Case Study: Dynamic line rating and reducing special regulations
Challenge and objective
The objective was to explore how to better utilize the capacity of the power grid using dynamic limits based on sensor data.
The challenge lies in optimizing grid operation to reduce unnecessary limitations in power transfer and avoid costly production regulation (called special regulations), while maintaining security of supply.
Work performed
Data from sensors (called "Neurons") placed on overhead power lines were analyzed to assess real-time grid capacity.
A model was developed to identify potential periods where special regulations would be required, and dynamic limits were proposed to increase grid utilization.
Significant results
Dynamic grid limits based on real-time data could increase grid capacity by 20%, reducing the need for special production regulation by over 80%.
Impact for distribution system innovation
The approach highlights the potential for data-driven grid operation for more efficient grid use without compromising security, laying groundwork for future grid innovations.
An illustration of the case study: three power lines equipped with sensors, hydropower plants and power intensive industry
