Nonlinear empirical pricing in electricity markets using fundamental weather factors

• Published in: Energy (Oxford) Vol. 139; pp. 594 - 605
• Main Authors: Mosquera-López, Stephanía, Uribe, Jorge M., Manotas-Duque, Diego Fernando
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 15.11.2017; Elsevier BV
• Subjects: Data processing; Electric power distribution; Electric rates; Electricity; Electricity distribution; Electricity pricing; Empirical analysis; Markets; Pricing; Quantile regression; Quantiles; Regression analysis; Risk; Studies; Weather; Weather; Risk; Electricity; Quantile regression; Pricing
• ISSN: 0360-5442; 1873-6785
• DOI: 10.1016/j.energy.2017.07.181

A nonlinear factor model based on fundamental weather variables, in addition to market-related variables, is proposed for modeling the price of electricity. The full conditional distribution of electricity prices using quantile regressions is modeled and the effect of weather factors on upside and downside risks in the electricity market is analyzed. Data from the Nord Pool is used to fit the proposed model to a wide and highly integrated market, as well as several individual national markets, and to search for possible asymmetries in both individual and aggregated levels of the price dynamics. By doing so, important differences across countries and quantiles in the price responses to weather variations are documented, but mostly extensive evidence in favor of the quantile-factor model based on weather variables is provided. •A nonlinear factor model for electricity prices is proposed.•The model is based on weather factors and it is controlled by market factors.•The effect of weather factors is analyzed across price quantiles.•Wind and temperature have the most significant effects over Nord Pool prices.•Weather asymmetrically affects prices across quantiles and markets.