In an effort to reduce operational and maintenance (O&M) costs in commercial and industrial (C&I) solar portfolios, Ecogy Energy has teamed up with Stony Brook University and Pacific Northwest National Laboratory (PNNL) to harness the power of artificial intelligence (AI). As part of the U.S. Department of Energy Solar Energy Technologies Office's initiative, Ecogy will receive $230,000 out of the $750,000 awarded to the research team. The project aims to make machine learning more accessible and affordable for multi-vendor C&I solar installations, which currently represent over 20% of the industry's total fleet.

By utilizing the open-source SolarNetwork platform, Ecogy plans to develop a machine learning solution that enhances interoperability and reduces costs associated with managing complex solar systems. The collaboration aims to provide the entire industry with a toolkit to improve operational efficiency, and all developments will be shared as open source to maximize accessibility. This initiative, supported by the SETO Fiscal Year 2020 funding program, not only aims to lower solar electricity costs but also boost the competitiveness of American solar manufacturing and businesses while increasing the reliability and resilience of the grid.

With the C&I solar industry forecasted to triple in the next five years, leveraging AI and machine learning can have a significant impact on cost reduction and operational efficiency. By addressing the complexity and cost barriers associated with multi-vendor footprints, this partnership between Ecogy, Stony Brook, and PNNL seeks to make machine learning accessible to a wider range of stakeholders. These collaborative efforts underline the industry's commitment to driving innovation and sustainability, ultimately accelerating the adoption of solar energy and its integration into various applications.

Source: renewableenergyworld.com