Robust PV performance and loss rate determination, and power forecasting using spatiotemporal graph neural network models in a reliable system-topology-aware learning framework
Ativa uses artificial intelligence and machine learning techniques to analyze data from a large number of neighboring photovoltaic (PV) systems in order to extract information about their short- and long-term performance. The development of spatiotemporal graph neural network models will address critical questions of long- and short-term performance for fleets of PV plants.
Machine learning methods are used to overcome data quality issues affecting individual plants.
AI based analitycs and advice for a better understanding of how your assets operate.
The deep-learning-powered probabilistic forecasting framework for day-ahead net-load at substations will separate behind-the-meter photovoltaic (PV) generation from net-load measurements and quantify its impact on net-load patterns.
Ativa is a hardware agnostic, plug and play platform, designed to connect to common OEMs.
Ativa will display the same transparent data as the software offered by your existing assets, with the added benefit of centralizing them and applying an AI layer on top.
Use one centralized tool for your entire portfolio.
Designed for OEMs, our white label solution allows them to offer their clinets a complete solution without the need to spend engineering resources.
Our API allows you to integrate Ativa’s secret sauce into your own platform.