Automatic generation control of power systems with unified power flow controller by improved grasshopper optimization algorithm

2020 ◽  
Author(s):  
Pabitra Mohan Dash ◽  
Sangram Keshori Mohapatra ◽  
Asini Kumar Baliarsingh
Keyword(s):  
Power Systems ◽  
Optimization Algorithm ◽  
Power Flow ◽  
Automatic Generation ◽  
Automatic Generation Control ◽  
Unified Power Flow Controller ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization ◽  
Power Flow Controller ◽  
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.

scholarly journals AGC of multi area power system based PSO under deregulated conditions

2018 ◽  
Vol 7 (3) ◽  
pp. 1446
Author(s):  
Ahmed Jasim Sultan ◽  
Falah Noori Saeed
Keyword(s):  
Power Flow ◽  
Optimization Technique ◽  
Automatic Generation ◽  
Automatic Generation Control ◽  
System Response ◽  
Area Control Error ◽  
Particle Swarm Optimization Technique ◽  
Power Flow Controller ◽  
Generation Control ◽  
Tie Line

In This research PIDF (Proportional Integral Derivative with Filter) is suggested to control the ACE (area control error) signal of automatic generation control circuit (AGC) for two-area multi units system under deregulated conditions, each area consist of two thermal reheat units with physical GRC (generating rate constrain). The parameters of the PIDF controller are tuned using PSO (particle swarm optimization) technique. To improve the system performance, Redox Flow Batteries (RFB) is presented in one area and one of FACTS components IPFC (Inter Line Power Flow Controller) is installed in tie line. The performance of the proposed controller is assessed under different working conditions of deregulated power market. Finally, a comparison will be made on the system response when testing with varying the load conditions and system parameter through MATLAB environment 2015Rb.  

scholarly journals Optimal Power Flow Controller for Grid-Connected Microgrids using Grasshopper Optimization Algorithm

Electronics ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 111 ◽  
Author(s):  
Touqeer Jumani ◽  
Mohd Mustafa ◽  
Madihah Rasid ◽  
Nayyar Mirjat ◽  
Mazhar Baloch ◽  
...  
Keyword(s):  
Dynamic Response ◽  
Power Quality ◽  
Optimization Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Harmonic Distortion ◽  
Optimal Power ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization ◽  
Power Flow Controller

Despite the vast benefits of integrating renewable energy sources (RES) with the utility grid, they pose stability and power quality problems when interconnected with the existing power system. This is due to the production of high voltages and current overshoots/undershoots during their injection or disconnection into/from the power system. In addition, the high harmonic distortion in the output voltage and current waveforms may also be observed due to the excessive inverter switching frequencies used for controlling distributed generator’s (DG) power output. Hence, the development of a robust and intelligent controller for the grid-connected microgrid (MG) is the need of the hour. As such, this paper aims to develop a robust and intelligent optimal power flow controller using a grasshopper optimization algorithm (GOA) to optimize the dynamic response and power quality of the grid-connected MG while sharing the desired amount of power with the grid. To validate the effectiveness of proposed GOA-based controller, its performance in achieving the desired power sharing ratio with optimal dynamic response and power quality is compared with that of its precedent particle swarm optimization (PSO)-based controller under MG injection and abrupt load change conditions. The proposed controller provides tremendous system’s dynamic response with minimum current harmonic distortion even at higher DG penetration levels.

A Probabilistic Multi-Objective Approach for Power Flow Optimization in Hybrid Wind-Based Power Systems Using Grasshopper Optimization Algorithm

2020 ◽  
Vol 11 (4) ◽  
pp. 61-86
Author(s):  
Barun Mandal ◽  
Provas Kumar Roy
Keyword(s):  
Power Systems ◽  
Optimization Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Thermal Power ◽  
Optimal Power ◽  
Valve Point Effect ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization ◽  
Practical Constraints

This article introduces a grasshopper optimization algorithm (GOA) to efficiently prove its superiority for solving different objectives of optimal power flow (OPF) based on a mixture thermal power plant that incorporates uncertain wind energy (WE) sources. Many practical constraints of generators, valve point effect, multiple fuels, and the various scenarios incorporating several configurations of WEs are considered for both singles along with multi-objectives for the OPF issue. Within the article, the considered method is verified on two common bus experiment systems, i.e. IEEE 30-bus as well as the IEEE 57-bus. Here, the fuel amount minimization and emission minimization are studied as the primary purposes of a GOA-based OPF problem. However, the proposed algorithm yields a reasonable conclusion about the better performance of the wind turbine. Computational results express the effectiveness of the proposed GOA approach for the secure and financially viable of the power system under various uncertainties. The comparison is tabulated with the existing algorithms to provide superior results.

Sign in / Sign up

Export Citation Format

Share Document