Having accurate connectivity, topology and GIS accuracy is crucial for utilities in planning, forecasting and monitoring efforts. Many utilities have realized the importance of building a ‘Digital Twin’, or digital representation of their electrical grid. However, an inaccurate representation of the grid is as good as no representation. An accurate digital grid is a connected grid. Achieving this begins by mapping out the elements and assets active within the system, then comes ensuring those elements are all connected.
Connectivity relates to the connections between elements in your grid. Be it how distribution lines are connected to transformers, transformers to metres, lines between each other, substations to feeders, etc.. Everything in the grid is connected, however often a utility’s data will say otherwise. This results from years of under-performed documentation and lack of consistency when making changes in the network.
Low connectivity and GIS accuracy make it almost impossible for operators and planners to understand the true energy flow in their grid. This not only makes forecasting complicated, but significantly restricts the effectiveness of DERMS (Distributed Energy Resource Management Systems) and ADMS (Advanced Distribution Management Systems). These advanced systems require a very accurate digital representation of the grid in order to function optimally.
Take an example. An automated DERMS believes that a DER or Electric Vehicle is connected to a certain feeder which is underloaded. As a result, it activates the DER to increase input into the grid and balance the feeder. However, all along the DER was actually connected to a different feeder. Its activation will have no effect on the underloaded feeder, and in fact causes more harm by inputting unwanted energy into a completely separate feeder. All because point of charging was badly associated trough GIS data.
TGI’s powerful algorithms perform a number of tasks:
- Take existing data and identify what is and isn’t connections
- Associate and connects disconnected elements to the correct grid elements
- Validate association values/attributes against real electrical connectivity information
- Can process CIM, Multi-speak and ESRI formats
- Can work with a number of GIS systems
Cleaning gaps and errors in GIS accuracy is essential to advance to a smart-grid future. Awesense provides a quick and cost-effective solution to solve these issues.
Geospatial Correction Results
After implementing TGI’s algorithm, utilities can expect a number of key results:
- Highly improved GIS & topology accuracy
- Grid-wide element connectivity
- Digital Twin model and accuracy improvements
- Optimally functioning DERMS and ADMS systems
- Accurate energy balancing
- More effective planning and operations
- First step in forecasting
- Validate -> Plan -> Forecast
- Insight into asset health
- Over/underloaded transformers, functioning capacitor banks, etc.
- Better situational awareness and outage prediction
- Complete storage of all GIS historical records and updates. Operators can scroll back to view any previous versions.
As Christophe Guille & Stephan Zach, Bain & Co. state: “Cleaning up data is a major challenge, requiring painstaking work to rationalize what is frequently a haphazard collection of systems and restructuring them along common lines so [utilities] can share and effectively use the data at hand.”
TGI’s connectivity and GIS correction algorithms empower utilities with a tool to quickly identify and solve their data quality issues. By providing automated monitoring and updating of the system data, they can be confident that critical decisions being made are the correct ones.