SkyLine II’s New-generation AI Tracking Algorithms Enable 7% More Energy Yield

Recently, the conflicts between Russia and Ukraine have stirred some kind of energy crisis in Europe. To swiftly curtail its reliance on Russian natural gas, which last year accounted for about 40% of the EU’s gas consumption, the EU wants to reduce imports of Russian gas by two-thirds this year and end its dependence on them entirely by 2027 and policymakers are banking on a faster expansion of solar, wind and other clean technologies to reduce demand for Russian gas while contributing to progress on existing climate goals.

Meanwhile, moving away from fossil fuels and transitioning to renewable energy is an inevitable trend around the globe. To adapt to the global trend, the key player in the renewable energy market, solar tracker manufacturers, are also seeking new technologies to enhance their products and optimize power generation in the PV plants.

Though solar trackers are designed to optimize energy absorption and increase power plant generation, solar trackers manufacturers have also started to resort to artificial intelligence (AI) technologies to enhance their competence.

While, unlike other solar tracker manufacturers who adopted the traditional solar tracker control strategy and assumed that trackers mount mono-facial modules and are installed on flat land, Arctech, the world's leading tracking, racking, and BIPV solutions provider, has developed a new generation AI tracking algorithms to help PV plants adapt to different conditions, allowing for real-time shading avoidance for up to 7% more energy generation.

Last October, Arctech, launched its latest horizontal single-axis solar tracking system SkyLine II, the first 1P (one-in-portrait) tracker designed with a pentagonal torque tube and synchronous multi-point drive mechanism. SkyLine II?is also empowered by Arctech’s new-generation AI tracking algorithms, which consist of four major strategies: tracking control strategy under real terrain conditions, bifacial strategy for bifacial modules and trackers, and cloud strategy based on real-time weather data, and control strategy based on sharing parameters with inverters.

Enhanced by new-generation AI tracking algorithms, SkyLine II could use machine learning based upon environment and operational data acquisition to optimize its working. SkyLine II’s smart backtracking algorithms are also optimized to determine the optimum tracker tilt in each topography and environment, allowing for real-time shading avoidance for up to 7% more energy generation, thereby boosting financial return for power plants owners and investors.

To sum up, the new-generation AI tracking algorithms of SkyLine II could help analyze terrain undulation, improve tracker layout, avoid shadows between arrays, maximize solar absorption, optimize tracking method based on real-time weather data, find the best tracker tilt in each topography and environment, thus increasing power generation of solar power plants by up to 7% easily.