Multidimensional Scaling Analysis of Electricity Market Prices
This paper studies the impact of energy and stock markets upon electricity markets using Multidimensional Scaling (MDS). Historical values from major energy, stock and electricity markets are adopted. To analyze the data several graphs produced by MDS are
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Multidimensional Scaling Analysis of Electricity Market Prices Filipe Azevedo and J. Tenreiro Machado
Abstract This paper studies the impact of energy and stock markets upon electricity markets using Multidimensional Scaling (MDS). Historical values from major energy, stock and electricity markets are adopted. To analyze the data several graphs produced by MDS are presented and discussed. This method is useful to have a deeper insight into the behavior and the correlation of the markets. The results may also guide the construction models, helping electricity markets agents hedging against Market Clearing Price (MCP) volatility and, simultaneously, to achieve better financial results.
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Introduction
Electricity is a non-storable product that, associated with the fact that electric power systems must always be balanced, poses special financial challenges. In fact, wide fluctuations in spot prices associated with weather high or low temperatures, can lead to prices climbing up to 1,000% during short periods [1]. The overall behavior is of high volatility, even when compared with the prices that occur in oil, gas and stock markets. A second implication of the electricity non-storability is the impossibility of transferring a certain amount of energy without considering the electric
F. Azevedo (*) INESC TEC - INESC Technology and Science (formerly INESC Porto) and ISEP/IPP - School of Engineering, Polytechnic Institute of Porto, Rua Dr. Anto´nio Bernardino de Almeida, 4200-072 Porto, Portugal Portugal and INESC TEC (formerly INESC Porto), Porto, Portugal e-mail: [email protected]/[email protected] J.T. Machado Institute of Engineering, Department of Electrical Engineering, Polytechnic of Porto (ISEP/IPP), Rua Dr. Anto´nio Bernardino de Almeida, 4200-072 Porto, Portugal e-mail: [email protected] A. Madureira et al. (eds.), Computational Intelligence and Decision Making: Trends and 345 Applications, Intelligent Systems, Control and Automation: Science and Engineering 61, DOI 10.1007/978-94-007-4722-7_32, # Springer Science+Business Media Dordrecht 2013
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transmission constraints. Besides the instantaneous nature of the electricity commodity, factors such as the uncertainty associated with fuel prices, energy demand, generation availability, or even technical restrictions, may have also considerable impact on electricity volatility [2–4]. Complementary, the structure and management rules of any specific electricity market may constitute sources of price volatility as well [5]. Due to these facts electricity market agents are required for understanding the factors underlying the market price evolution. A comprehensive knowledge allows agents to develop strategies for selling, or buying, electric energy both in the spot and futures market. Furthermore, those strategies are important to practice the hedge against electricity market volatility and to increase their profits. Derivatives were introduced in electricity markets for allowing agents to eliminate the risk of credit and
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