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- Electricity spot prices structural changes in the Iberian electricity marketPublication . Bolas, João; Sousa, Jorge A. M.; Martins, Ana Alexandra; Lagarto, JoãoIn recent years, the power sector has undergone a restructuring process in many economies in the world. This movement towards liberalization led to the establishment of electricity markets that promote the competitiveness of the production and trading segments of the power sector. In these markets, the agents have to deal with frequent electricity price changes leading to different strategies in their daily bidding behavior. There are a set of variables that can have an impact in the electricity price definition, such as: fuel prices, CO 2 emissions prices, electricity production and demand. This paper proposes to analyze structural changes in the Iberian electricity market price between two periods of time: 2007/2008 and 2010/2011. For this purpose, three quantitative analysis methods were used: correlation, causality and Principal Components. Results suggest that the electricity price had a structural change between the analyzed periods, in particular the increasing importance of special regime production.
- 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.
- Optimizing the renewable generation mix in the portuguese power system based on temporal and spatial diversityPublication . Pereira, João Venceslau; Ferreira, Rúben Aires Fonseca Paz; Sousa, Jorge A. M.; Lagarto, João; Martins, Ana AlexandraRenewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.
- Optimizing the renewable generation mix in the Portuguese power system based on temporal and spatial diversityPublication . Pereira, João Venceslau; Ferreira, Rúben Aires Fonseca Paz; Sousa, Jorge A. M.; Lagarto, João; Martins, Ana AlexandraRenewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.
- 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.
- Electricity market price analysis using time series clusteringPublication . Martins, Ana Alexandra; Lagarto, João; Cardoso, Maria MargaridaThe creation of the internal market of electricity has long been a goal of the European Union, for which it has established common rules through the directive 2009/72/EC. In this context, the analysis of electricity markets operation of the different countries that will form the internal market is of the utmost importance. In this work, we use clustering techniques to analyze 26 time series of day-ahead electricity prices from European markets between 2015 and 2018 in order to identify different price patterns. The cluster technique proposed uses a combination of three dissimilarity measures for time series: Euclidean, Pearson correlation based and periodogram based. Results show that there is a clear distinction between Northern markets, especially Nord Pool, and Southern markets, MIBEL and Italy. Moreover, results also show that despite some market prices presenting similar behaviors, a full integrated European electricity market is yet to be accomplished.
- Modeling the strategic behavior of the iberian electricity market producers using time series analysisPublication . Faria, Ricardo; Sousa, Jorge A. M.; Martins, Ana Alexandra; Lagarto, JoãoThe Iberian Electricity Market (MIBEL) emerges in the context of the integration and cooperation between the Portuguese and Spanish electricity markets, in response to the European Union incentive for regional electricity markets creation. The present study, focus on the modeling and forecasting of the hourly competitive strategies of the electricity producers in the MIBEL. For this analysis, the studied variable was the MIBEL's conjectural variation, which estimates the level of competitiveness of the electricity producers on the day-ahead electricity market. The methodology adopted for forecasting was time series analysis, using ARIMA and exponential smoothing models. The results obtained show that the estimated models that best suit the hourly MIBEL conjectural variation forecast were mainly of the ARIMA seasonal type with daily seasonality, followed by ARIMA non-seasonal type models. It was also observed, that the selected models were mainly estimated with a time series of 5 working days.
- 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.
- Short-term load forecasting using time series clusteringPublication . Martins, Ana Alexandra; Lagarto, João; Canacsinh, Hiren; Reis, Francisco; Cardoso, Maria MargaridaShort-term load forecasting plays a major role in energy planning. Its accuracy has a direct impact on the way power systems are operated and managed. We propose a new Clustering-based Similar Pattern Forecasting algorithm (CSPF) for short-term load forecasting. It resorts to a K-Medoids clustering algorithm to identify load patterns and to the COMB distance to capture differences between time series. Clusters' labels are then used to identify similar sequences of days. Temperature information is also considered in the day-ahead load forecasting, resorting to the K-Nearest Neighbor approach. CSPF algorithm is intended to provide the aggregate forecast of Portugal's national load, for the next day, with a 15-min discretization, based on data from the Portuguese Transport Network Operator (TSO). CSPF forecasting performance, as evaluated by RMSE, MAE and MAPE metrics, outperforms three alternative/baseline methods, suggesting that the proposed approach is promising in similar applications.