Distributed Generation Capacity Evaluation Using Combined Genetic Algorithm and OPF

2007 ◽  
Vol 8 (2) ◽  
Author(s):  
Gareth P Harrison ◽  
Antonio Piccolo ◽  
Pierluigi Siano ◽  
A. Robin Wallace
Keyword(s):  
Genetic Algorithm ◽  
Distributed Generation ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Maximum Amount ◽  
Optimal Power ◽  
Capacity Evaluation ◽  
Future Networks ◽  
Generation Capacity ◽  
Assigned Number

A range of techniques has been proposed to define the optimal locations and capacities of distributed generation (DG) as a means of ensuring that the maximum amount of DG can be connected to existing and future networks. However, there are limitations inherent in these methods, not least in finding the best combination of sites for connecting a predefined number of DGs. Here, a method combining optimal power flow and genetic algorithms aims to meet this requirement. Its use would be in enabling Distribution Network Operators to search a network for the best sites and capacities available to strategically connect a defined number of DGs among a large number of potential combinations. Some applications of the proposed methodology confirmed its effectiveness in sitting and sizing an assigned number of DG units.

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 Optimal Power Flow of Power Systems Including Distributed Generation Units Using Sunflower Optimization Algorithm

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 109289-109300 ◽  
Author(s):  
Mohamed A. M. Shaheen ◽  
Hany M. Hasanien ◽  
S. F. Mekhamer ◽  
Hossam E. A. Talaat
Keyword(s):  
Power Systems ◽  
Distributed Generation ◽  
Optimization Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Optimal Power
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