Multicontingency transient stability constrained optimal power flow by genetic algorithm

2006 ◽  
Author(s):  
N. Mo ◽  
G.T.Y. Pong ◽  
K.W. Chan ◽  
S.W. Mei
Keyword(s):  
Genetic Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Transient Stability ◽  
Optimal Power

Flexible Genetic Algorithm Based Optimal Power Flow of Power Systems

2018 ◽  
Vol 24 (3) ◽  
pp. 84
Author(s):  
Hassan Abdullah Kubba ◽  
Mounir Thamer Esmieel
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Test System ◽  
Multi Objective ◽  
Optimal Power ◽  
Blending Method ◽  
Real Coded Genetic Algorithm

Nowadays, the power plant is changing the power industry from a centralized and vertically integrated form into regional, competitive and functionally separate units. This is done with the future aims of increasing efficiency by better management and better employment of existing equipment and lower price of electricity to all types of customers while retaining a reliable system. This research is aimed to solve the optimal power flow (OPF) problem. The OPF is used to minimize the total generations fuel cost function. Optimal power flow may be single objective or multi objective function. In this thesis, an attempt is made to minimize the objective function with keeping the voltages magnitudes of all load buses, real output power of each generator bus and reactive power of each generator bus within their limits. The proposed method in this thesis is the Flexible Continuous Genetic Algorithm or in other words the Flexible Real-Coded Genetic Algorithm (RCGA) using the efficient GA's operators such as Rank Assignment (Weighted) Roulette Wheel Selection, Blending Method Recombination operator and Mutation Operator as well as Multi-Objective Minimization technique (MOM). This method has been tested and checked on the IEEE 30 buses test system and implemented on the 35-bus Super Iraqi National Grid (SING) system (400 KV). The results of OPF problem using IEEE 30 buses typical system has been compared with other researches.     

Closure on "optimal power flow by enhanced genetic algorithm"

2003 ◽  
Vol 18 (3) ◽  
pp. 1219-1220 ◽  
Author(s):  
A.G. Bakirtzis ◽  
P.N. Biskas ◽  
C.E. Zoumas ◽  
V. Petridis
Keyword(s):  
Genetic Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Optimal Power

scholarly journals Solution techniques for transient stability-constrained optimal power flow – Part I

2017 ◽  
Vol 11 (12) ◽  
pp. 3177-3185 ◽  
Author(s):  
Shrirang Abhyankar ◽  
Guangchao Geng ◽  
Mihai Anitescu ◽  
Xiaoyu Wang ◽  
Venkata Dinavahi
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Transient Stability ◽  
Optimal Power ◽  
Flow Part ◽  
Solution Techniques

A Numerical Study of the Fixed-Threshold Criterion for Expressing Transient Stability Constraints in Optimal Power Flow

2015 ◽  
Vol 781 ◽  
pp. 379-383
Author(s):  
Warut Suampun
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Transient Stability ◽  
Numerical Study ◽  
Threshold Value ◽  
Computing System ◽  
Threshold Values ◽  
Optimal Power ◽  
Threshold Criterion ◽  
Fixed Threshold

A numerical study of the widely used fixed-threshold criterion for expressing transient stability constraints in optimal power flow (TSCOPF) is conducted. Based on a stability-region framework, a more accurate expression of transient stability constraint in TSCOPF is presented. A method for computing system exact threshold values is proposed and employed for the study of threshold values under different conditions. It is shown via numerical results on the WSCC9 and IEEE145 systems that the exact threshold value for each system and contingency is in fact not a constant, and can vary greatly depending on several factors such as types of contingency, loading conditions, and network topology.

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