Loss Sensitivity Approach in Evolutionary Algorithms for Reactive Power Planning

This article presents evolutionary algorithm-based optimal reactive power planning. A "loss sensitivity" approach is developed and implemented using differential evolution, particle swarm optimization, and the genetic algorithm. The objectives are to minimize real power loss and to improve the voltage profile of an interconnected power system. Transmission loss is expressed in terms of voltage increments by relating the control variables, i.e., reactive var generations by the generators, tap positions of transformers, and reactive power injected by the shunt capacitors. Based on the values of the loss sensitivity, corrective action is taken by adding a shunt capacitor at the weak buses identified by weak bus analysis, by controlling reactive generations at the generator buses by judging the sensitivity at these buses, and also by controlling tap changing positions if the tap changing transformers are in between the loss sensitive buses. The solutions obtained by this method is compared with the solutions obtained by each of these evolutionary algorithm-separately and with their hybrids with simulated annealing. From the comparisons, it is shown how the sensitivity-based evolutionary technique can be a very useful new tool for the reactive power planning.