Optimal Placement of Multi-Type FACTS Devices for Total Transfer Capability Enhancement Using Hybrid Evolutionary Algorithm

2007 ◽  
Vol 35 (9) ◽  
pp. 981-1005 ◽  
Author(s):  
Peerapol Jirapong ◽  
Weerakorn Ongsakul
Keyword(s):  
Evolutionary Algorithm ◽  
Optimal Placement ◽  
Hybrid Evolutionary Algorithm ◽  
Total Transfer Capability ◽  
Facts Devices ◽  
Transfer Capability

scholarly journals Optimal placement of facts devices to reduce power system losses using evolutionary algorithm

2021 ◽  
Vol 21 (3) ◽  
pp. 1271
Author(s):  
Mahmood Khalid Zarkani ◽  
Ahmed Sahib Tukkee ◽  
Mohammed Jasim Alali
Keyword(s):  
Power System ◽  
Evolutionary Algorithm ◽  
Power Flow ◽  
Reactive Power ◽  
Research Work ◽  
Test System ◽  
Optimal Placement ◽  
Unified Power Flow Controller ◽  
Voltage Profile ◽  
Facts Devices

<p>The rapid and enormous growths of the power electronics industries have made the flexible AC transmission system (FACTS) devices efficient and viable for utility application to increase power system operation controllability as well as flexibility. This research work presents the application of an evolutionary algorithm namely differential evolution (DE) approach to optimize the location and size of three main types of FACTS devices in order to minimize the power system losses as well as improving the network voltage profile. The utilized system has been reactively loaded beginning from the base to 150% and the system performance is analyzed with and without FACTS devices in order to confirm its importance within the power system. Thyristor controlled series capacitor (TCSC), unified power flow controller (UPFC) and static var compensator (SVC) are used in this research work to monitor the active and reactive power of the carried out system. The adopted algorithm has been examined on IEEE 30-bus test system. The obtained research findings are given with appropriate discussion and considered as quite encouraging that will be valuable in electrical grid restructuring.</p>

AVAILABLE TRANSFER CAPABILITY DETERMINATION USING HYBRID EVOLUTIONARY ALGORITHM

2008 ◽  
Author(s):  
Peeraool Jirapong ◽  
Weerakorn Ongsakul ◽  
Nader Barsoum ◽  
Sermsak Uatrongjit ◽  
Pandian Vasant
Keyword(s):  
Evolutionary Algorithm ◽  
Available Transfer Capability ◽  
Hybrid Evolutionary Algorithm ◽  
Transfer Capability

FACTS Devices Allocation for Power Transfer Capability Enhancement and Power System Losses Reduction

2013 ◽  
Vol 2 (2) ◽  
pp. 1-14 ◽  
Author(s):  
Peerapol Jirapong
Keyword(s):  
Tabu Search ◽  
Power Systems ◽  
Power Loss ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Evolutionary Programming ◽  
Optimal Placement ◽  
Facts Devices ◽  
Transfer Capability

In this paper, a hybrid evolutionary algorithm (HEA) is proposed to determine the optimal placement of multi-type flexible AC transmission system (FACTS) devices to simultaneously maximize the total transfer capability (TTC) and minimize the system real power loss of power transfers in deregulated power systems. Multi-objective optimal power flow (OPF) with FACTS devices including TTC, power losses, and penalty functions is used to evaluate the feasible maximum TTC value and minimum power loss within real and reactive power generation limits, thermal limits, voltage limits, stability limits, and FACTS devices operation limits. Test results on the modified IEEE 30-bus system indicate that optimally placed OPF with FACTS by the HEA approach could enhance TTC far more than those from evolutionary programming (EP), tabu search (TS), hybrid tabu search and simulated annealing (TS/SA), and improved evolutionary programming (IEP) algorithms, leading to much efficient utilization of the existing transmission systems.

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