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Title: Multi-scale energy systems modeling of the renewable energy transition
Author: Pfenninger, Stefan Johannes
ISNI:       0000 0004 6059 1914
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2016
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The majority of greenhouse gas emissions produced by mankind come from the burning of fossil fuels. Therefore, to prevent dangerous climate change, the world needs to completely rebuild the way it uses energy. This transformation is already underway and one of its key features is the rising importance of variable renewable energy, particularly wind and photovoltaics (PV). To better understand this transition, a new energy systems modeling framework is developed, called Calliope. Calliope is designed to deal with data of high spatial and temporal resolution, to run on high-performance computing clusters, to be easily extensible and re-usable and thus allow the rapid development of models targeted at specific problems. A high-resolution modeling system requires high-resolution input data, particularly for the potential power production from renewable power plants. Thus, a method is developed and presented to simulate PV plants by using both meteorological reanalysis and satellite-measured data. To validate these simulations, a database of measured power output data from real PV systems across Europe is built. These methods are applied to two cases. First, scenarios for the British power system with different combinations of three key technology groups -- renewables, nuclear and fossil fuels -- are examined with regards to their cost, emissions, their import dependence and diversity. The results show that costs are similar across a wide range of combinations but that interconnection, storage or clean dispatchable technologies are needed for renewables shares above 80%. Second, the ability of concentrating solar (CSP) and nuclear power plants to provide a stable (baseload) power supply are examined for the case of South Africa, showing that CSP plants have the potential to be cost-competitive, and likely preferable with regards to environmental and investment risks. The methods and results presented here are a contribution towards a better understanding of the energy transition, and by extension, towards improved energy policy and planning.
Supervisor: Keirstead, James ; Nelson, Jenny Sponsor: Imperial College London ; Climate-KIC
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral