A Computational Comparison of Swarm Optimization Techniques for Optimal Load Shedding under the presence of Unified Power Flow Controller to Avoid Voltage Instability

A Computational Comparison of Swarm Optimization Techniques for Optimal Load Shedding under the presence of Unified Power Flow Controller to Avoid Voltage Instability

B.Venkateswara Rao, G.V.Nagesh Kumar
Copyright: © 2014 |Pages: 16
DOI: 10.4018/ijsir.2014100102
OnDemand:
(Individual Articles)
Available
$29.50
Current Special Offers
No Current Special Offers
TOTAL SAVINGS: $29.50

Abstract

Voltage instability has become a serious threat to the operation of modern power systems. Load shedding is one of the effective countermeasures for avoiding instability. Improper load shedding may result in huge technical and economic losses. So, an optimal load shedding is to be carried out for supplying more demand. This paper implements BAT and Firefly algorithms for solving the optimal load shedding problem to identify the optimal amount of load to be shed. This is applied for a multi objective function which conatins minimization of amount of load to be sheded, active power loss minimization and voltage profile improvement. The presence of with and with out Unified Power Flow Controller (UPFC) on load shedding for IEEE 57 bus system has been presented and analyzed. The results obtained with BAT and Firefly Algorithms were compared with Genetic Algorithm (GA).
Article Preview
Top

2. Unified Power Flow Controller

Gyugyi proposed the UPFC concept is used for real time control and dynamic compensation of the ac transmission system (Tiwari & Sood, 2012; Ghahremani & Kamwa, 2013). UPFC provides multifunctional flexibility required to solve many of the problems in the power system. The UPFC is able to control simultaneously or selectively all the parameters affecting power flow in the transmission line (i.e. voltage magnitude, line impedance and phase angle). This capability signifies the term ‘unified’ in the UPFC (Radu, 2006; Padiyar & Kulakarni, 1998).

Complete Article List

Search this Journal:
Reset
Volume 14: 3 Issues (2023)
Volume 13: 4 Issues (2022)
Volume 12: 4 Issues (2021)
Volume 11: 4 Issues (2020)
Volume 10: 4 Issues (2019)
Volume 9: 4 Issues (2018)
Volume 8: 4 Issues (2017)
Volume 7: 4 Issues (2016)
Volume 6: 4 Issues (2015)
Volume 5: 4 Issues (2014)
Volume 4: 4 Issues (2013)
Volume 3: 4 Issues (2012)
Volume 2: 4 Issues (2011)
Volume 1: 4 Issues (2010)
View Complete Journal Contents Listing