Data-led solutions
The effective management of decentralized grids is largely dependent on accurate data collection and analysis. For example, leveraging vast amounts of data – including weather patterns, auction outcomes, flexibility connections, and DER (distributed energy resources) profiles – to derive valuable insights and optimize grid operations. Robust interoperable architecture lets operators effectively manage data throughout the entire grid lifecycle, ensuring the smooth integration of diverse data layers.
Data-driven grids aggregate all the data from various streams to obtain value from it. AI and ML solutions can be used to analyze the data for predictive maintenance, localized substation management, and risk-based asset planning.
Taking data from connected assets also allows real-time grid health monitoring and management. This means better outage detection and improved grid balancing.
Connected assets provide data that is used to create demand/response models based on consumption patterns. By adapting to real-time data, smart infrastructures can optimize energy consumption in a way that favors renewable energy.
