Prediction of Missing PMU Measurement using Artificial Neural Network

This paper presents the concept of the prediction of phasor measurement unit (PMU) data, which are unavailable due to one reason or another at the central control room, using the 3-layered feedforward back-propagation neural network (BPNN). BPNN are used to determine hidden pattern in a process, using the historical data of that process. Work presented in this paper shows that, change in the voltage at PMU buses due to change in the system operating condition can be identified using the artificial neural network, and this information of changing voltage pattern can be used to reconstruct the missing measurement data, by making use of the voltage measurement of remaining PMU buses. The concept is initially tested on an IEEE 39-bus (New England) test system and then finally verified on northern regional Indian power grid, using the PMU measurement of 21st April 2014 between 08: 36 AM to 09: 36 AM.