Automatic generation control of a multi area hydrothermal system using reinforced learning neural network controller

This paper deals with automatic generation control (AGC) of a three unequal area hydrothermal system. Reheat turbines in thermal areas and electric governor in hydro area are considered. Appropriate generation rate constraints are considered in the areas. Bacterial foraging (BF) technique is used to simultaneously optimize the integral gains (K_Ii) and speed regulation parameter (R_i) keeping frequency bias fixed at frequency response characteristics. The integral controller in this case is termed as BFIC. The performance of a multilayer perception neural network (MLPNN) controller using reinforcement learning is evaluated for the system. In this reinforcement learning, the weights are dynamically adjusted online using backpropagation algorithm with error being the area control error (ACE). The performance of the MLPNN controller is compared with that of BFIC. Also, the performance of MLPNN controller over a wide range of system loading conditions and step load perturbations is compared with BFIC. Investigations clearly reveal the superior performance of MLPNN controller over BFIC. Sensitivity analysis subject to wide changes in system loading, inertia constant (H) and size and location of step load perturbation is carried out to investigate the robustness of the controller with the optimum K_Ii and R_i obtained at nominal condition.     

Automatic generation control of multi area thermal system using Bat algorithm optimized PD–PID cascade controller

This article presents automatic generation control (AGC) of an interconnected multi area thermal system. The control areas are provided with single reheat turbine and generation rate constraints of 3%/min. A maiden attempt has been made to apply a Proportional derivative–Proportional integral derivative (PD–PID) cascade controller in AGC. Controller gains are optimized simultaneously using more recent and powerful evolutionary computational technique Bat algorithm (BA). Performance of classical controllers such as Proportional Integral (PI) and Proportional Integral Derivative (PID) controller are investigated and compared with PD–PID cascade controller. Investigations reveal that PI, and PID provide more or less same response where as PD–PID cascade controller provides much better response than the later. Dynamic analysis has also been carried out for the controllers in presence of random load pattern, which reveals the superior performance of the PD–PID cascade controller. Sensitivity analysis reveals that the BA optimized PD–PID Cascade controller parameters obtained at nominal condition of loading, size and position of disturbance and system parameter (Inertia constant, H) are robust and need not be reset with wide changes in system loading, size, position of disturbance and system parameters. The system dynamic performances are studied with 1% step load perturbation in Area1.     

Ant Colony Optimized Fuzzy Control Solution for Frequency Oscillation Suppression

This paper presents a novel approach in addressing a critical power system issue, i.e., automatic generation control (AGC) in a smart grid scenario. It proposes the design and implementation of an optimized fuzzy logic controller (FLC) for AGC of interconnected power network. There are three different sources of power generation considered in the two-area interconnected model of power system network. First area is equipped with a single reheat thermal unit and a superconducting magnetic energy storage (SMES) unit, while another area has a hydro-unit with SMES. A multi-stage optimization strategy for the optimal solution of FLC for tie-line and frequency oscillation suppression is proposed in this paper using an ant colony optimization technique. The optimization of FLC is carried out in four different stages. The first stage is the optimization of range of input and output variables; the second stage is the optimization of membership function; the third and fourth stages are the optimization for rule base and rule weight optimization, respectively. The performance of the proposed controller is also compared with another control approaches to stabilize P_tie-line and Δf oscillations; these are the Ziegler–Nichols-tuned proportional–integral–derivative (PID) controller and genetic algorithm optimized PID controller. A comprehensive analysis of the traditional techniques and proposed techniques is presented on the basis of major dynamic performance parameters, i.e., settling time and peak overshoot.     

Comparison of performances of several FACTS devices using Cuckoo search algorithm optimized 2DOF controllers in multi-area AGC

This paper presents automatic generation control (AGC) of three unequal area thermal systems with single reheat turbine and appropriate generation rate constraints (GRC) in each area. A two degree of freedom (2DOF) controller called 2DOF-integral plus double derivative (2DOF-IDD) is proposed for the first time in AGC as secondary controller. Secondary controller gains and other parameters are optimized simultaneously using a more recent evolutionary computational technique called Cuckoo Search algorithm (CS). The system dynamic responses for various 2DOF controllers such as 2DOF-PI, 2DOF-PID, and 2DOF-DD are compared. Investigations reveal that responses with 2DOF-IDD are better than others. Performance of several FACTS devices such as Static synchronous series compensator (SSSC), Thyristor controlled series capacitor (TCSC), Thyristor controlled phase shifter (TCPS), and Interline power flow controller (IPFC) in presence of 2DOF-IDD controller are compared and found that the dynamic responses with IPFC are better than others. For the first time in AGC, a case study is performed with placement of IPFC and observed that IPFC present in all three areas of the system performs better. Sensitivity analysis reveals that the CS optimized 2DOF-IDD controller parameters obtained in presence of IPFC in all three areas at nominal condition of loading and size of step load perturbation (SLP) are robust and need not be reset with wide changes in system loading and SLP. Also, the comparison of convergence curve of various algorithms reveals that CS algorithm converges much faster than others.     

Automatic generation control of a multi-area system using ant lion optimizer algorithm based PID plus second order derivative controller

This article presents the automatic generation control of an unequal three area thermal system. Single stage reheat turbines and generation rate constraints of 3%/min are considered in each control area. Controllers such as Integral (I), Proportional – Integral (PI), Proportional – Integral – Derivative (PID), and Proportional – Integral – Derivative Plus Second Order Derivative (PID + DD) are treated as secondary controllers separately. A nature inspired optimization technique called Ant Lion Optimizer (ALO) algorithm is used for simultaneous optimization of the controller gains. Comparison of dynamic responses of frequencies and tie line powers corresponding to ALO optimized I, PI, PID and PID + DD controller reveal the better performance of PID + DD controller in terms of lesser settling time, peak overshoots as well as reduced oscillations. Robustness of the optimum gains of best controller obtained at nominal conditions is evaluated using sensitivity analysis. Analysis exposed that the optimum PID + DD controller gains obtained at nominal are robust and not necessary to reset again for changes in loading, parameter like inertia constant (H), size and position of disturbance. Furthermore, the performance of PID + DD controller is found better as compared to PID controller against random loading pattern condition.     

Application of capacitive energy storage for transient performance improvement of power system

In this paper, a comparative transient performance of two types of single machine power system is analyzed. The two types of system configurations are viz. (i) automatic voltage regulator (AVR) loop with single input conventional power system stabilizer (CPSS) combined with automatic generation control (AGC) loop, (ii) AVR with CPSS combined with capacitive energy storage (CES) unit-based AGC loop. For AGC loop both thermal unit and hydro unit are individually considered. The thermal unit is considered with either single or double stage reheat turbine, hydro unit is considered with mechanical or electric governor. Integral controller is provided in the AGC loop. It is shown that the CES-based integral controlled AGC loop along with CPSS assists in the best transient performance of the power system in all cases under different operating conditions. Parameters of the CPSS installed in AVR loop, gains of the integral controller in AGC loop are optimized with the help of a novel particle swarm optimization, developed by the authors, called as craziness-based particle swarm optimization (CRPSO). Transient performance is carried out with 1% step perturbation in either reference voltage or load torque.     

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

This 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.     

Load frequency control of a realistic power system with multi-source power generation

In this paper, load frequency control (LFC) of a realistic power system with multi-source power generation is presented. The single area power system includes dynamics of thermal with reheat turbine, hydro and gas power plants. Appropriate generation rate constraints (GRCs) are considered for the thermal and hydro plants. In practice, access to all the state variables of a system is not possible and also their measurement is costly and difficult. Usually only a reduced number of state variables or linear combinations thereof, are available. To resolve this difficulty, optimal output feedback controller which uses only the output state variables is proposed. The performances of the proposed controller are compared with the full state feedback controller. The action of this proposed controller provides satisfactory balance between frequency overshoot and transient oscillations with zero steady state error in the multi-source power system environment. The effect of regulation parameter (R) on the frequency deviation response is examined. The sensitivity analysis reveals that the proposed controller is quite robust and optimum controller gains once set for nominal condition need not to be changed for ±25% variations in the system parameters and operating load condition from their nominal values. To show the effectiveness of the proposed controller on the actual power system, the LFC of hydro power plants operational in KHOZESTAN (a province in southwest of Iran) has also been presented.     

Analysis of cascaded multilevel inverters for active harmonic filtering in distribution networks

This paper aims at the investigation of an active power filter (APF) comprised of a transformerless multilevel inverter (MLI) for power conditioning in three-phase three-wire distribution network. The inverter topologies used here are three, five, seven and nine-level. The system configuration mainly involves cascaded MLI structure of APF, generation of compensation filter currents based on instantaneous active and reactive current component (i_d–i_q) method and dc-link voltage regulation using a PI controller. Not many papers focus on the regulation of dc-link capacitor voltage. Here we have proposed the implementation of bacterial foraging optimization (BFO) to extract the gains of PI controller. The proposed work provides improved dc-link voltage regulation, quick prevail over current harmonics and reduction of overall source current THD. Adequate MATLAB/Simulink simulation results are presented for the different cascaded MLIs discussed above. Additionally, the performance has been validated in real-time using Opal-RT Lab simulator considering three different conditions of supply i.e., balanced sinusoidal, balanced non-sinusoidal and unbalanced sinusoidal.     

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.     

Effective oscillation damping of an interconnected multi-source power system with automatic generation control and TCSC

Stabilizing area frequency and tie-line power oscillations in interconnected power systems are main concerns that have received significant attention in automatic generation control (AGC) studies. This paper deals with modeling and simulation of thyristor controlled series capacitor (TCSC) based damping controller in coordination with AGC to damp the oscillations and thereby, improve the dynamic stability. The contribution of TCSC in tie-line power exchange is formulated analytically for small perturbation and a systematic method based on the Taylor series expansion is proposed for modeling of TCSC based damping controller. The integral gains of AGC and TCSC parameters are optimized simultaneously using an improved particle swarm optimization (IPSO) algorithm through minimizing integral of time multiplied squared error (ITSE) performance index. The performance of the proposed TCSC–AGC coordinated controller is compared with case of AGC alone. A two-area interconnected multi-source power system, including TCSC located in series with the tie-line, is studied considering nonlinearity effects of generation rate constraint (GRC) and governor dead band (GDB). Simulation results show that proposed controller shows greater performance in damping of the oscillations and enhancing the frequency stability. Furthermore, sensitivity analyses are carried out against system loading condition, parametric uncertainties, and different perturbation patterns to show the robustness of TCSC–AGC.     

SELECTION OF SAMPLING PERIOD FOR AUTOMATIC GENERATION CONTROL

ABSTRACT

The paper presents the analysis of automatic generation control (AGC) of a two-equal area reheat thermal system in the presence of generation rate constraints considering a discrete-continuous time mathematical model. The effect of variation of sampling period on optimum integral gain setting and system dynamic performance has been analyzed considering supplementary controllers based on conventional area control errors (ACEs) and new area control errors (ACENs). Investigations reveal that the optimum integral gain setting and system dynamic performance are hardly affected over a wide range of sampling period T for controllers based on conventional ACEs. Studies also reveal that the permissible sampling period is further enhanced with integral controllers based on new area control errors (ACENs).     

POWER GENERATION CONTROL USING DUAL-MODE CONTROL

Abstract

Dual-mode control is applied to the problem of power generation control. The proposed controller is simple in structure and easily implementable. The effect of changes in some important system parameters like self-regulation parameter, turbine time constant and generation rate constraints, on the dynamic performance of the system for reheat and non-reheat type steam turbines is also studied     

ENERGY FUNCTION ANALYSIS FOR POWER SYSTEM STABILITY

Abstract

This paper describes an application of fuzzy logic to design a fuzzy controller for the automatic generation control (AGC) problem in power system studies. A two area power system is considered. Frequency and tie-line power deviations for a step load increase in one area are plotted as a function of time, and are compared with available responses using the classical integral controller     

Genetically tuned fuzzy PID controller in two area reheat thermal power system

This paper demonstrates the design and analysis of automatic generation control using intelligent genetic algorithm tuned fuzzy based controller. A two area thermal power system simulated for four different scenarios considers a reheat steam turbine in each area with Generator rate constraints. The Integral Time Squared Error (ITSE) employed to get an objective function for the optimization of controller gains. The simulation results compared with the conventional Proportional Integral Derivative (PID) controller, Genetic Algorithm (GA) tuned PID controller and GA tuned Fuzzy PID controller. The proposed GA tuned Fuzzy based PID Controller can generate the best performance for peak overshoot, undershoot and settling time with step load disturbances. Robustness of the performance of the proposed controller provided with system parametric uncertainties.     

A hybrid firefly algorithm and pattern search technique for automatic generation control of multi area power systems

In this paper, a novel hybrid Firefly Algorithm and Pattern Search (hFA–PS) technique is proposed for Automatic Generation Control (AGC) of multi-area power systems with the consideration of Generation Rate Constraint (GRC). Initially a two area non-reheat thermal system with Proportional Integral Derivative (PID) controller is considered and the parameters of PID controllers are optimized by Firefly Algorithm (FA) employing an Integral Time multiply Absolute Error (ITAE) objective function. Pattern Search (PS) is then employed to fine tune the best solution provided by FA. The superiority of the proposed hFA–PS based PID controller has been demonstrated by comparing the results with some recently published modern heuristic optimization techniques such as Bacteria Foraging Optimization Algorithm (BFOA), Genetic Algorithm (GA) and conventional Ziegler Nichols (ZN) based PI/PID controllers for the same interconnected power system. Furthermore, sensitivity analysis is performed to show the robustness of the optimized controller parameters by varying the system parameters and operating load conditions from their nominal values. Finally, the proposed approach is extended to multi area multi source hydro thermal power system with/without considering the effect of physical constraints such as time delay, reheat turbine, GRC, and Governor Dead Band (GDB) nonlinearity. The controller parameters of each area are optimized under normal and varied conditions using proposed hFA–PS technique. It is observed that the proposed technique is able to handle nonlinearity and physical constraints in the system model.     

Optimal Automatic Generation Control with Hydro,Thermal, Gas,and Wind Power Plants in 2-Area Interconnected Power System

Abstract

This paper explores automatic generation control (AGC) of a more realistic 2-area multi-source power system comprising hydro, thermal, gas, and wind energy sources-based power plants in each control area. The wind power plants (WPPs) have been growing continuously worldwide due to their inherent feature of providing eco-friendly sustainable energy. But, operations of WPPs are associated with system stability problems due to lack of inertia. However, WPPs do not participate in the elimination of mismatch between generation and demand by AGC but disturbance can be injected by the WPPs due to the stochastic nature of wind energy. An optimal controller based on full state feedback control theory is designed to conduct the study. The system dynamic performance analysis is carried out for 1% step load disturbance in corresponding control areas. It is observed that the system dynamic graphs of deviation in area frequency and tie-line power are significantly improved with the implementation of optimal AGC controller compared to GA tuned classical controller. It has also been shown that the WPPs aid the increase in load disturbance when the input wind power reduces but it negates the effect of increase in load disturbance for increase in wind energy to the WPPs.     

Application of Hybrid Differential Evolution–Grey Wolf Optimization Algorithm for Automatic Generation Control of a Multi-Source Interconnected Power System Using Optimal Fuzzy–PID Controller

This paper deals with an optimal hybrid fuzzy-Proportional Integral Derivative (fuzzy-PID) controller optimized by hybrid differential evolution–Grey Wolf optimization algorithm for automatic generation control of an interconnected multi-source power system. Here a two area system is considered; each area is provided with three types of sources namely a thermal unit with reheat turbine, a hydro unit and a gas unit. The dynamic performance of the system is analyzed under two cases: with AC tie-line and with AC-DC tie-line. The efficiency and effectiveness of the proposed controller is substantiated equally in the two cases. The sturdiness of the system is proved by varying the values of the system parameters. The supremacy of the recommended work is additionally ascertained by comparison with the recently published results like differential evolution optimized PID Controller and hybrid Local Unimodal Sampling-Teaching Learning based Optimization (LUS-TLBO) optimized fuzzy-PID controller. The dynamic performance of the system is observed in terms of settling time, peak overshoot and peak undershoot. Finally the analysis is extended by applying the proposed control technique in two different models namely (i) A three area unequal thermal system considering proper generation rate constraints (GRC) and (ii) A three area hydro-thermal system with mechanical hydro governor. These test results reveal the adaptability of the proposed method in multi-area interconnected power system.     

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

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.     

Robust decentralized load frequency control of interconnected power system with Generation Rate Constraint using Type-2 fuzzy approach

The Load Frequency Control (LFC) problem has been a major subject in electrical power system design/operation. LFC is becoming more significant recently with increasing size, changing structure and complexity in interconnected power systems. In practice LFC systems use simple Proportional Integral (PI) controllers. As the PI control parameters are usually tuned, based on classical approaches. Moreover, they have fixed gains; hence are incapable of obtaining good dynamic performance for a wide range of operating conditions and various load changes, in multi-area power system. Literature shows that fuzzy logic controller, one of the most useful approaches, for utilizing expert knowledge, is adaptive in nature and is applied successfully for power system stabilization control. This paper proposes a Type-2 (T2) fuzzy approach for load frequency control of two-area interconnected reheat thermal power system with the consideration of Generation Rate Constraint (GRC). The performance of the Type-2 (T2) controller is compared with conventional controller and Type-1 (T1) fuzzy controller with regard to Generation Rate Constraint (GRC). The system parametric uncertainties are verified by changing parameters by 40% simultaneously from their typical values.