Fan He
About
My research project
Grid-Scale Energy Storage for Low-Carbon Power Systems: System Impacts, Transition Dynamics, and Climate ResilienceThe transition to low-carbon power systems requires increasing integration of renewable energy, which introduces significant variability and uncertainty into electricity systems. Grid-scale energy storage is widely recognised as a key technology to enhance system flexibility, support renewable integration, and improve system resilience. However, the system-wide impacts of storage remain uncertain across different temporal and spatial scales, as well as under evolving technological and climatic conditions.
This thesis investigates the role of grid-scale energy storage in future power systems through a series of optimisation-based electricity system models. First, a short-term single-node model is applied to case studies in the United Kingdom and China to evaluate the whole-system economic impacts of grid-scale storage, incorporating input–output analysis to capture broader economic effects. Second, a long-term multi-period optimisation model for the UK power system explores how technological progress and policy evolution influence the deployment and value of storage technologies across different time scales. Finally, a spatially resolved multi-node model is developed to examine how extreme climate conditions affect power system operation in 2050 and to assess the role of energy storage in enhancing system resilience.
Together, these studies provide a comprehensive assessment of grid-scale storage from short-term system impacts to long-term transition dynamics and climate resilience, offering insights for power system planning and energy policy in the transition to low-carbon electricity systems.
Supervisors
The transition to low-carbon power systems requires increasing integration of renewable energy, which introduces significant variability and uncertainty into electricity systems. Grid-scale energy storage is widely recognised as a key technology to enhance system flexibility, support renewable integration, and improve system resilience. However, the system-wide impacts of storage remain uncertain across different temporal and spatial scales, as well as under evolving technological and climatic conditions.
This thesis investigates the role of grid-scale energy storage in future power systems through a series of optimisation-based electricity system models. First, a short-term single-node model is applied to case studies in the United Kingdom and China to evaluate the whole-system economic impacts of grid-scale storage, incorporating input–output analysis to capture broader economic effects. Second, a long-term multi-period optimisation model for the UK power system explores how technological progress and policy evolution influence the deployment and value of storage technologies across different time scales. Finally, a spatially resolved multi-node model is developed to examine how extreme climate conditions affect power system operation in 2050 and to assess the role of energy storage in enhancing system resilience.
Together, these studies provide a comprehensive assessment of grid-scale storage from short-term system impacts to long-term transition dynamics and climate resilience, offering insights for power system planning and energy policy in the transition to low-carbon electricity systems.
Publications
Increasing local energy access in developing countries, particularly in off-grid regions where mini-grids are often overloaded, remains a critically underexplored area in energy transition. These regions often face significant technical and economic challenges, such as low generation capacity, high energy costs, limited energy access, and heavy reliance on diesel fuels. This study explores capacity expansion by integrating small-scale geothermal energy into such a mini-grid system to enhance the local energy supply. Unlike commonly studied solar-wind hybrid systems, this study evaluates the largely untapped potential of decentralized small-scale geothermal energy in providing a clean, reliable baseload complement to the variable solar PV system at Eka Awoke, Ikwo, Ebonyi State, Nigeria, at a minimal cost. The linear programming (LP) model presents the first in-depth analysis of the integration of small-scale geothermal energy into an existing mini-grid in sub-Saharan Africa. It evaluates the energy system under four realistic demand scenarios: Baseline, suppressed demand, increased connection demand, and increased connections with eCooking demand scenarios. The results obtained show that the geothermal capacity increased by 21.21% and 77.71% for the increased connection and increased connection with eCooking, respectively, while it decreased by 37.7% for the suppressed demand scenario. These findings provide valuable insights for energy providers and policymakers seeking to decarbonize and design more capacity and cost-effective strategies for increasing local energy access in mini-grids.
Energy storage is important in future power systems. However, the role of grid-scale energy storage in the power system and in the whole socio-economic system is unclear. A copula-based whole system model is developed to explore the economic and environmental effects of grid-scale energy storage, thus supporting the decision-making at micro and macro levels. A power system optimisation model is linked with an input-output model, and the copula function is embedded in the model to reflect the multiple and interactive uncertainties from electricity demand, emission constraints, and sector disaggregation. We conducted case studies on China and the UK in 2025 considering different storage technologies (Pumped hydro, Battery, Flywheels storage) to show the differences related with power systems and economic structures. We find that increasing energy storage capacity leads to increase in renewable generation capacity (solar generation in China and wind generation in the UK). Thus, it can reduce their total economy-wide carbon emissions. Uncertainty in sector disaggregation will have a large impact on carbon emissions in some extreme cases, especially in those sectors closely linked to the power sector and with high emission intensity.