scholarly journals Dynamic optimal power flow calculates intermittent wind turbine using ant colony method

2021 ◽  
Vol 926 (1) ◽  
pp. 012108
Author(s):  
R P Siwi ◽  
IC Gunadin ◽  
SM Said ◽  
A Siswanto ◽  
S Humena
Keyword(s):  
Power Plant ◽  
Wind Turbine ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Peak Load ◽  
Flow Simulation ◽  
Ant Colony ◽  
Short Time Scale ◽  
System Operation ◽  
Optimal Power

Abstract Intermittent is electrical energy that is not available continuously due to uncontrollable external factors generated by a power plant which conditions vary in a reasonably short time scale. Intermittent can be limited or even mitigated by electricity storage, which is a rapidly growing area of research. In this research, the renewable energy used is the wind turbine. This study aims to schedule an economic generator by considering the intermittent wind turbine. Dynamic optimal power flow calculate Intermittent wind turbine uses ant colony method to determine the value of optimizing system operation with the integrated wind turbine. To determine the optimization value of the system operation, this study use a south sulawesi system consisting of 76 buses, 21 generators, and two wind power plant. From the results of the dynamic optimal power flow simulation, it is found that the generation costs are reduced from the real system costs using the ant colony method when the peak load time is 18.28% and the out peak load time is 18.08%, so that in only two times the ant colony optimization method, can reduce the cost of generation by Rp. 121,123,830.

scholarly journals The Solution for Optimal Power Flow (OPF) Method Using Differential Evolution Algorithm

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Hazel Ariantara ◽  
Sarjiya Sarjiya ◽  
Sasongko Pramono Hadi
Keyword(s):  
Power Plant ◽  
Differential Evolution ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Differential Evolution Algorithm ◽  
Bat Algorithm ◽  
Plant Production ◽  
Optimal Power ◽  
Bus Voltage ◽  
The Cost

Optimal Power Flow (OPF) is one of techniques used to optimize the cost of power plant production while maintaining the limit of system reliability. In this paper, the application of differential evolution (DE) method is used to solve the OPF problem with variable control such as the power plant output, bus voltage tension, transformer tap, and injection capacitor. The effectiveness of the method was tested using IEEE 30 buses. The result shows that this method is better than generic algorithm (GA), particle swarm optimized (PSO), fuzzy GA, fuzzy PSO, and bat-algorithm. The simulation of the power plant systems of 500 kV Java-Bali with the proposed method can reduce the total cost of generation by 13.04% compared to the operating data PT. PLN (Persero).

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.

Sign in / Sign up

Export Citation Format

Share Document