With this step, bus injections (P i+ jQ i) are known at all buses other than the slack bus. This is necessary as voltage magnitude and angle are specified at this bus (only two variables can be specified at any bus). While active and reactive generations are allocated to the slack bus, these are permitted to vary during iterative computation. P Di and Q Di known), allocate P Gi and Q Gi to all generating stations.

With the load profile known at each bus (i.e.

The steps of a computational algorithm are given below: Presently we shall continue to consider the case where all buses other than the slack are PQ buses. It is much slower to converge and may sometimes fail to do so. If instead of updating voltages at every step of an iteration, updating is carried out at the end of a complete iteration, the process is known as the Gauss iterative method. The computation process is then said to converge to a solution. Iterations are repeated till no bus voltage magnitude changes by more than a prescribed value during an iteration. V 1, the slack bus voltage being fixed is not required to be updated. During each iteration voltages at buses i = 2, 3, …, n are sequentially updated through use of Eq. (6.41) are the most recently calculated (updated) values for the corresponding buses. The voltages substituted in the right hand side of Eq. During the course of any iteration, the revised voltage at the ith bus is obtained as follows:

These values are then updated through an iterative process. The slack bus voltage being specified, there are (n – 1) bus voltages starting values of whose magnitudes and angles are assumed.

We shall see later that the method can be easily adopted to include PV buses as well. To explain how the Gauss Seidel Method is applied to obtain the load flow solution, let it be assumed that all buses other than the slack bus are PQ buses.

Method Gauss Seidel IN python