Auction Design for Local Reserve Energy Markets
AbstractIn this paper we develop an auction mechanism that is designed for a local energy market. It aims to enable regionally or virtually restricted trading of ancillary services, which enhances the position of the balance group responsible party beyond that of simple accounting. Furthermore, it makes local market participants somewhat more independent from the transmission grid operator, but at the same time provides incentives for investments in distributed generation technologies. A wider spread of these technologies can help to save CO2 emissions, while at the same time a part of them can also be used to counter the fluctuations of energy from volatile renewable sources, such as wind and solar power. Because of their relatively high margins and small share in total production, ancillary services are well-suited for a remuneration scheme. Participants in the auction are, thus, private households, which imposes specific design characteristics on the auction. Most importantly, it needs to be transparent and easy to understand, as homeowners will typically not have the insights of a professional trader as well as lack a similar position and motivation. Also, the confinement to a single balance group, i.e. a local market, means that especially in the beginning of the trading only a small number of bidders can be expected. Therefore, competition will initially be limited, so that the auction design needs to be adapted accordingly. In order to test the performance of the proposed auction market design under varying information policies, a simple agent-based simulation program has been developed. We find that the theoretical predictions hold and that competition quickly leads to price convergence.
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Bibliographic InfoPaper provided by E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN) in its series FCN Working Papers with number 7/2012.
Length: 42 pages
Date of creation: Jul 2012
Date of revision: Mar 2013
auction; ancillary services; local market; agent-based simulation; distributed generation;
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