When 55 million people suddenly lost power in Spain and Portugal in late April, many instinctively assumed the outage must have been caused by the weather. It made sense. Extreme weather events can significantly disrupt renewable energy infrastructures – and the Iberian peninsula’s grid is 80% powered by renewables.
Turns out the weather wasn’t the culprit this time. Conditions were pristine on April 28 – balmy temperatures, no precipitation – and the Iberian grid was back up and running by the next morning. In fact, some groups are saying the nice weather contributed to an overabundance of renewable energy causing line congestion and ultimately system instability. A month later, people are still debating the cause of the worst European outage in recent memory. A joint expert panel established by the European Network of Transmission System Operators for Electricity has launched an investigation into the root cause.
Here in the U.S., solar, wind, geothermal, hydropower and other renewable sources are becoming important parts of more energy conversations. Taken all together, these sources accounted for about 90% of the U.S.’s new installed capacity in 2024, according to a report by the World Resources Institute. The same report notes that renewables make up 30% of the country’s large-scale power generating capacity and supply nearly 25% of all electricity.
Weather Risks For Renewables
Given renewables’ prospects, operators are taking more interest in how weather will affect the energy sources’ future. Renewables, of course, depend on weather to physically generate power. Their performance also depends heavily on operators’ ability to protect energy sources from all kinds of weather.
For example, hydroelectric plants are affected by intense droughts that reduce water availability or heavy rainfall can overwhelm systems. Heavy gusts of wind can damage wind turbine blades and put mechanical stress on turbine systems and severe weather make up 80% of solar farm insurance claims.
Even small weather events can progressively reduce solar output by 1% annually according to a 2024 National Renewable Energy Laboratory on weather and solar system performance.
But rather than viewing weather fluctuations solely as operational risks to be mitigated, sophisticated operators can use advanced weather intelligence to leverage weather impact arbitrage.
Weather Impact Arbitrage
Arbitrage in the traditional sense is a trading strategy where investors take advantage of price discrepancies for the same asset in different markets. Cross-regional energy trading exemplifies this approach, as operators with superior weather intelligence can anticipate production surges or deficits across different regions before they’re reflected in market prices.
My position for weather impact arbitrage involves capitalizing on discrepancies but in broader terms. It is leveraging energy assets and operations to capitalize on weather patterns across different geographies and timeframes. By understanding weather variations with greater precision, energy operators can make more informed profitable decisions about when to generate, store or consume energy, and optimize operations for time, financial or efficiency savings.
Weather Impact Arbitrage Examples
Here are a few of many examples of how weather impact arbitrage would benefit the energy industry.
Consider strategic maintenance scheduling that moves beyond simply avoiding severe weather to identifying periods when the revenue opportunity cost is lowest based on long-term weather pattern analysis. Or routine work that is delayed or rescheduled based on weather intelligence. For example, using wildfire forecasting to plan or revise work in an area with a high probability of ignition could help prevent catastrophic physical and financial outcomes.
Energy scheduling using weather intelligence can optimize output. For example, through high-resolution forecasts of solar irradiance, operators can anticipate fluctuations in sunlight caused by cloud cover, storms, or atmospheric haze. With granular forecasting, they can protect assets during a severe weather event in a specific area of the field for the necessary time to maximize energy generation. This foresight allows them to better manage energy storage systems and optimize production.
Excess renewable energy, such as wind and solar, can cause grid congestion. This is one of the causes considered for the Spain and Portugal outage. When this happens, transmission operators will enact dispatch down or curtailment measures. Dispatch down events can cause energy prices to plummet during extreme oversupply conditions. Grid operators must also pay the renewable energy provider a downward dispatch fee that can cost thousands of dollars per megawatt per hour. Energy operators who use a combination of seasonal forecasts, predictive and real-time forecasts have better insights and can strategically plan for dispatch down probabilities.
Dynamic line rating for grid balancing in increasingly becoming a global strategy for grid stability. In the U.S. the upcoming regulation FERC 881 addresses the continuing influence of weather on transmission line capacity for better dynamic and responsive line capacity management. Current calculations without DLR are based on conservative estimates of worst-case weather conditions and do not adjust in real-time to actual weather conditions. Conversely, hot conditions limit the ability to dissipate heat, increasing the risk of overheating, sagging, and potential damage to the lines. Both scenarios affect market prices, grid stability and optimizing renewable integration.
Battery storage operators can develop algorithms that charge and discharge based not just on price signals but on proprietary weather forecasts that predict price movements before they occur. Large energy consumers with flexible loads could time their consumption based on weather forecasts, reducing usage during weather-induced supply constraints and increasing it during weather-driven production surges.
What Do You Need For Weather Impact Arbitrage?
Weather Impact arbitrage depends on utilizing weather intelligence including hyperlocal weather forecasting capabilities with greater accuracy and longer lead times than traditional models. This also requires the integration of weather intelligence directly into existing systems with other data sources, such as pricing, asset locations, service areas and operations. Ensemble forecasts informed by advanced algorithms such as AI and machine learning further leverage weather arbitrage strategies.
It is time to stop viewing the weather only as a risk. Weather impact arbitrage could fundamentally transform renewable energy economics by positioning weather intelligence not as a defensive tool but as a source of competitive advantage and value creation in an increasingly weather-dependent energy landscape.
