Abstract
Advances in low-carbon technologies and energy transition unavoidably give rise to remarkable variability and uncertainty issues in the energy system. The roll-out of flexibility services strikingly boosts the system’s capacity to respond to potential risks both in the operation, planning and energy trading stages. Unlike the flexibility values in operation which have been extensively researched, facilitating flexibility in the low carbon energy market under long-term and short-term uncertainties is comparatively under-researched, yet its significance is growing with more renewable generation of the energy mix towards the carbon mitigation pathways. Under the background of decarbonization, the principal achievements of the thesis lie in the field of flexibility facilitation by multi-energy system modelling and state-of-the-art data analysis tools, in view of low-carbon technologies.There are five main chapters and can be categorized into two main parts, i.e., energy system planning and low-carbon market analysis and design. Given that long-term uncertainties (i.e., energy demand growth) causes inefficient utilization of network infrastructures and thus a high likelihood of over-investment, the first two main chapters investigate investment flexibility of the electricity distribution networks and integrated energy systems. The key methods incorporate the Real-options-based Assessment Method, Geometric Brownian Motion Model and Multi-stage Investment Strategies to capture long-term flexibility values, add strategic opportunities to network reinforcement measures, and increase the flexibility of network upgrading investment portfolios.
The other three chapters integrate system flexibility into multiple energy markets to allow for a well-functioning market framework design, i.e., network pricing, carbon-oriented electricity balancing market, analysis of long-term indicators of the balancing market. The presented outcomes and involved techniques validate that the scenario-building and advanced energy modelling techniques can accelerate an equitable and sustainable energy transition.
| Date of Award | 17 Jan 2024 |
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| Original language | English |
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| Supervisor | Chenghong Gu (Supervisor) & Furong Li (Supervisor) |