Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/3041
Appears in Collections:Economics eTheses
Title: The UK Electricity Markets: Its Evolution, Wholesale Prices and Challenge of Wind Energy
Authors: Cui, Cathy Xin
Supervisor(s): Bell, David
Hanley, Nick
Keywords: Electricity supply industry
trading arrangements
wholesale prices
stack model
climate change
wind energy
energy security
portfolio risk
Issue Date: 30-Mar-2010
Publisher: University of Stirling
Abstract: This thesis addresses the problems associated with security of the electricity supply in the UK. The British electricity supply industry has experienced a significant structural change. Competition has been brought into the electricity industry and a single wholesale electricity market of Great Britain has been established. The evolution of the British electricity market raises new challenges, such as improving the liquidity of wholesale markets and developing clean energy. The wholesale electricity prices are less transparent and trading arrangements are very complex in the British electricity market. In this thesis a fundamental model, called a stack model, has been developed in order to forecast wholesale electricity prices. The objective of the stack model is to identify the marginal cost of power output based on the fuel prices, carbon prices, and availability of power plants. The stack model provides a reasonable marginal cost curve for the industry which can be used as an indicator for the wholesale electricity price. In addition, the government's targets for climate change and renewable energy bring new opportunities for wind energy. Under the large wind energy penetration scenario the security of the energy supply will be essential. We have modelled the correlations between wind speed data for a set of wind farms. The correlation can be used to measure the portfolio risk of the wind farms. Electricity companies should build their portfolio of wind farms with low or negative correlations in order to hedge the risk from the intermittency of wind. We found that the VAR(1) model is superior to other statistic models for modelling correlations between wind speeds of a wind farm portfolio.
Type: Thesis or Dissertation
URI: http://hdl.handle.net/1893/3041
Affiliation: Stirling Management School
Economics

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