AGC of a multi-area multi-source hydrothermal power system interconnected via AC/DC parallel links under deregulated environment

Arya, Yogendra; Kumar, Narendra

doi:10.1016/j.ijepes.2015.08.015

Cited by 100 publications

(90 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For us to express the ability of the optimal control strategy to cope with large interconnected systems, the study is also extended to an unequal 3‐area system having reheat thermal units in each area with generation rate constraint (GRC) . In practice, because of physical operating limits of the boiler characteristics, power generation in steam plants can vary only in a limited range known as GRC . A saturation limit (±0.03 pu/second) is considered to imitate practical limit on the response of the turbine .…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…In a restructured or deregulated power environment, GENCOs, DISCOs, transmission companies, and independent system operator operate the power sector, while monopoly of vertically integrated utilities does not exist . However, AGC objectives do not alter in restructured environment.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…And in hybrid scenario, contracts between DISCOs and GENCOs do not follow the area boundary restrictions. To ensure area regulation, independent system operator, the impartial entity, clears all these power contracts . The concept of DISCO participation matrix (DPM) is used to operate these contracts .…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…The design of optimal controllers is reported in literature . The optimal control law of AGC system is given by Equation and a quadratic cost performance index

normalJ = true {true\int}_{0}^{\infty} \frac{1}{2} ([],, X^{T} {QX + normalU}^{T} RU) dt

is given by

U^{*} = {- normalK}^{*} normalX,

where

{K^{*} = normalR}^{- 1} B^{T} normalP,

and the matrix P is the solution of continuous time algebraic matrix Riccati equation

{PA + normalA}^{T} {normalP - PBR}^{- 1} B^{T} normalP + normalQ = 0 .

…”

Section: Design Of Optimal Agc Controllersmentioning

confidence: 99%

“…The research works reported in the literature on AGC using modern optimal control strategy pertains to various types of single and multiarea power systems . But no work has been witnessed so far in the literature to present a comparative study of various performance parameters between AGC controller designed using modern optimal control theory and classical controller optimized using various recent artificial intelligent techniques.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Optimal control strategy–based AGC of electrical power systems: A comparative performance analysis

Arya¹,

Kumar

2017

Optim Control Appl Methods

Self Cite

View full text Add to dashboard Cite

Summary This study extensively addresses the application of optimal control approach to the automatic generation control (AGC) of electrical power systems. Proportional‐integral structured optimal controllers are designed using full‐state feedback control strategy employing performance index minimization criterion. Some traditional single/multiarea and restructured multiarea power system models from the literature are explored deliberately in the present study. The dynamic performance of optimal controllers is observed superior in comparison to integral/proportional‐integral controllers tuned using some recently published modern heuristic optimization techniques. It is observed that optimal controllers show better system results in terms of minimum value of settling time, peak overshoot/undershoot, various performance indices, and oscillations corresponding to change in area frequencies and tie‐line powers along with maximum value of minimum damping ratio in comparison to other controllers. The results are displayed in the form of tables for ease of comparison. Sensitivity analysis affirms the robustness of the optimal feedback controller gains to wide variations in some system parameters from their nominal values.

show abstract

Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…The design of optimal controllers is reported in literature . The optimal control law of AGC system is given by Equation and a quadratic cost performance index

normalJ = true {true\int}_{0}^{\infty} \frac{1}{2} ([],, X^{T} {QX + normalU}^{T} RU) dt

is given by

U^{*} = {- normalK}^{*} normalX,

where

{K^{*} = normalR}^{- 1} B^{T} normalP,

and the matrix P is the solution of continuous time algebraic matrix Riccati equation

{PA + normalA}^{T} {normalP - PBR}^{- 1} B^{T} normalP + normalQ = 0 .

…”

Section: Design Of Optimal Agc Controllersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Optimal control strategy–based AGC of electrical power systems: A comparative performance analysis

Arya¹,

Kumar

2017

Optim Control Appl Methods

Self Cite

View full text Add to dashboard Cite

show abstract

PID‐RLNN controllers for discrete mode LFC of a three‐area hydrothermal hybrid distributed generation deregulated power system

Das

Bera

Sarkar

2021

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary The inequality between active power generation and load demand due to volatile power generation and random changes of load poses a challenge to maintain the system frequency. To address this, in the present work, reinforced learning neural network based–proportional‐integral‐derivative (PID‐RLNN) controllers are proposed in the discrete mode load frequency control (LFC) problems for a three‐area hydrothermal hybrid distributed generation (HDG) deregulated power system. The proposed power system is incorporated with super conducting magnetic energy storage system (SMES), and each control area is interconnected via AC/DC parallel links. The dynamic responses using PID‐RLNN controllers are compared with PID controllers and RLNN controllers for different loading conditions. The gains and parameters of all the controllers are optimized using grasshopper optimization algorithm (GhOA). Investigation reveals that the PID‐RLNN controllers give better dynamic performances compared to PID and RLNN controllers for different loading conditions. Sensitivity analyses are performed to investigate the robustness of the proposed controllers, and investigation reveals that their performances are quite robust for variation of inertia constant and loading conditions. The fluctuation of loads in each area is also considered to analyze the performances of proposed controllers and it is seen that the proposed PID‐RLNN controllers damp the oscillations of dynamic responses.

show abstract

Frequency regulation for microgrid using genetic algorithm and particle swarm optimization tuned STATCOM

Saxena¹,

Gao

Sharma

et al. 2022

Circuit Theory & Apps

View full text Add to dashboard Cite

This paper presents the genetic algorithm (GA) and particle swarm optimization (PSO) based frequency regulation for a wind‐based microgrid (MG) using reactive power balance loop. MG, operating from squirrel cage induction generator (SCIG), is employed for exporting the electrical power from wind turbines, and it needs reactive power which may be imported from the grid. Additional reactive power is also required from the grid for the load, directly coupled with such a distributed generator (DG) plant. However, guidelines issued by electric authorities encourage MGs to arrange their own reactive power because such reactive power procurement is defined as a local area problem for power system studies. Despite the higher cost of compensation, static synchronous compensator (STATCOM) is a fast‐acting FACTs device for attending to these reactive power mismatches. Reactive power control can be achieved by controlling reactive current through the STATCOM. This can be achieved with modification in current controller scheme of STATCOM. STATCOM current controller is designed with reactive power load balance for the proposed microgrid in this paper. Further, gain values of the PI controller, required in the STATCOM model, are selected first with classical methods. In this classical method, iterative procedures which are based on integral square error (ISE), integral absolute error (IAE), and integral square of time error (ISTE) criteria are developed using MATLAB programs. System performances are further investigated with GA and PSO based control techniques and their acceptability over classical methods is diagnosed. Results in terms of converter frequency deviation show how the frequency remains under the operating boundaries as allowed by IEEE standards 1159:1995 and 1250:2011 for integrating renewable‐based microgrid with grid. Real and reactive power management and load current total harmonic distortions verify the STATCOM performance in MG. The results are further validated with the help of recent papers in which frequency regulation is investigated for almost similar power system models. The compendium for this work is as following: (i) modelling of wind generator‐based microgrid using MATLAB simulink library, (ii) designing of STATCOM current controller with PI controller, (iii) gain constants estimation using classical, GA and PSO algorithm through a developed m codes and their interfacing with proposed simulink model, (v) dynamic frequency responses for proposed grid connected microgrid during starting and load perturbations, (vi) verification of system performance with the help of obtained real and reactive power management between STATCOM and grid, and (vii) validation of results with available literature.

show abstract

AGC of a multi-area multi-source hydrothermal power system interconnected via AC/DC parallel links under deregulated environment

Cited by 100 publications

References 57 publications

Optimal control strategy–based AGC of electrical power systems: A comparative performance analysis

Optimal control strategy–based AGC of electrical power systems: A comparative performance analysis

PID‐RLNN controllers for discrete mode LFC of a three‐area hydrothermal hybrid distributed generation deregulated power system

Frequency regulation for microgrid using genetic algorithm and particle swarm optimization tuned STATCOM

Contact Info

Product

Resources

About