scholarly journals The Optimization of the Location and Capacity of Reactive Power Generation Units, Using a Hybrid Genetic Algorithm Incorporated by the Bus Impedance Power-Flow Calculation Method

2020 ◽  
Vol 10 (3) ◽  
pp. 1034
Author(s):  
Insu Kim
Keyword(s):  
Genetic Algorithm ◽  
Power Generation ◽  
Calculation Method ◽  
Power Flow ◽  
Distribution Systems ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Hybrid Genetic Algorithm ◽  
Power Flow Calculation ◽  
Flow Calculation

Dynamic and static reactive power resources have become an important means of maintaining the stability and reliability of power system networks. For example, if reactive power is not appropriately compensated for in transmission and distribution systems, the receiving end voltage may fall dramatically, or the load voltage may increase to a level that trips protection devices. However, none of the previous optimal power-flow studies for reactive power generation (RPG) units have optimized the location and capacity of RPG units by the bus impedance matrix power-flow calculation method. Thus, this study proposes a genetic algorithm that optimizes the location and capacity of RPG units, which is implemented by MATLAB. In addition, this study enhances the algorithm by incorporating bus impedance power-flow calculation method into the algorithm. The proposed hybrid algorithm is shown to be valid when applied to well-known IEEE test systems.

scholarly journals Optimal location of unified power flow controller genetic algorithm based

2020 ◽  
Vol 11 (2) ◽  
pp. 886
Author(s):  
Sana Khalid Abdul Hassan ◽  
Firas Mohammed Tuaimah
Keyword(s):  
Genetic Algorithm ◽  
Power Generation ◽  
Power System ◽  
Transmission Line ◽  
Transmission Lines ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Optimal Location ◽  
Power Losses

<p>Now-a-days the Flexible AC Transmission Systems (FACTS) technology is very effective in improving the power flow along the transmission lines and makes the power system more flexible and controllable. This paper deals with overload transmission system problems such as (increase the total losses, raise the rate of power generation, and the transmission line may be exposed to shut down when the load demand increase from the thermal limit of transmission line) and how can solve this problem by choosing the optimal location and parameters of Unified Power Flow Controllers (UPFCs). which was specified based on Genetic Algorithm (GA) optimization method, it was utilized to search for optimum FACT parameters setting and location based to achieve the following objectives: improve voltages profile, reduce power losses, treatment of power flow in overloaded transmission lines and reduce power generation. MATLAB was used for running both the GA program and Newton Raphson method for solving the load flow of the system The proposed approach is examined and tested on IEEE 30-bus system. The practical part has been solved through Power System Simulation for Engineers (PSS\E) software Version 32.0 (The Power System Simulator for Engineering (PSS/E) software created from Siemens PTI to provide a system of computer programs and structured data files designed to handle the basic functions of power system performance simulation work, such as power flow, optimal power flow, fault analysis, dynamic simulations...etc.). The Comparative results between the experimental and practical parts obtained from adopting the UPFC where too close and almost the same under different loading conditions, which are (5%, 10%, 15% and 20%) of the total load. can show that the total active power losses for the system reduce at 69.594% at normal case after add the UPFC device to the system. also the reactive power losses reduce by 75.483% at the same case as well as for the rest of the cases. in the other hand can noted the system will not have any overload lines after add UPFC to the system with suitable parameters.</p>

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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