This dissertation was written as part of the MSc in Energy and Finance at the
International Hellenic University.
The aim of this paper is to analyze the fundamental drivers and relationships of
the electricity prices in the Hellenic Day-Ahead-Market (DAM), and compare the
results with other large markets of the European Union, such as German, Italian,
French and Swedish. As for any market, the forces of demand and supply,
generally speaking, play the most important role in the formation of prices. The
idiosyncratic features of the electricity markets make them very special and by
far their analysis should be founded based on some assumptions. Currently, the
electricity markets are organized as markets for any other financial asset,
accepting bids and asks. The purpose of electricity markets, is the scheduling of
the Day- Ahead electricity supply, and the corresponding prices. Many are the
variables that play a role in the formation of prices, which especially in the case
of electricity markets, take into account not only economic realities and relations,
but also technological developments, networks constraints, primary fuel prices
and during the last decades, the generation and injection into the system, of
electricity that is produced by renewable energy resources. Also the intraday
distribution of demand plays a crucial role, since helps to distinguish between the
high demand hours, which are called peak hours, that have high corresponding
prices, and the valley time, called off-peak hours, that the demand is
characterized as “normal”. The purpose of this dissertation is to mainly unveil the
market’s pricing model for electricity using a rich set of fundamental variables.
The relationship between the day ahead prices, demand and the injection of
renewable energy into the system, and not by conventional power plants and
fossil fuels. To achieve our goals and give a valid interpretation of our results, we
have used principal components analysis to estimate the factors and loadings of
factors of the factor model. In addition, we try to find possible patterns in the
markets related to and caused by seasonal parameters.
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