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Electrical network capacity support from demand side response: Techno-economic assessment of potential business cases for small commercial and residential end-users

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  • Martínez Ceseña, Eduardo A.
  • Good, Nicholas
  • Mancarella, Pierluigi

Abstract

Demand Side Response (DSR) is recognised for its potential to bring economic benefits to various electricity sector actors, such as energy retailers, Transmission System Operators (TSOs) and Distribution Network Operators (DNOs). However, most DSR is provided by large industrial and commercial consumers, and little research has been directed to the quantification of the value that small (below 100kW) commercial and residential end-users could accrue by providing DSR services. In particular, suitable models and studies are needed to quantify potential business cases for DSR from small commercial and residential end-users. Such models and studies should consider the technical and physical characteristics of the power system and demand resources, together with the economic conditions of the power market. In addition, the majority of research focuses on provision of energy arbitrage or ancillary services, with very little attention to DSR services for network capacity support. Accordingly, this paper presents comprehensive techno-economic methodologies for the quantification of three capacity-based business cases for DSR from small commercial and residential end-users. Case study results applied to a UK context indicate that, if the appropriate regulatory framework is put in place, services for capacity support to both DNOs and TSOs can result into potentially attractive business cases for DSR from small end-users with minimum impact on their comfort level.

Suggested Citation

  • Martínez Ceseña, Eduardo A. & Good, Nicholas & Mancarella, Pierluigi, 2015. "Electrical network capacity support from demand side response: Techno-economic assessment of potential business cases for small commercial and residential end-users," Energy Policy, Elsevier, vol. 82(C), pages 222-232.
    • Handle: RePEc:eee:enepol:v:82:y:2015:i:c:p:222-232
    DOI: 10.1016/j.enpol.2015.03.012
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    9. Good, Nicholas & Ellis, Keith A. & Mancarella, Pierluigi, 2017. "Review and classification of barriers and enablers of demand response in the smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 57-72.
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    11. Ayman Esmat & Julio Usaola & Mª Ángeles Moreno, 2018. "A Decentralized Local Flexibility Market Considering the Uncertainty of Demand," Energies, MDPI, vol. 11(8), pages 1-32, August.
    12. Devine, Mel T. & Bertsch, Valentin, 2018. "Examining the benefits of load shedding strategies using a rolling-horizon stochastic mixed complementarity equilibrium model," European Journal of Operational Research, Elsevier, vol. 267(2), pages 643-658.
    13. Bertsch, Valentin & Devine, Mel & Sweeney, Conor & Parnell, Andrew C., 2018. "Analysing long-term interactions between demand response and different electricity markets using a stochastic market equilibrium model," Papers WP585, Economic and Social Research Institute (ESRI).
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