Evaluation of Demand Response Systems for Smart Grids: state of the art, value potential and the Hyllie case

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Examensarbete för masterexamen
Master Thesis
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2014
Författare
Holmgren, Ulrika
Mavrikas, Panagiotis
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The thesis is made in order to investigate potentials for reducing or shifting electricity consumption at the demand side. There are many questions none solved within the topic and the aim is to answer some of these questions. The method for reducing or shifting electricity consumption at the demand side is named Demand Response and there are many varieties within the concept. Electricity consumption should be reduced and/or shifted to eliminate GHG emissions, decrease costs, ensure safe electricity supply and enable more integration of renewable intermittencies. There is no such system completed in commercial and large scale projects in Sweden and therefore it is of interest to investigate Demand Response. The project method is literary research and the result comprise of the information and reflections done about Demand Response, in Sweden as well as from international studies. The result also consists of three business models for the role of aggregator in a Demand Response System. Demand Response aggregation is a new concept for the power system and is therefore important to be analyzed. Calculation of saving potentials for residential customers was performed. This calculation shows very small saving potential for customers and the reason for that is lack of regulations and technology to make Demand Response profitable. Learnings from the work is complexity in energy markets, the role of economic incentives for participants, technological possibilities within energy and communication technologies and the great importance of standards and cooperation among organizations. The largest implication was to find relevant information as the topic is comparatively unexplored of today. Behaviour and consumption patterns are aspects that are difficult to foresee and hence the response from higher electricity prices is hard to tell.
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Data- och informationsvetenskap, Computer and Information Science
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