Title :
Regulating power from supermarket refrigeration
Author :
O´Connell, Niamh ; Madsen, Henrik ; Pinson, Pierre ; O´Malley, Mark ; Green, Torben
Author_Institution :
Dept. of Appl. Math. & Comput. Sci., Tech. Univ. of Denmark, Lyngby, Denmark
Abstract :
This paper presents an analysis of the demand response capabilities of a supermarket refrigeration system, with a particular focus on the suitability for participation in the regulating power market. An ARMAX model of a supermarket refrigeration system is identified using experimental data from the Danfoss refrigeration test centre. The complexities of modelling demand response are demonstrated through simulation. Simulations are conducted by placing the identified model in a direct-control demand response architecture, with power reference tracking using model predictive control. The energy-limited nature of demand response from refrigeration is identified as the key consideration when considering participation in the regulating power market. It is demonstrated that by restricting the operating regions of the supermarket refrigeration system, a simple relationship can be found between the available up- or down-regulation power, and the duration for which the service can be sustained. The available demand response resource within these operational restrictions is reduced from the optimised physical capabilities. The benefit of these restrictions is that the available demand response can be represented in a manner that is sufficiently simple to communicate to a market operator in the form of a bid for the provision of regulating power.
Keywords :
demand side management; power control; power markets; predictive control; refrigeration; ARMAX model; Danfoss refrigeration test centre; demand response capabilities; demand response modelling; direct-control demand response architecture; down-regulation power; energy-limited nature; model predictive control; operational restrictions; power market regulation; power reference tracking; supermarket refrigeration system; up-regulation power; Data models; Load management; Mathematical model; Power demand; Predictive models; Steady-state; Demand Response; Electricity Markets; Regulating Power; Smart Grid; Time Series Analysis;
Conference_Titel :
Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2014 IEEE PES
Conference_Location :
Istanbul
DOI :
10.1109/ISGTEurope.2014.7028781