Automatic Generation Control Study Research Articles

Application of an intelligent fuzzy logic based sliding mode controller for frequency stability analysis in a deregulated power system using OPAL-RT platform

Owing to unpredicted power demand, integration of distributed generators and parametric disparity in the system cause the power system more intricacy which in turn affects the frequency and power fluctuation critically. To mitigate these phenomena, an intelligent and efficient automatic generation control (AGC) is indispensable. Therefore, in this paper, an intelligent and robust controller named fuzzy sliding mode controller (FSMC) has been recommended to tackle the AGC problem in a deregulated power system in the presence of distributed generators effectively. Again, to manifest its dominance over SMC, fuzzy-PID and PID controllers, dynamic response of the deregulated system under Poolco, Bilateral and Contract violation conditions has been evaluated and compared. Further, to support the FSMC controller’s ability, another test model has been taken for the AGC study. The gains of these controllers have been enumerated by Gannet Optimization Algorithm (GOA) subjecting to a minimization problem. Exploration phase of GOA involves two steps, namely U- & V-shaped diving patterns of Gannets and exploitation phase again involves two steps namely sudden rotation and random walk of Gannets. These four steps ensures quick convergence of the objective function to its optimal value. Apart from transient response under different power transaction conditions, parametric uncertainties of the system, solar and wind power variation and abrupt load change have been considered to support the robustness & credibility of FSMC controller. In addition to this, the stability of the proposed model has been analyzed in the frequency domain. Finally, the MATLAB/SIMULINK based transient response has been validated by a real-time simulator using OPAL-RT-4510, Xilinx Kintex-7 FPGA software.

Comparative Performance Investigation of Genetic Algorithms (GAs), Particle Swarm Optimization (PSO) and Bacteria Foraging Algorithm (BFA) Based Automatic Generation Control (AGC) with Multi Source Power Plants (MSPPs)

This paper presents comparative performance analysis of GAs, PSO and BFA technique-based AGC regulators with MSPPs in each system. Each control area consists of hydro, thermal and gas power plants (HTGPPs) for generation of electricity. In this work, proportional integral derivative (PID) control structure-based AGC regulators are designed by using the above intelligent techniques. However, the cost function for designing of these intelligent controllers is formulated using the integral square error (ISE) performance index. In the previous AGC studies, simulation time for tuning of above intelligent AGC controller to analyze performance was not reported. Therefore, this research work proposes a new study to investigate the performance of these intelligent AGC controllers based upon performance indicators: (i) simulation time of these techniques, (ii) first peak value of transient response, (iii) oscillations in transient response and (iv) settling time of transient response. The parameters of the controllers are evaluated using these techniques and investigations are carried out to find the best performance of the system. Besides, system dynamic performance of BFA-tuned AGC controllers are also demonstrated for +1% to +4% step load disturbance in the respective control areas.

Generation‐based automatic generation control with multisources power system using bacterial foraging algorithm

AbstractThis article presents an application of bacterial foraging algorithm (BFA) for design and implementation of generation‐based PID structured automatic generation control (AGC) in a 2‐area multisources power system with hydro, thermal, and gas power plants incorporated in each area. Most of AGC studies carried out so far have considered the initial system loading to be equal to 50% of the area generation capacity. But, AGC controller parameters are uncertain due to stochastic nature of power demand of the end users. Hence, in this article, the design of AGC controller is proposed on the basis of generation schedule by incorporating changes in power system gain constant, power system time constant, frequency bias constant, and so on. The dynamic responses of power system with BFA tuned AGC controller are compared with the genetic algorithm tuned AGC controller. The parameters of the controllers are evaluated by using these techniques and investigations are carried out to find the best performance of the system. Therefore, it is desirable to find the parameters of the generation‐based controller depending upon the contribution of its constituent hydro, thermal, and gas energy sources in the total power generation.

Application of hybrid crow-search with particle swarm optimization algorithm in AGC studies of multi-area systems

This article presents the hybridization of crow-search algorithm with particle swarm optimization (hCA-PSO) in automatic generation control (AGC) studies. A new controller termed by integral-minus-tilt-derivative-control with filter (I-TDN) is proposed and its dynamics are compared with PIDN and TIDN. The proposed controller parameters are optimized by the proposed hCA-PSO technique and are compared with CA, PSO algorithms and are found to be better in terms of settling time, oscillation magnitude. Moreover, the integration of HVDC tie-lines improves system dynamics over AC tie-line. Further, sensitivity analysis suggests that system dynamics with I-TDN controller optimized by hCA- PSO technique obtained at diverse and nominal conditions are robust.

Fractional order cascaded controller for AGC study in power system with PV and diesel generating units

This paper emphases on automatic generation control (AGC) of a two-area power system comprising of different diversified sources such as hydro, thermal, wind, photo voltaic (PV), and diesel. Integration of a PV unit brings the intricacy in the system frequency and tie-line power fluctuation due to lack of damping under normal and severe load change. To overcome this problem a novel three degrees of freedom cascade controller incorporated with derivative filter (N) (3DOF-FOPIDN-FOPDN) controller is designed by endorsing a maiden application of WGA (Wild Goat Algorithm) algorithm to reach out an improved dynamic performance. The proficiency of 3DOF-FOPIDN-FOPDN controller against a random load perturbation as well as power fluctuation in PV unit, stands tall which ensures the robustness of the controller.

Novel application of optimal fuzzy‐adaptive symbiotic organism search‐based two‐degree‐of‐freedom fuzzy proportional integral derivative controller for automatic generation control study

Novel application of optimal fuzzy‐adaptive symbiotic organism search‐based two‐degree‐of‐freedom fuzzy proportional integral derivative controller for automatic generation control study

Application of Fractional Order Cascaded Controller for AGC Study in Power System Integrated With Renewable Sources

The intent of this paper assimilates the issues of automatic generation control (AGC) of a two-area power system entailing five numbers of renewable as well as conventional sources such as thermal unit, hydro unit, wind unit, diesel unit, and photovoltaic (PV) unit. To make the proposed model more realistic, some non-linearities like boiler dynamics, governor dead band (GDB), and generation rate limit (GRC) are inducted into their concerned sources. The frequency stability of the system is enhanced by assuaging the transient indices like undershoot, overshoot, rise time, and settling time by employing two degrees of freedom (2-DOF) based fractional order (FO) cascaded controller incorporating with derivative filter (N) named 2-DOF-FOPIDN-FOPDN controller. The proposed controller along with 2-DOF-PIDN-PDN, and PID controllers are designed by endorsing selfish herd optimization technique (SHOT). The performance of the proposed controller is corroborated by comparing the performance exhibited by 2-DOF-PIDN-PDN, and PID controllers. Besides this, the know-how of the recommended controller is evaluated and investigated against solar power variation, load perturbation, and system’s parameter deviation which confers the robustness of the controller is conceived.

A Novel Hybrid Salp Swarm Differential Evolution Algorithm Based 2DOF Tilted-Integral-Derivative Controller for Restructured AGC

This article elevates the study of Automatic Generation Control (AGC) for a multisource interconnected power system under the restructured environment. Physical constraints such as Generation Rate Constraints (GRC), Governor Dead Band (GDB) and Boiler Dynamics (BD) are incorporated into the system for a more realistic approach. Distribution Generation (DG) system is also considered to incorporate the effects of renewable energy sources penetration. A novel cascaded topology of 2-Degree of Freedom Tilted-Integral-Derivative Controller with filter (2DOF-TIDN) is proposed for anticipated AGC mechanism. A maiden application of Hybrid Salp Swarm Differential Evolution Algorithm (HSSDEA) has been successfully applied to get the different optimum gains of the proposed controller. Capacitive Energy Storage (CES) system is also incorporated for the proposed system for the AGC mechanism. The supremacy of the proposed controller is examined by comparing with other well-known or benchmark controllers. The robustness of the proposed system has been analyzed for the contract violation case of deregulation. Finally, the efficacy of the proposed work has been verified by comparing with the previously published work of literature on same platform.

Study of automatic generation control in two area power system with DFIG-based wind energy conversion

<p class="IEEEAbtract">The main objective of Automatic Generation Control (AGC) is to keep the frequency within specified limits through primary and secondary control. In this study, a model of two area thermal non-reheat power system with integration of Doubly Fed Induction Generator (DFIG) based Wind Energy Conversion (WEC) into both areas is presented. A Proportional Integral Derivative (PID) controller and a Fuzzy Logic Controller (FLC) have been applied and compared. The Proposed controllers are used to improve the dynamic response as well as to reduce or eliminate the steady-state error in Area Control Error (ACE). FLC has been offered better and faster performance over the PID controller. The results obtained prove the impact of DFIG-based WEC on AGC and confirm the participation of the DFIG in the frequency system.</p>

Optimal AGC Design for Diverse Sources of Power Generations in each Area Using Output Vector Feedback Control Technique

In this paper an attempt is made to design the regulator for automatic generation control (AGC) of an interconnected energy delivery system to regulate the frequency and tie-power to original value for sudden change in the energy demand of the customers. The considered energy delivery system is having the power generation via thermal, hydro and gas sources and connected via means of parallel AC/DC tie-lines. Further, most of AGC studies focussed on regulator design using application of control theory such as optimal control to manage the balance between generation and load demand considering all system states. However, inreality it is hard enough to measure all system states and design effective regulator for AGC action. Hence in this paper efforts are made to design regulator for AGC problem using few states which are easily measurable and available in real situation of the system i.e. output vector feedback. The feasibility & stability of proposed AGC is tested for 1% change in power demand and compared with optimal AGC which is based on all system states using obtained system responses, feedback gains of control as well as closed loop eigenvalues.

Hybrid-Peak-Area-Based Performance Index Criteria for AGC of Multi-Area Power Systems

The dynamic performance of automatic generation control (AGC) primarily relies upon the performance index criteria (PIC) being used to optimize the supplementary controller gains. Most of the previous AGC studies were focused on developing various intelligent controllers and meta-heuristic algorithms to improve the system dynamic performance of the AGC system. However, no significant efforts were made to formulate effective PICs in order to acquire better supplementary control and improved AGC dynamic performance. In this paper, a maiden attempt has been made and new hybrid-peak-area-based PICs have been proposed for the optimal tuning of supplementary controller gains. The proposed PICs have been implemented upon single area as well as standard New England IEEE 39 bus system. Sensitivity analysis has also been carried out to demonstrate the superiority of the proposed PICs for wide changes in AGC power system model parameters. The proposed PICs demonstrate better dynamic performance in comparison to existing PICs in terms of overshoot, subsequent oscillations, and settling time.

Real‐time parameter estimation based intelligent controllers for AGC operation under varying power system dynamic conditions

In this paper, real-time parameter estimation based intelligent controller has been proposed for the optimum automatic generation control (AGC) operation of multi-area interconnected power system. In earlier AGC studies, supplementary controllers were designed for presumed power system dynamic conditions, such as constant system loadings, fixed values of power system dynamic model parameters. However in practical AGC system, these power system model parameters, namely frequency bias parameter B, steam chest and reheater time constants & , power system time and gain constants & , load sensitivity factor D, etc., continuously varies depending upon the consumer's load demand and number of power generating units participating in AGC. The controller's operation no longer remains optimum as these system parameters changes from their initial values. In view of the above, parameter estimation based real-time intelligent controller has been designed which automatically adjusts its controller gain settings to its optimum conditions in real-time after sensing changes in power system model parameters. At first, different methodologies are presented to estimate dominant power system model parameters. Then, presented methodologies are utilised in the design of intelligent controller for AGC system. The proposed controller is successfully tested upon IEEE 39 bus system with various case studies.

AGC of Two Area Power System Based on Different Power Output Control Strategies of Thermal Power Generation

In this paper, dynamic performance of automatic generation control (AGC) of two area thermal–thermal power system is determined through the steam chest and reheater constant trajectories. In earlier AGC studies, steam chest and reheater time constants denoted as ${T_{\text{SC}}}$ and ${T_{\text{RH}}}$ are considered to be constant, irrespective of plant generation schedules. However, it is discovered that ${T_{\text{SC}}}$ and ${T_{\text{RH}}}$ follow the specific trajectories with the plant generation schedules. These time constant trajectories are determined by the power output control strategies being employed to change the plant generation schedules. These control strategies are the different combinations of steam pressure versus flow rate curves used to operate the plant at different generation schedules. In this paper, time constant versus generation schedule trajectories of ${T_{\text{SC}}}$ and ${T_{\text{RH}}}$ have been derived for different power output control strategies. Furthermore, these time constant trajectories have been utilized to investigate the dynamic performance of two area reheat thermal power system.

Discrete Data AGC of Hydrothermal Systems Under Varying Turbine Time Constants Along With the Power System Loading Conditions

The paper deals with the discrete data automatic generation control (AGC) of two area hydrothermal power system operating at different loading conditions. The power system load varies considerably throughout the day and accordingly, thermal and hydropower systems are scheduled to operate at different loading conditions. It is found that steam as well as hydro turbine time constants vary as the power system loading varies. In earlier AGC studies, these parameters are considered to be constant, irrespective of power system loadings. This paper studies the dynamic performance of hydrothermal power system considering the variation of these turbine time constants along with the nominal loading of power system. The studies have been conducted for linear as well as nonlinear models of speed governor and hydroturbine models recommended by the IEEE committee. It is also discovered that conventional empirical formula-based hydraulic governor settings recommended by the IEEE working group are completely unacceptable for hydrothermal power system. A maiden attempt is made to optimize the hydraulic governor settings simultaneously along with the controller gains using metaheuristic algorithm. The comparison of system dynamic responses reveal that optimization-based hydrogovernor settings give the better dynamic performance in case of linear as well as nonlinear models of hydro system, and therefore are strongly recommended over the conventional settings. The paper also deals with the optimum selection of sampling periods for discrete data AGC operation of hydrothermal systems.

Application of Edge theorem for robust stability analysis of a power system with participating wind power plants in automatic generation control task

This study investigates the dynamic participation of wind power plants (WPPs) in the automatic generation control (AGC) task. The pre-specified model of wind farm in the AGC studies has been used. It is shown that operating of WPPs at the command mode results in a significant improvement in the frequency behaviour of power system due to their faster response. However, the WPPs may change their operation mode from the command mode to the maximum power point mode according to the wind speed conditions and load variations. This reduces the improvement in the frequency response. In this condition, the shortage in the wind power should be compensated by the conventional units. Thus, the share of different units becomes uncertain (but bounded) when the WPPs participate in the AGC task. To address this challenge, this study provides the robust stable frequency operation of power system under uncertain shares of different units in the AGC task using the Edge theorem. Simulations are performed on an IEEE 39-bus test system connected to some wind farms in different buses. Results confirm the robust stability of the underlying power system, and hence, the effective capability of the wind farms to participate in the AGC task.

Optimal AGC regulator for multi-area interconnected power systems with parallel AC/DC links

AbstractThe problem of simultaneous tuning of the automatic generation control (AGC) regulator’s gains of multi-area interconnected power system is carried out in this manuscript. Based on the types of area interconnections, a power system model consisting of reheat turbines is investigated by two test cases for the AGC study. In one of the test case AC link is used as area interconnection, whereas the parallel combination of AC/DC links is used as area interconnection in other test case. Each test case control area is consisting of plants with reheat thermal turbines. Genetic algorithm (GA) is used to globally optimize the gains of proportional integral-based AGC regulators with simultaneous optimization of frequency bias coefficient and tie-line power flows. The dynamic response curves are obtained for various system states with the implementation of designed GA-based AGC regulators considering 1% load perturbation in one of the areas. The conventional AGC regulators are also developed using the popular...

Design and analysis of multi-source multi-area deregulated power system for automatic generation control using quasi-oppositional harmony search algorithm

The present article focuses on the study of automatic generation control (AGC) of a realistic power system having a distinct combination of multi-area multi-source generating units in each control area under deregulated framework. An attempt is made in this paper to integrate reheat thermal, hydro and gas generating unit in a single control area and, then, extended this combination to five control areas. In this work, six reheat thermal, six hydro and three gas generating units are taken into account for the modeling of five-area power system. Some important physical constraints like time delay, governor dead band and generation rate constraint are imposed in the power system dynamics to get an accurate perception of the deregulated AGC subject. The highlighting features of the present work are to model, simulate, optimize and co-relate their inter-related dynamic performances for the purpose of AGC study. For such a complex AGC model, the vital role of the proposed quasi-oppositional harmony search (QOHS) algorithm, as an optimizing tool, is signified while solving the AGC problem in deregulated regime. The simplicity of the structure and acceptability of the responses of the well-known proportional–integral–derivative controller, inherently, enforces to employ in this work. The three classes of extensive deregulated cases (in the presence of load following and physical constraints) are demonstrated by examining the closed loop performance of the studied model. The simulation results show that the designed power system model may be a feasible one and the proposed QOHS algorithm may be a promising optimization technique under these circumstances.

Automatic generation control of multi‐unit multi‐area deregulated power system using a novel quasi‐oppositional harmony search algorithm

This initiative work deals with the automatic generation control (AGC) of multi-unit multi-area power system in the prospective of deregulated power environment owing to load following issues. In present outlook, a deregulated four-area power system having eight generation companies and eight distribution companies is treated as a plant model. The concerned objective is to intensify the bilateral behaviour and investigate the system AGC performance. In the state of deregulation, the influence of a novel quasi-oppositional harmony search (QOHS) algorithm based Sugeno fuzzy-logic (SFL) technique is proposed as an AGC optimisation task by showing its consequences on bilateral policy/dynamics. In the entire work, the proposed QOHS based SFL technique is incorporated for the tuning of on-line, off-nominal controller gains. The salient advantage of this control strategy is to provide good dynamic responses over a wide range of system parametric variations. The observations are based on the three deregulated cases which, generally, takes place in deregulated power market. The presented simulation results show that the proposed QOHS based SFL is a promising optimisation technique in the field of deregulated AGC study.

Slow dynamics model of compressed air energy storage and battery storage technologies for automatic generation control

Increasing variable generation penetration and the consequent increase in short-term variability makes energy storage technologies look attractive, especially in the ancillary market for providing frequency regulation services. This paper presents slow dynamics model for compressed air energy storage and battery storage technologies that can be used in automatic generation control studies to assess the system frequency response and quantify the benefits from storage technologies in providing regulation service. The paper also represents the slow dynamics model of the power system integrated with storage technologies in a complete state space form. The storage technologies have been integrated to the IEEE 24 bus system with single area, and a comparative study of various solution strategies including transmission enhancement and combustion turbine have been performed in terms of generation cycling and frequency response performance metrics.

Automatic generation control of power system using a novel quasi-oppositional harmony search algorithm

Abstract The present work approaches a novel quasi-oppositional harmony search (QOHS) algorithm, as an optimization technique, for its optimum performance in the subject area of automatic generation control (AGC) of power system. The proposed QOHS algorithm is applied with an aim to converge rapidly towards the optimal solution(s) that houses both the characters of two guesses, i.e. opposite-point and quasi-opposite point. The area of concern of this study is to discuss the multi-objective problems of an interconnected power system for the benefits of AGC. The proposed QOHS algorithm is, individually, applied to single-area, precede to two-area considering the non-linearity effects of governor dead band and generation rate constraint and, finally, extended to four-area power system showing the consequences of multiple load disturbances. A case of robustness and stability analysis are also investigated for the studied two-area power system model. The control strategy, for the dynamic power system model, is based on area control error. The simplicity of the structure and acceptability responses of the well-known proportional–integral–derivative controller enforces to implement as a controller in this work. The comparative evaluation of the proposed QOHS algorithm is carried out by the way of comparing the dynamic performances of the studied power system model with those offered by other algorithms reported in the recent state-of-the-art literature. The simulation works, presented in the paper, reveal that the proposed QOHS algorithm may be effectively utilized for the purpose of AGC study of power system having varying degrees of complexities and non-linearities. Moreover, the proposed QOHS based control strategy adopted in this work provides a robust and stable speed control mechanism.