Stochastic co-optimisation of energy, frequency and carbon services considering flexible nuclear power plants

Integration of high levels of non-synchronous Renewable Energy Sources (RES) and nuclear power plant will play a vital role in decarbonising the electricity grid of Great Britain (GB). However, the uncertainties associated with RES may increase the risk of grid frequency deterioration, which will increase the requirement for the provision of ancillary services such as inertia and Frequency Response (FR). Furthermore, nuclear power plants typically have lower operational flexibility due to limited load following capabilities and the ability to provide FR services, which will not only lead to high system operation cost but also present a potential barrier to reach the net-zero emissions target cost-effectively by reducing the utilisation of RES. A potential solution to mitigate these challenges consists of incorporating thermal energy storage and secondary steam rankine cycle into the nuclear power plant, effectively resulting in a Flexible Nuclear Power Plant (FNPP) configuration. Therefore, this paper proposes a novel ancillary services constrained stochastic unit commitment model, which optimises the simultaneous provision of energy production, synchronised inertia and primary FR from conventional power plants and FNPP, enhanced FR from wind, whilst explicitly considering the uncertainties associated with wind generation using the quantile-based scenario tree method. The effectiveness of the proposed model is demonstrated through several case studies conducted on the 2030 GB power system. The results explore the economic savings and carbon emissions cost reductions obtained from simultaneous co-optimisation of FNPP and the provision of FR services provided by FNPP and wind. • Flexible Nuclear Power Plant (FNPP) concept enhances grid flexibility. • A stochastic unit commitment model co-optimises energy and ancillary services. • Quantile-based scenario tree handles wind generation uncertainty effectively. • FNPP and wind provide frequency response and inertia simultaneously. • Co-optimisation reduces system cost and carbon emissions in GB power grid.