Steady State Estimation of an Open Loop Distributed Network Based on a feed Forward Neural Network

Energy efficiency measurement plays an important role in the operation and design phase of a distribution control system. The main objective of any energy adequacy test is to determine the exact location of the steady state for a known load and active and reactive power flows in each branch. In this case, one of the main results of the calculation is the voltage constancy at the nodes. Iterative methods are usually used to calculate power flows in distributed networks. This leads to the fact that high computational speed and reliability of all operations are required. With this in mind, this paper presents a distributed network model based on feedforward artificial neural networks. Its use allows to increase the level of energy consumption in the distribution system. The validity of the model is determined on the example of a real scheme of a 6-10 kV distribution network with an open loop.