An algorithm for power system monitoring to reduce execution time and communication needs

What is it about?

State estimation is an important power system application, performed in real-time, which help operators improve the system reliability and minimize the operating costs. Tracking state estimators, which consider the time evolution of the power system states, are computationally more complex for very large grids and real-time operation may not be possible. This paper proposes an algorithm to reduce the computational burden, to allow real-time operation, by parallelizing the existing state estimation algorithm.

Featured Image

Why is it important?

The proposed algorithm ensures that: 1) the data exchange requirement is reduced, 2) the computational burden is reduced, 3) no need to transmit any sensitive information, and 4) increased reliability as the algorithm is now executed in parallel, spread over a wide geographical area.