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Market Power and Transmission Congestion in the Italian Electricity Market

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  • Simona Bigerna
  • Carlo Andrea Bollino
  • Paolo Polinori

Abstract

Analysis of market power in electricity markets is relevant for understanding the competitive development of the industry’s restructuring and liberalization process, but in the existing literature, there is not an adequate consideration of line transmission congestion. The aim of this paper is to propose a new approach to measuring market power in the Italian Power Exchange (IPEX), explicitly considering transmission line congestion. We construct a new measure of the residual demand curve to disentangle unilateral market power from congestion rent for the main Italian generators during the period April 2004 to December 2007. In Italy, this period was one of stable transmission network structure. Following the approach of Wolak (2003, 2009), we measure the unilateral market power with the Lerner index (LI), computed as the inverse of the residual demand elasticity. In conclusion, the correct modeling of the residual demand curve including transmission congestions enables us to compute the zonal LI and therefore more accurately measure the market power when congestion occurs. Our results show that various generators exercise market power only in specific zones. These findings provide deeper understanding of market outcomes in the presence of congestion, suggesting appropriate policy directions for market surveillance and competition regulation.

Suggested Citation

  • Simona Bigerna & Carlo Andrea Bollino & Paolo Polinori, 2016. "Market Power and Transmission Congestion in the Italian Electricity Market," The Energy Journal, , vol. 37(2), pages 133-154, April.
    • Handle: RePEc:sae:enejou:v:37:y:2016:i:2:p:133-154
    DOI: 10.5547/01956574.37.2.sbig
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    1. repec:aen:journl:2005se-a03 is not listed on IDEAS
    2. Gianfreda, Angelica & Grossi, Luigi, 2012. "Forecasting Italian electricity zonal prices with exogenous variables," Energy Economics, Elsevier, vol. 34(6), pages 2228-2239.
    3. Bosco, Bruno & Parisio, Lucia & Pelagatti, Matteo, 2012. "Strategic bidding in vertically integrated power markets with an application to the Italian electricity auctions," Energy Economics, Elsevier, vol. 34(6), pages 2046-2057.
    4. repec:aen:journl:2007v28-02-a01 is not listed on IDEAS
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