Fan He

The transition to net-zero electricity systems requires an effective integration of energy storage across multiple timescales to balance renewables intermittency and provide flexibility. However, the impacts of large-scale multi-timescale storage deployment on power system under evolving technology and policies remain unclear. Through hierarchical modelling of short-(battery), medium-(pumped hydro, compressed air, thermal), and long-duration (hydrogen) storage, this study develops a multi-period optimisation framework to explore how grid-level multi-timescale energy storage integration affects the United Kingdom's power system performance and configuration in 2035 and 2050 under different scenarios of technology advancement, renewable energy availability, and emission reduction pathways. Results reveal that power systems with multi-timescale storage outperform those with only short-duration storage in terms of both cost and carbon emissions, with 22% lower cost and 25% lower emissions in 2050. In a power system with different energy storage types of varying storage durations, advancements in storage technology that lower storage costs reduce electricity costs in 2050 by 7% under the fast technology advancement level compared to the base level. A more ambitious emission reduction target in 2035 increases electricity costs (18%) but significantly lowers carbon emissions (73%) compared to the base target. With unlimited renewable capacity caps, system's electricity costs decrease by 23% and carbon emissions fall by 13%, in 2050 compared to the base cap level. These findings highlight the crucial role of multitimescale energy storage in achieving cost-effectively net-zero power systems and underscores the importance of integrated planning that jointly considers technology improvement and the policy environment.

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.

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.