Multi-facts devices installation for loss minimization and techno-economic impact assessment based on computational intelligence technique / Siti Amely Jumaat

This thesis presents a new meta-heuristic approach technique for optimal location andsizing of multi-unit Flexible Alternating Currents System (FACTS) device installation using single- and multi-objective problems. It also considers techno-economic impactin the system. In this research, the first objective is to develop heuristic technique Single-Objective Particle Swarm Optimization (SOPSO) for optimal location andsizing of single-unit FACTS device installation with loss minimization, voltage monitoring and taking into account the cost of installation in the system. The verification was conducted through comparative studies with Single-Objective Evolutionary Programming (SOEP) and Single-Objective Artificial Immune System(SOAIS) techniques. The effect of weight coefficient, a and C2 and the effect of population size of loss minimization are also investigated. The second objective is todetermine the location and sizing of multi-unit and multi-type FACTS device installation using SOPSO and SOEP. Consequently, the third objective of this research is to develop a new meta-heuristic technique termed as Evolutionary Particle Swarm Optimization (EPSO) for optimal placement and sizing of multi-unit FACTS device with single-objective problem. Comparative studies with respect to traditionalPSO and classical EP techniques indicated that EPSO has its merit in terms of loss minimization. In addition, the cluster formation of FACTS device installation is alsoderived from the obtained results. The cluster formation of FACTS device installation was derived by looking at how many times (frequency) the load buses are selected forFACTS device installation identified by EPSO, PSO and EP techniques. The fourth objective in this research is to develop a new optimization technique termed as sigmaMulti-Objective EPSO (a-MOEPSO) technique for optimal location and sizing of FACTS devices installation for multi-objective problem to minimize the transmissionloss and cost of installation in power system. Finally, the fifth objective is to assess the techno-economic impact of FACTS device installation in power system. Thisassessment is performed by using a hybrid Evolutionary Particle Swarm Optimization - Net Present Value (EPSO-NPV) for assessing the impact of FACTS devices
installation in duration up to 20 years. Comparative study has been done with Evolutionary Programming - Net Present Value (EP-NPV) technique. It was found that the proposed technique has been able to produce better performance as comparedto other techniques and could be beneficial to power system planner in order to perform FACTS devices installation scheme for the minimization of loss and cost in their systems.