Rauno Jokelainen
CTO
The data presented here is collected through real-time measurements from locations where Truman Data’s standalone IoT devices are installed in collaboration with Truman Data’s Energy Coop PaaS. Real-time device data from energy assets is transmitted to the backend of Energy Coop, i.e., dedicated databases, through a secure virtual private network. Electricity consumption and the flexibility available for trading are forecasted using AI-based machine learning methods, and visualization is performed with cloud-native tools.
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Data collection devices from the platform, as well as those on the client side, are implemented as physical nodes within the Energy Coop PaaS virtual private network. Data connections utilize multi-layered encryption to ensure secure transfer of measurements from on-site devices to backend database servers. Data storage is structured with multiple isolated databases to further enhance data security and privacy.
Collected electricity consumption data is used for 48-hour forecasting with Prophet, leveraging its strength in time-series data featuring yearly, weekly, and daily seasonality, as well as holiday effects. Flexibility capacity is then calculated based on forecasted electricity consumption. This flexibility capacity is compared in real time with external market information using backend processes that run as cloud-native services on the Google Cloud Platform, with multiple layers of encryption.
Real-time energy use vs. pricing data:
Enabling customer participation in flexibility markets
Energy flexibility revenue opportunity in Riihimäki ›
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Matching sell and buy orders ›
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