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Ciarreta, A., Nasirov, S., & Silva, C. (2016). The development of market power in the Spanish power generation sector: Perspectives after market liberalization. Energy Policy, 96, 700–710.
Abstract: This paper provides a comprehensive analysis of the market power problem in the Spanish power generation sector and examines how and to which extent the market has developed in terms of market power concerns after the market liberalization reforms. The methodology applied in this study includes typical ex-post structural and behavioral measures employed to estimate potential for market power, namely: concentration ratios (CR) (for the largest and the three largest suppliers), the Herfindahl-Hirschman Index (HHI), Entropy, Pivotal Supply Index, the Residual Supply Index and Residual Demand Elasticity (RDE). The results are presented for the two largest Spanish generating companies (Endesa and Iberdrola) acting in the Iberian Electricity Market (MIBEL), and in the Spanish Day-ahead electricity market. The results show evidence that these companies have behaved much more competitively in recent periods than in the beginning of the market liberalization. In addition, the paper discusses important structural and regulatory changes through market liberalization processes in the Spanish Day ahead electricity market. (C) 2016 Elsevier Ltd. All rights reserved.
Ciarreta, A., Martinez, B., & Nasirov, S. (2023). Forecasting electricity prices using bid data. Int. J. Forecast., 39(3), 1253–1271.
Abstract: Market liberalization and the expansion of variable renewable energy sources in power systems have made the dynamics of electricity prices more uncertain, leading them to show high volatility with sudden, unexpected price spikes. Thus, developing more accurate price modeling and forecasting techniques is a challenge for all market par-ticipants and regulatory authorities. This paper proposes a forecasting approach based on using auction data to fit supply and demand electricity curves. More specifically, we fit linear (LinX-Model) and logistic (LogX-Model) curves to historical sale and purchase bidding data from the Iberian electricity market to estimate structural parameters from 2015 to 2019. Then we use time series models on structural parameters to predict day-ahead prices. Our results provide a solid framework for forecasting electricity prices by capturing the structural characteristics of markets.& COPY; 2022 The Author(s). Published by Elsevier B.V. on behalf of International Institute of Forecasters. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).