scholarly journals Correction to: Grasshopper optimization algorithm optimized multistage controller for automatic generation control of a power system with FACTS devices

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Pratap Chandra Nayak ◽  
Ramesh Chandra Prusty ◽  
Sidhartha Panda
Keyword(s):  
Power System ◽  
Optimization Algorithm ◽  
Automatic Generation ◽  
Automatic Generation Control ◽  
Facts Devices ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization ◽  
Generation Control

scholarly journals Grasshopper optimization algorithm optimized multistage controller for automatic generation control of a power system with FACTS devices

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Pratap Chabdra Nayak ◽  
Ramesh Chandra Prusty ◽  
Sidhartha Panda
Keyword(s):  
Power System ◽  
Real Time ◽  
Optimization Algorithm ◽  
Automatic Generation ◽  
Pi Controller ◽  
Automatic Generation Control ◽  
Facts Devices ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization ◽  
Generation Control

AbstractThis paper uses a Grasshopper Optimization Algorithm (GOA) optimized PDF plus (1 + PI) controller for Automatic generation control (AGC) of a power system with Flexible AC Transmission system (FACTS) devices. Three differently rated reheat turbine operated thermal units with appropriate generation rate constraint (GRC) are considered along with different FACTS devices. A new multistage controller design structure of a PDF plus (1 + PI) is introduced in the FACTS empowered power system for AGC while the controller gains are tuned by the GOA. The superiority of the proposed algorithm over the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithms is demonstrated. The dynamic responses of GOA optimized PDF plus (1 + PI) are compared with PIDF, PID and PI controllers on the same system. It is demonstrated that GOA optimized PDF plus (1 + PI) controller provides optimum responses in terms of settling time and peak deviations compared to other controllers. In addition, a GOA-tuned PDF plus (1 + PI) controller with Interline Power Flow Controller (IPFC) exhibits optimal results compared to other FACTS devices. The sturdiness of the projected controller is validated using sensitivity analysis with numerous load patterns and a wide variation of parameterization. To further validate the real-time feasibility of the proposed method, experiments using OPAL-RT OP5700 RCP/HIL and FPGA based real-time simulations are carried out.

Automatic Generation Control of Interconnected Power System using Cuckoo Optimization Algorithm

2015 ◽  
Vol 4 (2) ◽  
pp. 22-35
Author(s):  
Shanchari Laik ◽  
Shatabdi Dey ◽  
Puja Das ◽  
Sneha Sultana ◽  
Sourav Paul ◽  
...  
Keyword(s):  
Power System ◽  
Optimization Algorithm ◽  
Dynamic Performance ◽  
Automatic Generation ◽  
Automatic Generation Control ◽  
Interconnected System ◽  
Cuckoo Optimization Algorithm ◽  
Interconnected Power System ◽  
Generation Control ◽  
Tie Line

Automatic generation control (AGC) is added in power system to ensure constancy in frequency and tie-line power of an interconnected multi-area power system. In this article, proportional integral (PI) controlled based AGC of two-area hydrothermal system is solved by cuckoo optimization algorithm (COA). It is one of the most powerful stochastic real parameter optimization in current use. The design objective is to improve the dynamic performance of the interconnected system following a disturbance. System performance is examined considering 1% step load perturbation in thermal area with generation rate constraints. The results are compared with BBO, GA and DE to show the effectiveness of the proposed method. Computed results shows that the proposed method effectively improve the performance of the objective function with corresponding minimization of the overshoot, undershoot and settling time to reach steady state.

Sign in / Sign up

Export Citation Format

Share Document