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2018 | OriginalPaper | Buchkapitel

Demand Side Management: A Case for Disruptive Behaviour

verfasst von : Dina Subkhankulova, Artem Baklanov, David McCollum

Erschienen in: Advanced Computational Methods for Knowledge Engineering

Verlag: Springer International Publishing

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Abstract

The UK electricity system is undergoing a significant transformation. Increasing penetration of renewable generation and integration of new consumer technologies (e.g. electric vehicles) challenge the traditional way of balancing electricity in the grid, whereby supply matches demand. Demand-side management (DSM) has been shown to offer a promising solution to the above problem. However, models proposed in literature typically consider an isolated system whereby a single aggregator coordinates homogeneous consumers. As a result potential externalities of DSM are overlooked. This work explores the value of DSM in the context of an interacting electricity system, where utilities compete for cheap electricity in the wholesale market. A stylized model of the UK electricity system is proposed, whereby a traditional supplier competes with a ‘green’ supplier in the wholesale market. The modelling was able to show that with enough dispatchable capacity the traditional supplier was able to benefit from instructing his consumers to increase demand peaks, which had an adverse effect on the system.

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Fußnoten
1
This type of a suppliers represents one of the ‘Big Six’ energy utilities operating in the UK market.
 
2
These companies represent the new entrants in the UK electricity market like Ecotricity and Good Energy.
 
3
This serves as a step for further development of the model where the consumers are able to switch suppliers.
 
4
We use standard residential demand profiles provided by the National Grid [5].
 
5
In order to model the generation capacity of the GS we take historical electricity supply profile from a 1.8 MW wind farm in Wales [9, 10].
 
6
Since the GS does not sell electricity in the market it omits the second term from (2).
 
7
The model code is also available on request.
 
Literatur
8.
Zurück zum Zitat Gan, L., Wierman, A., Topcu, U., Chen, N., Low, S.H.: Real-time deferrable load control: handling the uncertainties of renewable generation. In: Fourth International Conference on Future Energy Systems (E-Energy 2013), pp. 113–124 (2013). http://doi.org/10.1145/2567529.2567553 Gan, L., Wierman, A., Topcu, U., Chen, N., Low, S.H.: Real-time deferrable load control: handling the uncertainties of renewable generation. In: Fourth International Conference on Future Energy Systems (E-Energy 2013), pp. 113–124 (2013). http://​doi.​org/​10.​1145/​2567529.​2567553
17.
Zurück zum Zitat Voice, T., Vytelingum, P., Ramchurn, S., Rogers, A., Jennings, N.: Decentralised control of micro-storage in the smart grid. In: AAAI 2011: Twenty-Fifth Conference on Artificial Intelligence, pp. 1421–1426 (2011). http://eprints.soton.ac.uk/272262/ Voice, T., Vytelingum, P., Ramchurn, S., Rogers, A., Jennings, N.: Decentralised control of micro-storage in the smart grid. In: AAAI 2011: Twenty-Fifth Conference on Artificial Intelligence, pp. 1421–1426 (2011). http://​eprints.​soton.​ac.​uk/​272262/​
18.
Zurück zum Zitat Yang, Z., Li, K., Foley, A., Zhang, C.: Optimal scheduling methods to integrate plug-in electric vehicles with the power system: a review. In: IFAC World Congress, pp. 8594–8603 (2014) Yang, Z., Li, K., Foley, A., Zhang, C.: Optimal scheduling methods to integrate plug-in electric vehicles with the power system: a review. In: IFAC World Congress, pp. 8594–8603 (2014)
Metadaten
Titel
Demand Side Management: A Case for Disruptive Behaviour
verfasst von
Dina Subkhankulova
Artem Baklanov
David McCollum
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-61911-8_5

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