It’s no surprise that hourly PV modeling—still solar industry standard practice—leads to inaccuracies in energy estimation and system optimization. For example:
- In 2012, Sandia researchers found that hourly-averaged simulations could overpredict annual output by as much as 2%.
- More recently, the overprediction of AC energy due to clipping losses has been estimated at 1.5-4% annually depending on system design and location.
- High DC:AC ratios, a recent trend for new installations, lead to errors at the high end of the range.
- Hourly simulations are inadequate for modeling the sub-hourly ramps of solar power.
In addition, as solar meets a rapidly growing share of electricity demand, solar developers are increasingly asked to design systems that cost-effectively deliver firm power regardless of the weather. Sub-hourly modeling provides the insight needed to develop the solar plants of the future. A key challenge, however, has been the lack of site-specific solar data appropriate for sub-hourly modeling. New, high-resolution data options are making that challenge a thing of the past.
View this fifty-minute webinar to learn about:
- Advances in high-resolution solar resource data
- Practical applications including estimation of clipping losses for solar energy assessments and optimization of dispatchable or hybrid PV
- Best practices for sub-hourly solar modeling when using PlantPredict and SolarAnywhere
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About the Speakers
Akanksha Bhat
Product Manager
Akanksha is a product manager on the SolarAnywhere team at Clean Power Research. In this role, she focuses on how solar developers, owners and other stakeholders can use SolarAnywhere’s data and intelligence solutions to make better energy decisions.
Before joining Clean Power Research, Akanksha worked at the National Renewable Energy Laboratory where she worked on DER interconnection standards and techno-economic assessment of renewables for Net-zero energy homes. Akanksha holds an M.S. in Systems Engineering from the University of Maryland, College Park, and a B.S. in Electrical and Electronics Engineering from India.
David Spieldenner
Product Director
David is the product director of PlantPredict at Terabase Energy and brings over 24 years of IT and software development experience to the platform. David was introduced to the solar industry at First Solar, where he spent 15 years. He joined Terabase in October 2021, when Terabase acquired PlantPredict from First Solar.
David has spent the last 10 years focused on digitizing utility-scale solar building software that has done everything from modeling a PV powerplant, to monitoring construction sites with drones that use machine learning.
David is passionate about the renewable energy revolution and especially the role software can play in making utility scale solar the most cost-effective power source on the planet.
David has spent the last 10 years focused on digitizing utility-scale solar building software that has done everything from modeling a PV powerplant, to monitoring construction sites with drones that use machine learning.
David is passionate about the renewable energy revolution and especially the role software can play in making utility scale solar the most cost-effective power source on the planet.
Akanksha Bhat
Product Manager
David Spieldenner
Product Director
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