|dc.description.abstract||The long-term policy analysis of societal transitions, such as transitions in energy sectors, is identified as a ‘wicked policy problem’. This is a wicked problem as transitions lie over complex processes of change, involving several interacting technical, economic and societal systems, and unfolding under deep uncertainty conditions. ‘Sustainability transitions’ is an emerging field which can address this wickedness in societal transitions. There has been a growing interest in this field to study the sustainability challenges of emerging economies, with their specific institutional settings, in the recent years. Among them, the transition in India’s electricity sector with policy interventions for realising the 60 GW wind and 100 GW on-grid solar installed capacity by 2022 is an interesting exemplar, where its future pathways are vague and uncertain.
In order to address the wickedness of policy analysis in societal transitions in general and in India’s electricity sector in particular, a robust understanding of transition dynamics in the face of multiple plausible futures is required. The significance of a combined (qualitative) narrative and (quantitative) modelling standpoint in achieving this understanding has been advocated recently by scholars in the sustainability transitions and modelling communities. However, this is an area which has been addressed only sparingly in the literature. This gap, if gets filled, will be theoretical and methodological contributions for the policy analysis of societal transitions. This will be also an empirical contribution, if it is applied to the transition of India’s electricity sector, which brings insights for practitioners about the historical and future transition pathways. Therefore, this thesis aims ‘to improve the policy analysis of complex transition pathways under deep uncertainty conditions through the development of a framework to exploit the synergetic interactions between narrative and modelling approaches.’
To achieve the aim, a novel approach called the ‘dual narrative-modelling approach’ is developed and implemented in the case study. The dual narrative-modelling approach explains how to exploit the synergetic interactions between narratives and models in the policy analysis of transition pathways over decades. In the first phase of this research, an empirically-underpinned theoretical framework is developed to explain how transitions, as long-term, fundamental, multi-dimensional and path-dependent processes, unfold. The framework is developed based on theoretical concepts from sustainability transitions. Using this framework, in the second phase, the dynamics of historical transitions in the case study are described in form of a stylised narrative. This brings a historically-informed review—in form of detailed and stylised storylines—of the unfolding of transitions. In the third phase, a system dynamics model is developed to better explain the complexities of transitions in electricity sectors. The theoretical framework and stylised narrative can inform this model by identifying the case specific boundary conditions, feedback loops, and contingencies and also by assisting it in validating simulation results. In the fourth phase, the model is used to explore future transition pathways under deep uncertainty. Again, the synergies between narratives and models can inform the framed and open-ended exploration of transition pathways.
This study uses the transition of India’s electricity generation sector from fossil fuels towards renewable sources as an illustrative case. The transition is assumed to be the continuation of historical transitions, started from 1990. The application of the dual narrative-modelling approach in this case study explains the dynamics of historical transition (1990-2015) in a stylised narrative and uncovers its non-linear and time delay interactions in a model. It also explores the plausible transition pathways of India’s electricity sector and the realisation of its renewable targets in deeply uncertain futures (1990-2030).||en_US