DERs play a major role in supplying the modern grid. However, their growing integration introduces intermittent disruptions to real-time grid operations. This increasing unpredictability poses a challenge for grid operators, making it hard to respond effectively to immediate grid conditions or foresee future grid states. The need to transition from real-time grid operation to a more proactive and anticipatory approach has never been greater.
Today’s grid operators need a forward-looking perspective, empowering them to proactively identify potential grid violations and constraints in the hours and days ahead. This proactive approach enables them to plan ahead and implement remedial actions to ensure grid stability and reliability.
To facilitate this proactive approach, the integration of Artificial Intelligence (AI) and Machine Learning (ML) forecasting capabilities is essential. GridOS Distributed Energy Resource Management System (DERMS) forecasting leverages these technologies to help operators anticipate potential variations in power flow and their grid impacts well in advance, facilitating timely interventions. However, identifying potential violations is just the first step. Grid operators also require a method for acting on these forecasts. Yet, coordinating actions among a vast number of DERs is virtually an impossible task for a human operator in a control room, especially considering that these actions must be coordinated across potentially thousands of DERs. Automation is the key to utilities effectively identifying and dispatching the right actions to DERs at scale.
Automated DER scheduling is a key capability of GridOS DERMS. After it receives precise forecasts from its integrated Forecasting module, GridOS DERMS can leverage this data for look-ahead DER scheduling, complete with DER optimization. Grid operators can configure DER optimization use cases tailored to their specific grid perimeter, including defined time horizons, techno-economic optimization objectives, and a range of grid and DER levers. They can also choose their preferred level of automation, such as fully automated, semi-automated, or “advisory mode” (allowing the operator to validate solutions before scheduling or dispatching them).
Incorporating automated DER scheduling via GridOS DERMS empowers utilities to accommodate increasing DER penetration while keeping the lights on for their customers.