Long term impact of wind power generation in the Iberian day-ahead electricity market price

The Iberian power systems went through important changes at the legal, regulatory and organizational levels in the last 20 years. One of the most relevant ones was the increasing penetration of distributed generation, namely wind parks, together with the development of the common market involving Portugal and Spain. In Portugal, distributed generation is paid using feed in tariffs while in Spain it can choose between receiving a regulated feed in tariff or the market price plus a participation prize. The feed in scheme is now under discussion since it is argued that it represents an excessive cost that is internalized in the end user tariffs. However, this discussion is frequently conducted without complete knowledge of the real impact of wind power on the electricity market price, since it contributes to reduce the demand on the market thus inducing a price reduction. To clarify these issues we used a long term System Dynamics based model already reported in a previous publication to estimate the long term evolution of the market price. This model was applied to the Iberian generation system using different shares of wind power capacity to quantify the impact of wind power on the day-ahead electricity market price.

[1]  Eraldo Banovac,et al.  Analysis of economic characteristics of a tariff system for thermal energy activities , 2007 .

[2]  Jong-Bae Park,et al.  An improved genetic algorithm for generation expansion planning , 2000 .

[3]  J. Forrester System Dynamics and the Lessons of 35 Years , 1993 .

[4]  Fernando Olsina,et al.  Modeling long-term dynamics of electricity markets , 2006 .

[5]  A. Gomes Martins,et al.  A multiple objective mixed integer linear programming model for power generation expansion planning , 2004 .

[6]  Mark Sanford,et al.  Utilizing System Dynamics Modeling to Examine Impact of Deregulation on Generation Capacity Growth , 2005, Proceedings of the IEEE.

[7]  Kadir Erkan,et al.  Power generation expansion planning with adaptive simulated annealing genetic algorithm , 2006 .

[8]  Adelino J. C. Pereira,et al.  Generation expansion planning (GEP) – A long-term approach using system dynamics and genetic algorithms (GAs) , 2011 .

[9]  A. Botterud,et al.  Optimal investments in power generation under centralized and decentralized decision making , 2005, IEEE Transactions on Power Systems.

[10]  J. Keppler,et al.  Projected Costs of Generating Electricity : 2010 Edition , 2010 .

[11]  Jin-Ho Kim,et al.  Generation expansion planning in a competitive environment using a genetic algorithm , 2002, IEEE Power Engineering Society Summer Meeting,.

[12]  V. Kachitvichyanukul,et al.  A New Efficient GA-Benders' Decomposition Method: For Power Generation Expansion Planning With Emission Controls , 2007, IEEE Transactions on Power Systems.

[13]  B. Gorenstin,et al.  Power system expansion planning under uncertainty , 1993 .

[14]  Yixin Ni,et al.  Applications of AI techniques to generation planning and investment , 2004, IEEE Power Engineering Society General Meeting, 2004..

[15]  S. Tesnjak,et al.  Establishing an Efficient Regulatory Mechanism - Prerequisite for Successful Energy Activities Regulation , 2009 .