MULTIMACHINE POWER SYSTEM OSCILLATION DAMPING: PLACEMENT AND TUNING PSS VIA MULTIOBJECTIVE HBMO

In this paper a Multi-objective Honey Bee Mating Optimization (MOHBMO) technique is applied to damp power system oscillation by tuning the Power System Stabilizer (PSS) parameters. Selecting the parameters of PSS which simultaneously stabilize system oscillations is converted to a simple optimization problem which is solved by a HBMO. In the proposed syndicate tuning technique, two performances indicates as ITAE and FD are computed for the stability and performance at each of the given set of operating conditions of the system simultaneously, which leads to use multi objective technique. This newly proposed controller is more efficient because it cope with oscillations and different operating points. The effectiveness of proposed controller is tested in two case studies. The first one is single machine infinite bus system which is compared with Strength Pareto Evolutionary Algorithm (SPEA) and robust PSS that is tuned by Genetic Algorithm (GA). The second case study is the Two Area Four Machine (TAFM) system of Kundur in comparison with the SPEA, GA and Quantitative Feedback Theory (QFT) based tuned PSS under different load conditions. Also in this case the placement of PSSs is presented. Simulation results show the effectiveness of the proposed PSS to damp the oscillation of multi-machine system and work effectively under variable loading and fault conditions.