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The sustainability transition of electricity sectors is a matter of competition between multiple emerging renewable systems and dominant, established conventional systems. These transitions are multi-dimensional and are featured with non-linear and causal interactions between social, technical, economic and political components. Understanding the dynamic of transitions, i.e. how transitions unfold, can inform effective policy interventions. This paper aims to present a narrative-modelling approach to improve the understanding and description of transition dynamics in electricity sectors. The central ideas of the paper are: (1) the use of qualitative transition narratives helps to capture the co-evolving nature of society and technology which are simplified in modelling approaches; (2) narratives, with concepts from the sustainability transitions field, also guide the development of a model structure; and (3) computational models, in return, reproduce the complexity of transition dynamics, i.e. feedback loops, non-linearity, and time delays—the features which are impracticable to analyse with transition narratives alone. We use the historical transition of India's electricity sector to demonstrate the implementation of our proposed approach. First, an overview of the transition narratives is presented and the model structure, developed based on the narratives, is explained. Then, it is argued how the coupling of the narratives and model improves our understating of the positive impacts as well as the side-effects of stable feed-in tariffs and accelerated depreciation on the penetration levels of wind and solar electricity. [ABSTRACT FROM AUTHOR]

A large number of Indian thermal power plants are tied under power purchase agreements with distribution companies. However, the existing energy models do not account for these 'take or pay' contracts for investigating climate policies. In this context, this paper investigates the impact of these power purchase agreements on power sector operations, cost of electricity and emissions from the Indian power sector. An optimization model was developed for this study with 620 coal, 239 gas, 21 nuclear and 686 hydro units with technology and operational characteristics to analyze electricity dispatch for power sector. The operations of thermal power plants were analyzed with and without power purchase agreements, and low carbon policy scenario. The scenarios are compared for power plant operations, cost of electricity, stranded assets, and emissions. The results show that there is a significant cost advantage for plants covered under power purchase agreements which favors the operations of older inefficient power plants in baseline scenarios. In addition, the representation of power purchase agreements raises the cost of electricity by 26 percent. A change in operating strategy from least cost to least emissions with a lower demand growth scenario can mitigate 24 percent emissions. The cost of carbon abatement is 268–277 USD/tonne for policy scenarios. Options like renegotiation of power purchase agreements can be considered to mitigate emissions. • Indian power sector optimization model is formulated with power purchase agreements. • Older power plants have cost advantage under existing power purchase agreements. • Power contracts in existing models result in total cost escalation of 26 percent. • The power sector can reduce emissions by 24 percent with optimal operations under lower demand. • Existing projects in pipeline will result in large stranded assets. [ABSTRACT FROM AUTHOR]