Power Flow Distribution For Hybrid Fuel Cell Vehicle Via Genetic Algorithm Method

2004 ◽  
Author(s):  
S. M. Mehdi ◽  
M. Ansarey ◽  
Mohsen Mohammadian ◽  
S. M. Taghi Bathaee
Keyword(s):  
Genetic Algorithm ◽  
Fuel Cell ◽  
Power Flow ◽  
Flow Distribution ◽  
Fuel Cell Vehicle ◽  
Genetic Algorithm Method

scholarly journals Optimalisasi Penempatan UPFC Pada Sistem Jawa Bali 500kv Menggunakan Algoritma Genetika

2018 ◽  
Vol 2 (1) ◽  
pp. 42-47
Author(s):  
Danu Firmansyah ◽  
Istiyo Winarno
Keyword(s):  
Genetic Algorithm ◽  
Power System ◽  
Transmission Line ◽  
Power Flow ◽  
Reactive Power ◽  
Total Loss ◽  
Electrical Transmission ◽  
Channel Power ◽  
Power Injection ◽  
Genetic Algorithm Method

The transmission network is an important part of the power system to deliver electrical energy from the power  plant to the load, therefore the power system must be maximized to achieve optimal power flow, Unified Power Flow Control (UPFC) is one of the Flexible AC Transmission System (FACTS ) capable of controlling the power of the transmission line separately on electrical transmission and can be mounted on both the sender and the receiving end of the power. The UPFC power injection model to the transmission line is made in a power flow equation. In the Java Bali (Jali) 500 kV system analyzed by the Genetic Algorithm method, to produce a power injection  that  minimizes  the  active  and  reactive power losses of the transmission line without exceeding the UPFC device limit. In the Java Bali (Jali) 500 kV system analyzed by Genetic Algorithm method, the optimum UPFC value of Reactive Power injected  to  the  system for  bus  39  is  9695.593207MVar, bus 15 is 10598.78754 MVar, and on bus 37 is10755.88608 MVar. The total loss of channel power on  the  system  prior  to  installation  of  UPFC  is1815.775809 MW, while the total loss of channel power in the system after installing UPFC with GA is1537.391648 MW.

Genetic Algorithm Optimized Power Flow Control with Facts Devices

2013 ◽  
Vol 1 (4) ◽  
pp. 17-27
Author(s):  
G.N. Sreenivas ◽  
◽  
A. Yashoda Devi ◽  
K. Suresh Kumar ◽  
◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Flow Control ◽  
Power Flow ◽  
Power Flow Control ◽  
Facts Devices

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.     

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