Oxford Energy Podcast – Decarbonized Market Design: An Insurance Overlay on Energy Only Electricity Markets
The ECJ’s recent annulment of a 2014 decision by the European Commission not to raise objections to the aid scheme for the capacity market in the United Kingdom has highlighted some of the challenges faced by governments in implementing centralised capacity mechanisms to respond to shortfalls in the market provision of electricity. There are also other issues around using centralised approaches to provide ‘reliability’ against the context of electricity generation becoming increasingly variable and decentralised. First, centralized mechanisms highlight the challenges in decision-making by a central authority, reflected in a misalignment between performance outcomes and agency incentives. This is mainly because the incentives of the government are indirect and non-pecuniary. Second, existing capacity mechanisms require the central agency to infer consumer preferences for reliability, something that is very challenging in practice. Third, the existing mechanism allocates the full costs of reliability related-outages to consumers, without providing them with the ability to manage or transfer the risk to those who are able to mitigate them. Fourth, an equitable allocation of costs of procured capacity among consumers can be challenging, especially when retail tariffs have a strong energy component.
In this podcast Anupama Sen interviews Rahmat Poudineh, Lead Senior Research Fellow of the OIES Electricity Programme, and Farhad Billimoria, Visiting Research Fellow at the OIES and currently with the Australian Energy Market Operator, to discuss their recent paper: “Decarbonized Market Design: An Insurance Overlay on Energy Only Electricity Markets”. The discussion focuses on a new model for electricity market design—the insurer-of-last-resort model—that works as a risk overlay on an existing energy-only market. This model unbundles energy and reliability and incorporates insurance-based risk management concepts with the aims of (1) aligning incentives for centralized decision making and (2) allowing revealed consumer preferences to guide new capacity deployment. The authors take us through the design of their model, and how to implement it in practice.
