc.description.fil
Fil: Perfumo, Cristian. CSIRO Energy Technology; Australia. Universidad de Newcastle; Australia  
dc.description.fil
Fil: Kofman, Ernesto Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina  
dc.description.fil
Fil: Braslavsky, Julio H.. CSIRO Energy Technology; Australia  
dc.description.fil
Fil: Ward, John K.. CSIRO Energy Technology; Australia  
dc.journal.title
Energy Conservation And Management  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://doi.org/10.1016/j.enconman.2011.10.019  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0196890411002998