The concept of digital twins was originally applied to complex production systems such as aircraft production, but with today’s low cost sensors and all pervasive AI and machine learning capabilities, the concept is fast being used for many other sectors, including solar.
Digital twins for solar power plants, using historical data and current behavioral data, and combining such data with modeling and simulation, provides advance insights for optimizations and also predicts performance. A digital twin can incorporate a comprehensive set of parameters and variables for processing and inferences, a lot more than traditional SCADA software use. Through the use of machine learning algorithms, digital twins also improve their own analyses and inferences over time.
11-08-2021
22-08-2021
03-08-2021
Core sciences & engineering
Corporate researcher
Solution provider
Power