Infrastructure Engineering - Theses
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ItemEnergy Policy Analysis Towards Clean Energy Transitions in Mexico( 2022)Energy transitions from fossil fuel-based to cleaner energy systems are required to fulfil international commitments on climate change mitigation. To fulfil international climate agreements, Mexico has established ambitious national GHG emissions reduction targets (22% by 2030 from business as usual and 50% from 2000 levels), expecting the electricity sector to be the largest contributor to these emission reductions. However, the targets in clean energy may represent a great challenge for the Mexican energy system as it has been experiencing a period of deep structural changes over time (e.g. institutional restructuring derived from the intense energy reform declared by the Mexican government in December 2013). By considering the effects of historical structural transformations within energy systems and given the right mix of policy instruments, Mexico has the potential to advance clean energy development and therefore diversify its energy mix and significantly reduce its GHG emissions. Policymakers design and implement policy strategies to solve problems based on the analysis and interpretation of available information. Energy policymaking in Mexico, as in other developing countries, depends largely on limited available information. Traditional policymaking approaches have a deterministic, predictive, and reactive perspective on future issues. However, performance trends of energy systems could be different in the future due to incorrectly predicted changes in economic, technological, social, political, and environmental conditions. The decision-making process becomes even more challenging as the number of variables and decision makers increases. Policymaking within the energy sector, especially in developing countries, is characterised by many stakeholders, information is not always available or imprecise, and complex dynamic interactions among policy, economy, society, environment, and technology that may affect the intended outcomes of policy strategies, and therefore the behaviour of energy systems. These conditions make policymaking for energy transitions to be considered as a problem under deep uncertainty. The application of traditional policy-making approaches to complex, evolving issues (e.g. energy transitions) is limited. Thus, energy policymaking in the context of deep uncertainty calls for an alternative paradigm aimed at connecting short-term decisions with long-term objectives by using models as exploratory tools instead of a prediction tool. The analysis of policy-relevant information using an exploratory approach may help policymakers to identify and select robust policy alternatives towards clean energy transitions. The aim of this thesis is to explore the effects of robust energy policy mixes towards clean energy transitions in Mexico. To achieve this aim, a new integrated method has been developed and implemented to support policymakers with the design of robust energy policy alternatives. A policy alternative is considered robust if the system of interest (e.g. electricity system) performs satisfactorily under a broad range of plausible futures. The integrated method is developed by combining quantitative and qualitative approaches (i.e. mixed method), integrating sustainability and energy transitions concepts, analytical tools used by robustness-based approaches, quantitative simulation modelling techniques, and exploratory modelling and analysis. Implementing the proposed method encompasses a series of interdependent analytical processes, including policy problem definition, deep uncertainty characterisation, exploratory modelling and analysis, and (the development of) policy recommendations. As policymaking for energy transitions under deep uncertainty is conceptualised as a learning process, learning may be facilitated by an iterative approach revealing stakeholders’ preferences and possible trade-offs among alternative problem framings and solutions. Thus, the stepwise implementation of these analytical processes leads to the development and application of complementary analytical tools to improve the applicability of the integrated method developed. Following the iterative learning approach of the integrated method, a new theoretical framework has been developed for qualitatively describing the evolution of energy systems at a national level. By integrating concepts from sustainability transitions, policy mixes for energy transitions, and interactive governance literature, this thesis describes the historical evolution of the Mexican electricity sector in general and the role that clean energy technologies have played in particular. In addition, relevant drivers and barriers towards a clean energy transition in Mexico are identified and discussed. Technological learning has been identified as one of these key drivers. Thus, a new integrative technological learning model has been developed to explore the effects of learning processes on technological-based cost developments. The influence of different learning curve approaches is explored by choosing how key parameters and sources of learning are defined. In addition, a new definition of technological experience has been developed and presented in this thesis. This new definition accounts for diverse learning sub-processes (learning-by-doing, learning-by-using, and international experience spillovers) to estimate the total experience gained through technology deployment. By implementing the new definition of experience within the integrative technological learning model, historical and future technology cost developments have been explored for diverse clean energy technologies. Insights from the development and application of these complementary analytical tools are used in this thesis as inputs to explore the plausible consequences of adopting different policy mixes towards a clean energy transition in Mexico. By implementing the integrated method developed within this study, multiple energy transition pathways are simulated and analysed using statistical and data-mining techniques. Based on the comprehensive analysis conducted here, the exploratory results show that although a broad range of policy mixes could be implemented, policymakers in Mexico could focus on economic signals and performance standards to meet medium and long-term policy objectives on greenhouse gas emissions reduction strategies (i.e. clean energy development, energy efficiency improvement). Thus, this thesis highlights the relevance of applying model-based policy analysis with a robust approach to help policymakers improve the policy exploration process by identifying the consequences of implementing different policy alternatives towards energy transitions under deep uncertainty conditions.
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ItemEnergy Policy Analysis Towards Clean Energy Transitions in Mexico( 2022)Energy transitions from fossil fuel-based to cleaner energy systems are required to fulfil international commitments on climate change mitigation. To fulfil international climate agreements, Mexico has established ambitious national GHG emissions reduction targets (22% by 2030 from business as usual and 50% from 2000 levels), expecting the electricity sector to be the largest contributor to these emission reductions. However, the targets in clean energy may represent a great challenge for the Mexican energy system as it has been experiencing a period of deep structural changes over time (e.g. institutional restructuring derived from the intense energy reform declared by the Mexican government in December 2013). By considering the effects of historical structural transformations within energy systems and given the right mix of policy instruments, Mexico has the potential to advance clean energy development and therefore diversify its energy mix and significantly reduce its GHG emissions. Policymakers design and implement policy strategies to solve problems based on the analysis and interpretation of available information. Energy policymaking in Mexico, as in other developing countries, depends largely on limited available information. Traditional policymaking approaches have a deterministic, predictive, and reactive perspective on future issues. However, performance trends of energy systems could be different in the future due to incorrectly predicted changes in economic, technological, social, political, and environmental conditions. The decision-making process becomes even more challenging as the number of variables and decision makers increases. Policymaking within the energy sector, especially in developing countries, is characterised by many stakeholders, information is not always available or imprecise, and complex dynamic interactions among policy, economy, society, environment, and technology that may affect the intended outcomes of policy strategies, and therefore the behaviour of energy systems. These conditions make policymaking for energy transitions to be considered as a problem under deep uncertainty. The application of traditional policy-making approaches to complex, evolving issues (e.g. energy transitions) is limited. Thus, energy policymaking in the context of deep uncertainty calls for an alternative paradigm aimed at connecting short-term decisions with long-term objectives by using models as exploratory tools instead of a prediction tool. The analysis of policy-relevant information using an exploratory approach may help policymakers to identify and select robust policy alternatives towards clean energy transitions. The aim of this thesis is to explore the effects of robust energy policy mixes towards clean energy transitions in Mexico. To achieve this aim, a new integrated method has been developed and implemented to support policymakers with the design of robust energy policy alternatives. A policy alternative is considered robust if the system of interest (e.g. electricity system) performs satisfactorily under a broad range of plausible futures. The integrated method is developed by combining quantitative and qualitative approaches (i.e. mixed method), integrating sustainability and energy transitions concepts, analytical tools used by robustness-based approaches, quantitative simulation modelling techniques, and exploratory modelling and analysis. Implementing the proposed method encompasses a series of interdependent analytical processes, including policy problem definition, deep uncertainty characterisation, exploratory modelling and analysis, and (the development of) policy recommendations. As policymaking for energy transitions under deep uncertainty is conceptualised as a learning process, learning may be facilitated by an iterative approach revealing stakeholders’ preferences and possible trade-offs among alternative problem framings and solutions. Thus, the stepwise implementation of these analytical processes leads to the development and application of complementary analytical tools to improve the applicability of the integrated method developed. Following the iterative learning approach of the integrated method, a new theoretical framework has been developed for qualitatively describing the evolution of energy systems at a national level. By integrating concepts from sustainability transitions, policy mixes for energy transitions, and interactive governance literature, this thesis describes the historical evolution of the Mexican electricity sector in general and the role that clean energy technologies have played in particular. In addition, relevant drivers and barriers towards a clean energy transition in Mexico are identified and discussed. Technological learning has been identified as one of these key drivers. Thus, a new integrative technological learning model has been developed to explore the effects of learning processes on technological-based cost developments. The influence of different learning curve approaches is explored by choosing how key parameters and sources of learning are defined. In addition, a new definition of technological experience has been developed and presented in this thesis. This new definition accounts for diverse learning sub-processes (learning-by-doing, learning-by-using, and international experience spillovers) to estimate the total experience gained through technology deployment. By implementing the new definition of experience within the integrative technological learning model, historical and future technology cost developments have been explored for diverse clean energy technologies. Insights from the development and application of these complementary analytical tools are used in this thesis as inputs to explore the plausible consequences of adopting different policy mixes towards a clean energy transition in Mexico. By implementing the integrated method developed within this study, multiple energy transition pathways are simulated and analysed using statistical and data-mining techniques. Based on the comprehensive analysis conducted here, the exploratory results show that although a broad range of policy mixes could be implemented, policymakers in Mexico could focus on economic signals and performance standards to meet medium and long-term policy objectives on greenhouse gas emissions reduction strategies (i.e. clean energy development, energy efficiency improvement). Thus, this thesis highlights the relevance of applying model-based policy analysis with a robust approach to help policymakers improve the policy exploration process by identifying the consequences of implementing different policy alternatives towards energy transitions under deep uncertainty conditions.