The US Department of Energy has selected kWh Analytics to quantify degradation rates and increase the affordability and reliability of photovoltaics.
The DoE has through its Solar Energy Technologies Office awarded kWh Analytics with a $1.25 million contract which includes the provision of the firm’s real-world performance data.
The solution provider will under the “Deciphering Degradation: Machine Learning on Real-World Performance Data” project build a machine learning model on its industry-wide data repository to statistically quantify degradation rates on an ongoing basis.
Degradation rates are one of the key factors restraining the solar PV market.
A study conducted by NREL states that the uncertainty in degradation has a total potential impact of $17/MWh, “even exceeding the impact of the initial cost” of the solar power plant itself.
Howard Wenger, CEO of SunPower Systems, said: “The lack of long-term solar panel performance data has been a real challenge because buyers of inferior panels have been unable to readily know the difference in quality between the various products on the market.
“With data on one-in-five American solar assets and growing, kWh Analytics is uniquely positioned to address this industry-wide challenge and enable the solar industry to accurately price quality and inform buyers on how to value their solar power assets before and after purchase.”
kWh Analytics’ work to quantify degradation rates will create systemic, scalable impact by:
- Delivering real-world perspective on the causes of degradation, enabling the industry to improve reliability.
- Creating a price signal that puts a tangible dollar value on high reliability, via insurance premium pricing.
- Contributing to the open source community by sharing the proposal’s resulting machine learning model.