How to set the input and target in power state estimation using neural network?

I am doing an experiment on power system state estimation using neural network  for IEEE 14 bus system with fully observed. Fully observe means all sensors are working and all measured data from sensors are transmitted to the control center. So I set the input as measured data (available measurements) and target as the true state variables (load angle and magnitude voltage), however  the measured data (input) has different samples from the target (state variables), so can we set every type of input as vector. For example, active power injections as a first vector (row) in the input matrix, reactive power injections as a second vector (second row) and the same for active power flow and reactive power flow. Or it is wrong and we have to set all measurements as one vector as we do when we use weighted least square, kalman filter, linear programing and so on. 

[SRAVAN KOTHA]

hi Hossam Mosbah,

Iam doing research in the area of power system state estimation,i request you to please share the model and code of the above work it will become more helpful to me.please dont ignore sir.

hope for the positive reply sir.

[Abolfazl Jebeleh]

Hi

I nead this code too

Please help me

[Dina Elsafy]

Hi Sir,

Iam doing a research in the area of Deep learning state estimation in power system , please can you send to me the model and code of the above work.

Answer 1

[Greg Heath]

For N pairs of I-dimensional "I"nputs and resulting O-dimensional "O"utput targets

 [ I N ] = size(input)

 [ O N ] = size(target)

Hope this helps

Thank you for formally accepting my answer

Greg