Wavelet Multivariate Adaptive Regression Splinesand Their Application to the UK Electricity Market

2015-05-16
Yıldırım, Miray Hanım
Bayrak, Özlem Türker
Kestel, Sevtap Ayşe
G Wilhelm, Weber
The growing effect of electricity prices on energy markets appeals for more accurate forecasting techniques since the market suffers from high volatility, high frequency, nonstationarity and multiple seasonality. Aiming at maximum utilities under highly-volatile conditions, both the supplier and the consumer sides seek to monitor and response to the ongoing changes of the electricity prices. In this study, we use a new hybrid approach, called Wavelet - Multivariate Adaptive Regression Splines (W MARS), to forecast day-ahead electricity prices by considering their challenging structures. Here, wavelet transform captures multiple seasonality, unusual behaviors and volatility, whereas MARS eliminates the selection of explanatory variables problem. Hence, W MARS method combines the advantages of Wavelet Transform and Multivariate Adaptive Regression Splines in terms of all prediction performances, computational efforts and learning effects. In contrary to classical regression and time-series techniques, no assumption is required for the data structures or during the implementation process. This new hybrid method overcomes the drawbacks of previously recommended techniques for huge data sets by a fast and automated machine learning method. The performance of the new W MARS method is tested by using United Kingdom electricity market data. That market is characterized by day-ahead forecasting and half-hourly metering. The presentation ends with a conclusion and an outlook to future studies.
5. EURO Working Group Commodities and Financial Modelling Conference, (14 - 16 Mayıs 2015)

Suggestions

Forecasting the Hydro Inflow and Optimization of Virtual Power Plant Pricing
Çabuk, Sezer; Mert, Özenç Murat; Kestel, Sevtap Ayşe; Kalaycı, Erkan (Springer, 2021-01-01)
Hydro inflow forecasting is crucial for effective hydro optimization, virtual power plant pricing, volume risk management, and weather derivatives pricing in the electricity markets. Predicting hydro inflow allows the decision-makers to economically use water for optimal periods, quantify volume risk and determine effective portfolio management strategies. This study aims pricing a hydroelectricity power plant as a Virtual Power Plant based on Turkish energy markets. For pricing of such a non-standard optio...
Multiobjective Optimization of the DC-DC Stage of a Module-Integrated Inverter Based on an Efficiency Usage Model
Mirjafari, Mehran; Balog, Robert S.; Turan, Raşit (Institute of Electrical and Electronics Engineers (IEEE), 2014-05-01)
As photovoltaic (PV) energy continues to gain market penetration due to the lower cost of PV modules, attention is shifting to the balance of system. In this paper, a new efficiency evaluation technique based on a usage model that is synthesized from high-temporal operational data of a PV module is investigated, along with a multiobjective design optimization of the dc-dc stage of a module-integrated inverter. The analysis shows that the technique provides more accurate results than the California Energy Co...
Hydro Inflow Forecasting and Virtual Power Plant Pricing in the Turkish Electricity market
Çabuk, Sezer; Kestel, Sevtap Ayşe; Kalaycı, Erkan (2019-05-23)
Hydro inflow forecasting with most accurate quantitative models is a very crucial subject for effective hydro optimization, virtual power plant pricing, volume risk management and weather derivatives pricing in the Turkish electricity market. Predicting increase or decrease in hydro inflow, seasonal characteristics of hydrological years such as wet, dry or normal, allow the decision-makers to economically use water for optimal periods, quantify of volume risk and determine effective portfolio management str...
Hydro inflow forecasting and virtual power plant pricing in the Turkish electricity market
Çabuk, Sezer; Kestel, Sevtap Ayşe; Danışoğlu, Seza; Department of Financial Mathematics (2016)
Hydro inflow forecasting with most accurate quantitative models is a very crucial subject for effective hydro optimization, virtual power plant pricing, volume risk management and weather derivatives pricing in the Turkish electricity market. Predicting increase or decrease in hydro inflow, seasonal characteristics of hydrological years such as wet, dry or normal, allow the decision makers to economically use water for optimal periods, quantify of volume risk and determine effective portfolio management strat...
Risk Transmission from Oil and Natural Gas Futures to Emerging Market Mutual Funds
Ewing, Bradley T.; Gormus, Alper; Soytaş, Uğur (2018-01-01)
This study evaluates the impacts of energy markets on emerging market mutual funds (EMMFs). In particular, we investigate the volatility transmission between these funds and the oil and natural gas prices. The findings suggest significant risk spillover from the energy markets to EMMFs. Furthermore, we find a large number of EMMFs' risk transmitting to oil prices and almost all of the EMMFs' risk transmitting to natural gas prices. By dividing the sample into two (before and after 2008), we find the EMMFs' ...
Citation Formats
M. H. Yıldırım, Ö. T. Bayrak, S. A. Kestel, and W. G Wilhelm, “Wavelet Multivariate Adaptive Regression Splinesand Their Application to the UK Electricity Market,” presented at the 5. EURO Working Group Commodities and Financial Modelling Conference, (14 - 16 Mayıs 2015), Ankara, Türkiye, 2015, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/78713.