scholarly journals Multi-objective optimal power flow considering the multi-terminal direct current

2021 ◽  
pp. 60-66
Author(s):  
B. Ayachi ◽  
T. Boukra ◽  
N. Mezhoud
Keyword(s):  
Direct Current ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Transient Stability ◽  
Alternating Current ◽  
Test System ◽  
Active Power ◽  
Base Case ◽  
Multi Objective ◽  
Optimal Power

Introduction. In recent years, transmission systems comprise more direct current structures; their effects on alternating current power system may become significant and important. Also, multi-terminal direct current is favorable to the integration of large wind and solar power plants with a very beneficial ecological effect. The novelty of the proposed work consists in the effects of the aforementioned modern devices on transient stability, thus turn out to be an interesting research issue. In our view, they constitute a new challenge and an additional complexity for studying the dynamic behavior of modern electrical systems. Purpose. We sought a resolution to the problem of the transient stability constrained optimal power flow in the alternating current / direct current meshed networks. Convergence to security optimal power flow has been globally achieved. Methods. The solution of the problem was carried out in MATLAB environment, by an iterative combinatorial approach between optimized power flow computation and dynamic simulation. Results. A new transient stability constrained optimal power flow approach considering multi-terminal direct current systems can improve the transient stability after a contingency occurrence and operate the system economically within the system physical bounds. Practical value. The effectiveness and robustness of the proposed method is tested on the modified IEEE 14-bus test system with multi-objective optimization problem that reflect active power generation cost minimization and stability of the networks. It should be mentioned that active power losses are small in meshed networks relative to the standard network. The meshed networks led to a gain up to 46,214 % from the base case.

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.     

A Solution to Multi Objective Optimal Power Flow Using Hybrid Cultural-Based Differential Evolution

2013 ◽  
Vol 457-458 ◽  
pp. 1236-1240
Author(s):  
Isaree Srikun ◽  
Lakkana Ruekkasaem ◽  
Pasura Aungkulanon
Keyword(s):  
Differential Evolution ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Test System ◽  
System Operation ◽  
Power System Operation ◽  
Multi Objective ◽  
Optimal Power ◽  
Generation Cost ◽  
And Control

This paper presents a hybrid Cultural-based Differential Evolution for solving a multi-objective Optimal Power Flow (OPF) in support of power system operation and control . The multi-objective OPF was formulated for tackling with total generation cost and environmental impacts simultaneously. The proposed method was applied to the standard IEEE 30-bus test system. The results show that solving the multi-objective OPF problem by the Cultural-based Differential Evolution is more effective than other swarm intelligence methods in the literature.

Multi-Objective Optimal Power Flow Solutions Using Differential Search Algorithm

2014 ◽  
Vol 1077 ◽  
pp. 241-245
Author(s):  
Isaree Srikun
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Search Algorithm ◽  
Test System ◽  
System Operation ◽  
Power System Operation ◽  
Multi Objective ◽  
Optimal Power ◽  
Generation Cost ◽  
And Control

This paper presents a Differential Search Algorithm for solving a multi-objective Optimal Power Flow (OPF) in support of power system operation and control . The multi-objective OPF was formulated for tackling with total generation cost and environmental impacts simultaneously. The proposed method was applied to the standard IEEE 30-bus test system. The results show that solving the multi-objective OPF problem by the Differential Search Algorithm is more effective than other swarm intelligence methods in the literature.

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