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How Ard’s Solar Forecasting Model Outshone the Competition Across Every Scenario

In the fast-moving transition to clean energy, solar power has become a foundational technology for utilities and developers worldwide. But with solar’s rise comes a challenge: variability. Output can shift dramatically with changes in cloud cover, sun angle, and environmental conditions.[1] In this evolving landscape, accurate solar power forecasting isn’t just helpful – it’s essential. It informs grid stability, market participation, operational planning, and the financial success of solar projects.[2] That’s why Ard undertook a comprehensive internal benchmarking analysis of its proprietary solar power forecasting model against a leading third-party alternative. The result? Ard’s model consistently delivered lower error rates and better predictive performance across a range of tested conditions. In this article, we unpack those results, explain what was tested, and explore what the findings mean for the solar energy industry. That’s why Ard undertook a comprehensive internal benchmarking analysis of its proprietary solar power forecasting model against a leading third-party alternative. The result? Ard’s model consistently delivered lower error rates and better predictive performance across a range of tested conditions. In this article, we unpack those results, explain what was tested, and explore what the findings mean for the solar energy industry.