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DE-RISKING THE ENERGY TRANSITION

FOR 

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YOUR INFORMATION EDGE

Sunairio is the first software company to leverage high-resolution climate simulation for energy investment, portfolio strategy, and business insights. Our technology is a comprehensive ecosystem powered by the most lifelike replication of climate, asset, and market variability — helping you make decisions that increase revenue, ensure reliability, and reduce risk.

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RENEWABLE ENERGY INVESTORS

Quickly simulate a utility-scale wind or solar project using hyperlocal climate data and machine learning
Generate more accurate pre-construction production estimates by accounting for climate variability
Select uncorrelated projects that reduce revenue risk 24%. Read the case study to find out how.

UTILITIES, ISOs, ELECTRIC COOPERATIVES

Simulate up to 15 years of climate change-aware, correlated hourly load, wind, and solar resources
Perform resource adequacy studies that reflect a full range of correlated weather outcomes–without relying on averages, profiles, or other unrealistic assumptions
Read the case study to learn more
Prepare for climate change risks that can cost your grid over $1 B in system costs. See the risks hour by hour.
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ENERGY STORAGE AND DISTRIBUTED ENERGY RESOURCES

Simulate hourly grid and market volatility 15 years into the future
Understand how intraday demand and price shapes evolve over time
Unlock opportunities for hedging and monetization via market valuations

ENERGY TRADERS AND PORTFOLIO MANAGERS

Monitor hourly net demand risks from 15 days to 15 years
Calculate probabilistic risk-reward for trade opportunities
Easily quantify the likelihood and magnitude of extreme events
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WHITE PAPER

SOLAR PRODUCTION RISK ASSESSMENT: 4X LESS UNCERTAINTY; INCORPORATES CLIMATE TRENDS

Solar production risk assessment is traditionally based on hypothetical power generation from Typical Meteorological Years (TMYs) or historical weather data. These approaches ignore climate trends and extrapolate from small datasets, leading to annual production estimates that are unreliable and drift from reality over time. At certain sites, the gap is as large as -5% currently, and as much as -12% a decade from now.
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CASE STUDY

REDUCE ANNUAL REVENUE RISK BY 24%

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Leeward Renewable Energy used the Sunairio platform to select new wind and solar projects that best diversified risks across different regions and different technologies. Sunairio enabled Leeward to simulate thousands of correlated future production and revenue outcomes at dozens of current and prospective sites. The Sunairio platform applied modern portfolio theory to pick an optimal combination of new projects.
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CASE STUDY

NET DEMAND SIMULATION

This case study presents the underlying motivation and representative insights from an electric cooperative net demand planning exercise that utilized a long-term (15-year) correlated climate simulation and machine learning-based energy resource modeling.
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CUSTOMERS AND PARTNERS

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