Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.640261
Title: Optimising the value of assets and financial contracts in the energy industries
Author: Aitken, C. L.
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2002
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Abstract:
The UK energy industries have been through a number of changes in recent years, leading to a need for market participants to adapt to the new environment. The new market structure is a topical research area due to the large number of energy products now being traded. As a result, the valuation of both simple and more complex products which are now appearing, is of high priority to market participants. This research considers three major types of contract found in energy markets; gas storage, take or pay contracts and tolling deals. Gas storage enables participants to purchase gas when market prices are deemed low, to be used during periods of high market prices, but are reliant on accurate pricing models. Take or pay contracts were developed from the gas storage problem; these contracts allow the holder to vary the amount of gas taken on each day within specified daily and annual limits. Tolling deals are a method of converting fuel into energy without actually having to own a power station. These contracts also describe certain constraints that must be satisfied, such as environmental limits on the amount of harmful gases released by the process. In collaboration with Innogy plc, techniques have been developed to give an indication of the value that can be placed on holding the above types of contract. The contracts are modelled in a variety of ways. Liner programming models are first used to give simple approximation to the problems. The energy prices used in these models are stochastic but are approximated by using expected prices which can be predicted from market data. Models can be developed to include stochastic prices by constructing a tree of expected future prices. This approach lends itself to a stochastic dynamic programming, as this is an efficient way of traversing a tree structure. Stochastic dynamic programming is much easier and quicker for this type of problem than other techniques such as stochastic linear programming. Data from the energy industries has been obtained and used to construct a realistic test set of problems. The models provide a safe way for companies to investigate the consequences of a variety of different situations. Insights into the way that the assets and contracts function have also been obtained.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.640261  DOI: Not available
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