MARKET POWER AND EFFICIENCY IN A COMPUTATIONAL ELECTRICITY MARKET WITH DISCRIMINATORY DOUBLE-AUCTION PRICING
Leigh Tesfatsion (),
Valentin Petrov and
James Nicolaisen
No 18195, Economic Reports from Iowa State University, Department of Economics
Abstract:
This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modified Roth Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.
Keywords: Industrial; Organization (search for similar items in EconPapers)
Pages: 27
Date: 2001
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (99)
Downloads: (external link)
https://ageconsearch.umn.edu/record/18195/files/er52.pdf (application/pdf)
Related works:
Working Paper: Market power and efficiency in a computational electricity market with discriminatory double-auction pricing (2002) 
Working Paper: Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing (2001)
Working Paper: Market Power and Efficiency in a Computational Electricity Market With Discriminatory Double-Auction Pricing (2001) 
Working Paper: Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing (2000) 
Working Paper: Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing (2000) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ags:iowaer:18195
DOI: 10.22004/ag.econ.18195
Access Statistics for this paper
More papers in Economic Reports from Iowa State University, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().