Computational framework for the technical and financial assessment of pumped hydropower storage systems under the day-ahead market prism

The increasing penetration of Renewable Energy Sources into the electricity system intensifies the need for large-scale energy storage technologies capable of providing flexibility, reliability, and economic value. Pumped storage constitutes the most mature and widely used large-scale energy storage option. The present study introduces a comprehensive computational framework for the techno-economic evaluation of pumped storage projects, focused on the operation of energy arbitrage in the Day-Ahead Market. The proposed methodology combines hydraulic simulations that account for geometric and operational constraints with analytical cost assessments, while revenue estimation is based on historical data from the Day-Ahead Market. As a pilot application, the pumped storage project that will utilize as lower tank the existing reservoir at Sfikia (it is referred to as Mprava pumped-storage system) is evaluated for a series of alternative operational scenarios, through a systematic investigation of combinations of installed capacity and pumping/generation duration, with the aim of drawing conclusions regarding the technical feasibility and economic attractiveness of the project. The economic evaluation is based on established investment viability criteria, namely Net Present Value (NPV), Internal Rate of Return (IRR), cumulative cash flows, while a sensitivity analysis is also applied with respect to critical geometric parameters. The results indicate that pumped storage becomes economically viable when intra-day price fluctuations are large enough to ensure a substantial difference between the pumping and generation phases, rather than on the basis of the total energy inflow or outflow balance of the system. The developed computational tool constitutes a transparent and adaptable pre-screening approach for the preliminary assessment of pumped storage projects, providing valuable information regarding the optimal geometric and operational configuration under market operating conditions.