GreenPowerMonitor deploys Machine Learning models in its GPM Plus and GPM Horizon solutions
New technologies such as Machine Learning, or ‘ML’, are being applied in the renewable energy sector to predict in a more accurate way production behavior, energy consumption and plants performance.
Machine Learning is an application of Artificial Intelligence (AI) that enables systems to continually learn and improve predictive performance without being explicitly programmed. Machine Learning focuses on the development of computer programs that can analyze data and use it to learn for themselves.
GreenPowerMonitor makes use of ML to extract information from the myriad of data points residing in our databases to provide value to our customers. ML models allow for a statistical description of site components given certain conditions and as a result our solutions can predict the component’s behaviour in such conditions.
How GPM deploys ML in our services
ML models are currently deployed within GPM Plus and GPM Horizon.
GreenPowerMonitor has a dedicated server tasked with data cleansing and ML model training such that the ML output is a tailored model that will emulate the behaviour of each component. The result will be a dedicated data series for expected power of that asset.
The deployment of xN ML-powered brains are used to predict performance of each site component (i.e. inverters). These brains model the component behaviour based on cleansed historical data. The result will be xN datapoints for expected power.
The 3 main benefits
Applying ML to our services has three main benefits:
- The ability to model the behavior of site components, i.e. inverters, to determine expected performance of the component at any point in time;
- The ability to predict future performance with forecast data.
- The capability to determine -via root cause analysis, the energy loss due to a list of factors
If you would like to know more about our ML applications, contact our team of experts and we will schedule a demonstration for you: firstname.lastname@example.org