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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Notes
- 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.
- 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.
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Acknowledgments
Part of the research was developed in the Young Scientists Summer Program at the International Institute for Systems Analysis, Laxenburg (Austria) with financial support from the United Kingdoms National Member Organization.
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Subkhankulova, D., Baklanov, A., McCollum, D. (2018). Demand Side Management: A Case for Disruptive Behaviour. In: Le, NT., van Do, T., Nguyen, N., Thi, H. (eds) Advanced Computational Methods for Knowledge Engineering. ICCSAMA 2017. Advances in Intelligent Systems and Computing, vol 629. Springer, Cham. https://doi.org/10.1007/978-3-319-61911-8_5
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