Multi-facts devices installation for loss minimization and techno-economic impact assessment using EPSO approach
This thesis presents a new meta-heuristic approach technique for optimal location and sizing of multi-unit Flexible Alternating Currents System (FACTS) device installation using single- and multi-objective problems. It also considers techno-economic impact in the system. In this research, the...
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| Format: | Thesis |
| Language: | English |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/1747/1/24p%20SITI%20AMELY%20JUMAAT.pdf http://eprints.uthm.edu.my/1747/ |
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| Summary: | This thesis presents a new meta-heuristic approach technique for optimal location and
sizing of multi-unit Flexible Alternating Currents System (FACTS) device installation
using single- and multi-objective problems. It also considers techno-economic impact in
the system. In this research, the first objective is to develop heuristic technique Single�Objective Particle Swarm Optimization (SOPSO) for optimal location and sizing 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, c1 and c2 and the effect of population size of loss minimization are also
investigated. The second objective is to determine 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 traditional PSO 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 also derived 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 for FACTS device installation identified by EPSO, PSO and EP techniques.
The fourth objective in this research is to develop a new optimization technique termed as
sigma-Multi-Objective EPSO (σ-MOEPSO) technique for optimal location and sizing of
FACTS devices installation for multi-objective problem to minimize the transmission loss
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. This assessment
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 compared to 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. |
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