Assessing irradiance forecasts value for an hybrid PV/fuel industrial site

With the worldwide increase of photovoltaic (PV) resources in the recent years, PV power forecasting becomes widely used by system operators in many contexts e.g. energy trading, smart grids, island grid operations or industrial off-grid power systems.

Forecasts providers generally have a good understanding of how to evaluate forecast accuracy, but low understanding of how the forecasts are used and generate value. It is the opposite for the forecasts user, which results in difficulties for the provider to generate high-value forecasts, and for the user to use them effectively.

Estimating the added-value of forecasts is thus a difficult task. Attempts have been made for market-related use-cases [1], [2]. However it is difficult to extend this work to power systems operation, since they have much more physical constraints and no quantitative price signal. In this work, we present a forecasting framework for operators of an hybrid PV/fuel off-grid industrial site, combined with a simulator that estimates the overall economical added-value of the system.

Based on discussions with the forecast users and understanding of their decision-making process, the framework is based on three elements. The first is a standard day-ahead forecast algorithm based on weather forecast. The second is a hour-ahead forecast that corrects the first based on measurements and satellite observations, which also takes into account live operational conditions of the PV plant : trackers malfunction, inverters faults, or curtailment. Finally, a state-of-the-art algorithm based on sky imagers that identifies incoming clouds in the next 30 minutes and the expected PV production drop.

The simulator takes the outputs of this framework and all measurements from the PV plant and simulates the system operation. Infering the added value of the system is helpful for all parties :

• The forecast supplier can promote his solution in a quantitative way to other potential customers,
• The forecast user can estimate the financial gain that came from using forecasts,
• The community can benefit from a reference point on how much value can be expected from forecasts in this use case, and progress towards increasing this value.

[1] David, M., Boland, J., Cirocco, L., Lauret, P., & Voyant, C. (2021). Value of deterministic day-ahead forecasts of PV generation in PV+ Storage operation for the Australian electricity market. Solar Energy, 224, 672-684.

[2] Alvarenga, R., Herbaux, H., & Linguet, L. (2023). On the Added Value of State-of-the-Art Probabilistic Forecasting Methods Applied to the Optimal Scheduling of a PV Power Plant with Batteries. Energies, 16(18), 6543.