Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

A Comparison on PSO Optimized PID Controller for Inter-Area Oscillation Control in an Interconnected Power System

A Comparison on PSO Optimized PID Controller for Inter-Area Oscillation Control in an... This paper emphasizes on the development of control strategy for inter area oscillation suppression for a unified two-area hydro-thermal deregulated power system. A particle swarm optimization (PSO) optimized Proportional Integral Derivative (PID) controller is proposed for automatic generation control (AGC). Further comparison between different variants of PSO are carried out, where 6 different variants have been explored, which are success rate based PSO, evolution speed and aggregation degree factors based PSO, global-local best inertia weight based PSO, distance from global best based PSO, fixed inertia weight based PSO and varying acceleration coefficients based PSO. A comprehensive analysis of these optimization techniques are presented on the basis of major dynamic performance parameters, i.e. settling time and peak overshoot. Successive rate based PSO variant found best among these six variants. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Technology and Economics of Smart Grids and Sustainable Energy Springer Journals

A Comparison on PSO Optimized PID Controller for Inter-Area Oscillation Control in an Interconnected Power System

Download PDF
14 pages

Loading next page...
 
/lp/springer-journals/a-comparison-on-pso-optimized-pid-controller-for-inter-area-f3Lq0xWiyn
Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2022
eISSN
2199-4706
DOI
10.1007/s40866-022-00127-0
Publisher site
See Article on Publisher Site

Abstract

This paper emphasizes on the development of control strategy for inter area oscillation suppression for a unified two-area hydro-thermal deregulated power system. A particle swarm optimization (PSO) optimized Proportional Integral Derivative (PID) controller is proposed for automatic generation control (AGC). Further comparison between different variants of PSO are carried out, where 6 different variants have been explored, which are success rate based PSO, evolution speed and aggregation degree factors based PSO, global-local best inertia weight based PSO, distance from global best based PSO, fixed inertia weight based PSO and varying acceleration coefficients based PSO. A comprehensive analysis of these optimization techniques are presented on the basis of major dynamic performance parameters, i.e. settling time and peak overshoot. Successive rate based PSO variant found best among these six variants.

Journal

Technology and Economics of Smart Grids and Sustainable Energy – Springer Journals

Published: Feb 15, 2022

Keywords: Two area power system; Automatic generation control; Proportional integral derivative controller; Deregulated environment; Particle swarm optimization

References

  • Simulation and optimization in an AGC system after deregulation
    Donde, V; Pai, MA; Hiskens, IA
  • Load frequency control issues in power system operations after deregulation
    Christie, RD; Bose, A
  • Bibliography on the fuzzy set theory applications in power systems (1994-2001)
    Bansal, RC
  • Load following in a bilateral market with local controllers
    Abraham, RJ; Das, D; Patra, A
  • AGC simulator for price-based operation-part ii: case study results
    Kumar, J; Ng, K-H; Sheble, G
  • AGC simulator for price-based operation part i: a model
    Kumar, J; Ng, K; Sheblt, G
  • Automatic generation control in a deregulated power system
    Bakken, BH; Grande, OS
  • Evolutionary computation based three-area automatic generation control
    Roy, R; Bhatt, P; Ghoshal, S
  • AGC logic based on NERC’s new control performance standard and disturbance control standard
    Yao, M; Shoults, RR; Kelm, R
  • LFC based adaptive PID controller using ANN and ANFIS techniques
    Mosaad, MI; Salem, F
  • Application of GA based optimal integral gains in fuzzy based active power-frequency control of non-reheat and reheat thermal generating systems
    Ghoshal, SP; Goswami, SK
  • Application of GA / GA-SA based fuzzy automatic generation control of a multi-area thermal generating system
    Ghoshal, SP
  • Optimizations of PID gains by particle swarm optimizations in fuzzy based automatic generation control
    Ghoshal, SP
  • A new load frequency variable structure controller using genetic algorithms
    Al-Hamouz, ZM; Al-Duwaish, HN
  • GA/particle swarm intelligence based optimization of two specific varieties of controller devices applied to two-area multi-units automatic generation control
    Bhatt, P; Roy, R; Ghoshal, S
  • GASA tuned optimal fuzzy regulator for AGC of an interconnected power system
    Hasan, N; Singh, O
  • Fruit fly algorithm-based automatic generation control of multiarea interconnected power system with FACTS and AC/DC links in deregulated power environment
    Shankar, R; Kumar, A; Raj, U; Chatterjee, K
  • Automatic generation control of an interconnected CCGT-thermal system using stochastic fractal search optimized classical controllers
    Saha, D; Saikia, LC
  • Modified sine cosine algorithm-based fuzzy-aided PID controller for automatic generation control of multiarea power systems
    Sahu, PC; Prusty, RC; Sahoo, BK
  • A comprehensive state of the art literature survey on LFC mechanism for power system
    Shankar, R; Pradhan, SR; Chatterjee, K; Mandal, R
  • A hybrid metaheuristic optimisation technique for load frequency control
    Ramjug-Ballgobin, R; Ramlukon, C
  • Energy flow estimation-control of two interconnected microgrids
    Tungadio, DH; Bansal, RC; Siti, MW
  • PID control system analysis, design, and technology
    Ang, KH; Chong, G; Li, Y
  • Two stage optimized fuzzy controlled multi-area system for AGC in smart grid age
    Bhateshvar, YK; Mathur, HD
  • Power-Frequency Balance in multi-generation system using optimized fuzzy logic controller
    Bhateshvar, YK; Mathur, HD; Bansal, RC
  • A novel particle swarm optimization algorithm with adaptive inertia weight
    Nickabadi, A; Ebadzadeh, MM; Safabakhsh, R
  • A modified particle swarm optimizer with dynamic adaptation
    Yang, X; Yuan, J; Yuan, J; Mao, H
  • On the improved performances of the particle swarm optimization algorithms with adaptive parameters, cross-over operators and root mean square (RMS) variants for computing optimal control of a class of hybrid systems
    Arumugam, MS; Rao, MVC
  • Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients
    Ratnaweera, A; Halgamuge, SK; Watson, HC