Comparison of the influence of photovoltaic and wind power on the Spanish electricity prices by means of artificial intelligence techinques

The paper analyses and compares the merit order effects of photovoltaic and wind power on final electricity prices in the Spanish spot market and the cost of electricity tariffs. Artificial intelligence techniques are used to model the electricity auction clearing process. Several algorithms are studied before the M5P learning algorithm is finally applied to create a tree model of the spot market. Electricity tariffs for domestic consumers are also recalculated for fictional scenarios with no photovoltaic or wind power production. The conclusion is that the influence of photovoltaic and wind power is uneven. Wind power reduces final electricity prices by €9.10/MWh, generating an overall saving for the system of €364.0 million and for the average domestic consumer of €1.95 using 2012 figures; photovoltaic power reduces electricity prices by €2.18/MWh, generating an overall cost overrun for the system of €2034.1 million and for the average domestic consumer of €38.82.

[1]  Alireza Hajiseyed Mirzahosseini,et al.  Environmental, technical and financial feasibility study of solar power plants by RETScreen, according to the targeting of energy subsidies in Iran , 2012 .

[2]  Ignacio J. Pérez-Arriaga,et al.  Design criteria for implementing a capacity mechanism in deregulated electricity markets , 2008 .

[3]  H. Weigt Germany's Wind Energy: The Potential for Fossil Capacity Replacement and Cost Saving , 2008 .

[4]  Iain MacGill,et al.  High penetration wind generation impacts on spot prices in the Australian national electricity market , 2011 .

[5]  Carlos Batlle,et al.  Security of electricity supply at the generation level: Problem analysis , 2012 .

[6]  Leo Breiman,et al.  Bagging Predictors , 1996, Machine Learning.

[7]  Pedro Linares,et al.  An ex-post analysis of the effect of renewables and cogeneration on Spanish electricity prices , 2011 .

[8]  Pablo del Río González,et al.  Analysing the impact of renewable electricity support schemes on power prices: The case of wind electricity in Spain , 2008 .

[9]  Chi-Keung Woo,et al.  The impact of wind generation on the electricity spot-market price level and variance: The Texas experience , 2011 .

[10]  Réjean Samson,et al.  Assessing the economic value of renewable distributed generation in the Northeastern American market , 2012 .

[11]  Ian H. Witten,et al.  Data mining: practical machine learning tools and techniques with Java implementations , 2002, SGMD.

[12]  J. Aghaei,et al.  Risk constrained self-scheduling of hydro/wind units for short term electricity markets considering intermittency and uncertainty , 2012 .

[13]  Mike Sandiford,et al.  Retrospective modeling of the merit-order effect on wholesale electricity prices from distributed photovoltaic generation in the Australian National Electricity Market , 2013 .

[14]  D. Azofra,et al.  Comparison of the influence of biomass, solar-thermal and small hydraulic power on the Spanish electricity prices by means of artificial intelligence techniques. , 2014 .

[15]  Stine Grenaa Jensen,et al.  Simultaneous attainment of energy goals by means of green certificates and emission permits , 2003 .

[16]  D. Azofra,et al.  Wind power merit-order and feed-in-tariffs effect: A variability analysis of the Spanish electricity market , 2014 .

[17]  Ian H. Witten,et al.  Data mining: practical machine learning tools and techniques, 3rd Edition , 1999 .

[18]  Catalina Gomez-Quiles,et al.  Large-scale wind power integration and wholesale electricity trading benefits: Estimation via an ex post approach , 2012 .

[19]  José M. Martínez-Val,et al.  Collateral effects of renewable energies deployment in Spain: Impact on thermal power plants performance and management , 2011 .

[20]  Ian H. Witten,et al.  Induction of model trees for predicting continuous classes , 1996 .

[21]  M. Genoese,et al.  The merit-order effect: A detailed analysis of the price effect of renewable electricity generation on spot market prices in Germany , 2008 .

[22]  Ron Kohavi,et al.  Wrappers for Feature Subset Selection , 1997, Artif. Intell..

[23]  Geoff Holmes,et al.  Generating Rule Sets from Model Trees , 1999, Australian Joint Conference on Artificial Intelligence.

[24]  Carlos Batlle,et al.  A critical assessment of the different approaches aimed to secure electricity generation supply , 2010 .