Ascertainment of Photovoltaic System Generation Access Capacity Based on Probabilistic Power Flow and Improved Genetic Algorithm

2012 ◽  
Author(s):  
Shu-jun Yao ◽  
Long-hui Liu ◽  
Yan Wang ◽  
Lu-yao Ma ◽  
Jing Yang
Keyword(s):  
Genetic Algorithm ◽  
Power Flow ◽  
Photovoltaic System ◽  
Improved Genetic Algorithm ◽  
System Generation ◽  
Probabilistic Power Flow

The Calculation of Photovoltaic System Generation Access Capacity in Distribution Network Based on Probabilistic Power Flow and the PSO Optimization

2012 ◽  
Vol 529 ◽  
pp. 371-375
Author(s):  
Lu Yao Ma ◽  
Shu Jun Yao ◽  
Yan Wang ◽  
Jing Yang ◽  
Long Hui Liu
Keyword(s):  
Distributed Generation ◽  
Power Flow ◽  
Optimization Problem ◽  
Flow Model ◽  
Expansion Method ◽  
Pso Algorithm ◽  
Photovoltaic System ◽  
System Generation ◽  
Probabilistic Power Flow ◽  
The Cost

With the distributed generation such as photovoltaic power system (PVS) is largely introduced into power grid, some significant problems such as system instability problem increase seriously. In order to make full use of PVS and make sure the voltage exceeding probability is limited within a certain range to ensure the power quality, as well as consider the cost of access device, the suitable PVS access node and capacity is important. Based on this problem, this paper establishes the probabilistic power flow model of PVS by introducing the combined Cumulants and the Gram-Charlier expansion method. Also, to solve the nonlinear combinatorial optimization problem, this paper uses PSO algorithm. Finally to get the suitable PVS access node and capacity, also calculate the solution of voltage exceeding probability.

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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