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It is understood that electricity generation from the waves and tides can be temporally and spatially offset from other, more established variable renewables, such as wind and solar. However, it is less well understood how this offsetting can impact on power system operation. A novel modelling framework has been developed to quantify the potential benefit of including higher proportions of ocean energy within large-scale electricity systems. Economic dispatch modelling is utilised to model hourly supply–demand matching for a range of sensitivity runs, adjusting the proportion of ocean energy within the generation mix. The framework is applied to a 2030 case study of the power system of Great Britain, testing installed wave or tidal stream capacities ranging from 100 MW to 10 GW. For all sensitivity runs it has been found that ocean energy increases renewable dispatch, reduces dispatch costs, reduces generation required from fossil fuels, reduces system carbon emissions, reduces price volatility, and captures higher market prices. For example, including 1 GW of wave displaces up to £137M and 128 ktCO2 over the year of dispatch modelled. Similarly, 1 GW of tidal stream displaces up to £95M and 87 ktCO2. When including 10 GW of ocean energy, dispatch costs reduce by up to 7% and carbon emissions reduce by up to 29%. This analysis has included the development and publication of open source models of the Great British power system. • Modelling framework developed to quantify power system benefits from ocean energy. • Economic dispatch modelling used to represent power system supply–demand balancing. • Hourly generation timeseries created to represent wave and tidal stream resource. • Sensitivity analyses used to vary proportion of ocean energy within power system. • GB case study quantifies economic and environmental benefits from ocean energy. [ABSTRACT FROM AUTHOR]

Cost reductions in nascent forms of Renewable Energy Technology (RET) are essential for them to contribute to the energy mix. Policy intervention can facilitate this cost reduction; however, this may require a significant investment from the public sector. These cost reductions fall into two broad categories: (1) incremental cost reductions through continual improvements to existing technologies, and (2) radical innovation where technologies that significantly differ from the incumbents are developed. This study presents a modelling methodology to integrate radical innovation in RET experience curve and learning investment analysis, using wave energy as an example nascent RET. This aims to quantify the potential effects of radical innovation on the learning investment, allowing the value of successful innovation to be better analysed. The study highlights the value offered by radical innovations in long-term deployment scenarios for wave energy. This suggests that high-risk R&D efforts in nascent RET sectors, even with low success rates, could still present significant expected value in offsetting future revenue support. [ABSTRACT FROM AUTHOR]