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  5. Inducing truthful revelation of generator reliability
 
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Inducing truthful revelation of generator reliability

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Author(s)
Devine, Mel T. 
Lynch, Muireann Á. 
Uri
http://hdl.handle.net/10197/10969
Date Issued
May 2017
Date Available
12T07:59:47Z August 2019
Abstract
Liberalised electricity markets often include a capacity remuneration mechanism to allow generation firms recover their fixed costs. Various de-rating factors and/or penalties have been incorporated into such mechanisms in order to reward the unit based on the contribution they make to system security, which in turn depends on the unit's reliability. However, this reliability is known to the firm but not to the regulator. We adopt a mechanism design approach for capacity payments based on a declaration by the firm of their reliability. The mechanism scales payments and penalties according to this declared reliability such that the firm's profit-maximising strategy is to truthfully reveal its reliability. A stochastic mixed complementarity problem (MCP) is used to model the interactions between the firms, and we apply this methodology to a test system using Irish electricity market data. Truth-telling is induced, increasing the efficiency of capacity payments while eliminating the requirement for the regulator to allocate resources to discovering reliability.
Sponsorship
Science Foundation Ireland
Other Sponsorship
SRI Energy Policy Research Center
European Regional Development Fund (ERDF)
Type of Material
Journal Article
Publisher
Elsevier BV
Journal
Energy Economics
Volume
64
Issue
Econ. Energy Environ. Policy 2 2 2013
Start Page
186
End Page
195
Copyright (Published Version)
2017 Elsevier
Keywords
  • Capacity payments

  • Reliability

  • Mechanism design

  • Mixed complementarity...

DOI
10.1016/j.eneco.2017.03.017
Language
English
Status of Item
Peer reviewed
ISSN
0140-9883
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Owning collection
Electrical and Electronic Engineering Research Collection
Scopus© citations
1
Acquisition Date
Feb 6, 2023
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Views
654
Acquisition Date
Feb 6, 2023
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Downloads
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Acquisition Date
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