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- Price forecasting in the day-ahead Iberian electricity market using a conjectural variations Arima modelPublication . Lagarto, João; Sousa, Jorge A. M.; Martins, Álvaro; Ferrão, PauloPrice forecast is a matter of concern for all participants in electricity markets, from suppliers to consumers through policy makers, which are interested in the accurate forecast of day-ahead electricity prices either for better decisions making or for an improved evaluation of the effectiveness of market rules and structure. This paper describes a methodology to forecast market prices in an electricity market using an ARIMA model applied to the conjectural variations of the firms acting in an electricity market. This methodology is applied to the Iberian electricity market to forecast market prices in the 24 hours of a working day. The methodology was then compared with two other methodologies, one called naive and the other a direct forecast of market prices using also an ARIMA model. Results show that the conjectural variations price forecast performs better than the naive and that it performs slightly better than the direct price forecast.
- Volatility spillovers in the Iberian electricity marketPublication . Vicente, João; Martins, Ana Alexandra; Lagarto, João; Sousa, Jorge A. M.With the globalization of the world economy, the relationships between commodities, financial and other markets are relevant. Although the electricity market is a more recent kind of market, it is still related with other markets, such as, commodities markets (natural gas, coal, oil), and carbon emissions markets. In this work, we propose to study the interconnections between the day-ahead Iberian electricity market (MIBEL) and the commodities markets, as well as, the carbon emissions markets between 2010 and 2016. To achieve this purpose, we use the Diebold-Yilmaz framework, which proposes measures of the interdependence of returns and volatilities through variance decomposition of forecasted error variances in a generalized vector autoregressive model. Results show that the markets that had a higher influence in MIBEL in the analyzed period were the TTF and Zeebrugge natural gas markets and the markets that MIBEL most influenced were the Coal (API2) and CER market.
- Modeling maximum day-ahead market price using circular statistical methodsPublication . Martins, Ana Alexandra; Lagarto, João; Sousa, Jorge A. M.Electricity day-ahead market price and traded quantity present a distinct pattern between peak and off-peak hours, following a pattern that tends to repeat over a 24-hour time cycle. The cyclic nature of these variables enables the use of circular statistics. Circular statistics is a set of techniques for modelling the random nature of directional data, which are typically expressed as angular measurements, which can be used to analyze any kind of data that are cyclic in nature, such as time-of-day data measured on a 24h clock. In this study, the circular statistical methods are used for analyzing the maximum values of day-ahead market price in the Iberian Electricity Market (MIBEL). The data considered in this study refer to the hourly price of electricity observed in the MIBEL, for Portugal and Spain. Also, variables that have influence on the electricity market prices such as demand, production by technology, namely hydro, coal, CCGT and Special Regime Production (production from CHP, wind, photovoltaic, small hydro, etc.) and the strategic behavior of market participants are also analyzed using circular statistics methods. The analysis performed allowed to conclude that circular statistical methods are a powerful tool to understand market price behavior.
- Modeling of cyclic events in electricity markets using circular statistical methodsPublication . Freitas, Daniel; Martins, Ana Alexandra; Lagarto, JoãoIn the current operation of electricity markets, market price and quantity present a distinct pattern between peak and off-peak hours. This pattern tends to repeat over a 24-hour time cycle. The purpose of this study is to analyze the maximum values of day-ahead market prices, considering the time of day when the maximum values are reached and the respective quantity traded. The cyclical nature of these variables allows the use of circular statistical methods that can be used to analyze any kind of data that are cyclic in nature, like time-of-day data measured on a 24h-clock. This study applies this methodology in analyzing the maximum day-ahead market prices in the Iberian electricity market (MIBEL) between 2012 and 2014 enabling the analysis over the years and between seasons. Results show that circular statistics methods enable to bring important insights into the characterization of electricity market price behavior.