The next challenge for Oman’s renewable grid

For most of the history of electricity generation, producing power has been relatively predictable. A gas-fired plant can increase or reduce its output according to demand. Solar and wind energy introduce a very different challenge. Their fuel arrives according to the weather.
As Oman rapidly expands renewable energy, knowing when that energy will arrive could become almost as important as generating it.
Renewable energy forecasting uses weather observations, satellite information and increasingly sophisticated computer models to predict how much electricity solar panels and wind turbines are likely to produce. Forecasts can range from minutes ahead to several days, giving electricity operators more time to balance supply with demand.
The technology is becoming increasingly important as renewable energy occupies a larger share of electricity systems worldwide.
For Oman, that shift is already under way. Renewable energy accounted for approximately 9.46 per cent of electricity transmitted through the national grid in 2025, according to Oman Electricity Transmission Company figures. The country is working towards increasing the contribution of renewables to around 30 per cent by 2030.
Much of that growth will come from solar and wind.
Unlike conventional generation, however, neither can simply be switched on whenever electricity is required. A layer of cloud moving across a large solar installation can affect generation, while changes in wind speed can alter the output of a wind farm.
Accurate forecasting helps grid operators prepare for these fluctuations.
Solar forecasts can combine satellite imagery with information on cloud movement, temperature and historical generation. Wind forecasting is more complex because wind conditions can vary considerably between locations and heights. Data collected from turbines, weather stations and atmospheric models can be used to estimate how conditions will change.
Artificial intelligence is adding another layer. Machine-learning systems can analyse enormous quantities of historical weather and electricity-generation data, identifying patterns that conventional forecasting models may overlook. As more operational data becomes available, predictions can potentially become increasingly precise.
This has implications beyond simply knowing whether tomorrow will be sunny.
Better forecasts can help determine when battery storage should charge or release electricity. They can also help conventional power stations respond more efficiently when renewable output is expected to fall, reducing the need to maintain unnecessary backup generation.
Oman presents an interesting environment for such technology. Solar resources are abundant, but dust, cloud cover and high temperatures can influence photovoltaic performance. Wind resources also differ significantly across the country, with some of the strongest conditions found in southern and coastal areas.
Understanding these variations will become more important as renewable projects spread across different governorates.
Forecasting will not eliminate the variability of renewable energy. Batteries, stronger transmission networks and flexible electricity systems will still be needed. What forecasting can provide is greater visibility, allowing operators to anticipate changes rather than simply react to them.
The renewable-energy transition is often associated with what can be seen: enormous solar farms stretching across the desert or turbines turning along windy coastlines.
But part of the infrastructure supporting Oman’s next energy system may be largely invisible.
As more electricity begins to depend on the movements of the sun, clouds and wind, predicting what the sky will do next could become an essential part of keeping the lights on.