Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.783912
Title: Three essays on the UK electricity market : risk premium, uncertainty of supply and forecasting
Author: Zafar, Muhammad Usman
ISNI:       0000 0004 7969 4905
Awarding Body: University of Essex
Current Institution: University of Essex
Date of Award: 2019
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Abstract:
This thesis investigates three issues related particularly to the UK electricity wholesale market. The first issue is whether the electricity forward market offers risk premia to compensate for the uncertainty of renewable supply. The empirical results suggest that the UK electricity forward market provides risk premia, which is higher for electricity generated from renewable sources as a compensation for the uncertainty of renewable supply. Secondly, the role of imbalances between demand and supply of electricity on the reduction in electricity prices as a result of merit order is investigated. The main finding is that imbalances due to uncertainty of supply influence the merit order effect. Moreover, the reduction in electricity wholesale prices due to electricity generation from wind is greater in case of deficit than surplus of electricity, which provides direction for participants in devising their balancing strategies. Finally, the third issue investigated is to improve prediction of electricity day-ahead prices. For this, a new method is proposed to estimate the long-term seasonal component, named as the multi-stage optimization filter with a leading Phase Shift (MOPS) to filter the data into trend and residual, and then forecasts for the trend and residual are generated separately and later combined. The proposed method for trend estimation performs better in terms of providing electricity day-ahead price forecasts as compared to some well-known trend estimation methods, such as frequency filters, wavelet decomposition, empirical mode decomposition and hodrick-prescott (HP) filter according to the Diebold and Mariano (1995) test.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.783912  DOI: Not available
Keywords: GE Environmental Sciences ; HG Finance ; TK Electrical engineering. Electronics Nuclear engineering
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