Three-area Interconnected Power System Research Articles

Decentralized Sampled-Data Control for Stochastic Disturbance in Interconnected Power Systems With PMSG-Based Wind Turbines.

The presented work is concerned with the stability performance of frequency response for interconnected power systems (IPSs) with permanent magnet synchronous generator (PMSG)-based wind turbines (WTs) via a decentralized control scheme against external and stochastic disturbances. To do this, initially, the state-space model is derived when a PMSG is penetration into IPSs. Differing from existing works, IPSs with PMSG-based WTs, including the stochastic disturbance, are modeled as a stochastic state-space model. Then, decentralized sampled-data load frequency control is designed to regulate the frequency response of the proposed model against the deterministic and stochastic noises. By constructing bilateral looped Lyapunov functional and using Itôs formula, stochastic sufficient conditions are derived, which ensure that the closed-loop form of the proposed model is asymptotically stable in the mean square with H∞ performance index γ . Finally, three-area IPSs with PMSG-based WTs are validated with derived sufficient conditions. The simulation results confirmed the better-stability performance of frequency response for the proposed stochastic IPSs with PMSG-based WTs.

Data-Driven Load Frequency Control Based on Multi-Agent Reinforcement Learning With Attention Mechanism

With the massive penetration of renewable energy, traditional reinforcement learning algorithms suffer from slow convergence and area control error (ACE) in interconnected power systems. This paper proposes data-driven load frequency control (LFC) based on multi-agent reinforcement learning with attention mechanism in interconnected power systems. It can be divided into two phases; in the centralized training, the agents are trained by an experience replay mechanism; in the decentralized execution, the trained agent automatically regulates the generation power to control the load frequency by real-time access to the grid data in the area. The agent can selectively focus on specific information in the environment by introducing a criticism network with an attention mechanism. The attention mechanism can reduce the training time for reinforcement learning while improving control performance under disturbance. A novel reward function based on a cooperation mechanism is used to score the performance of agent, which can guide the reinforcement learning algorithm to reduce the ACE of each area simultaneously. The proposed method is validated by the IEEE three-area interconnected power system, and it is concluded that the method can reduce the ACE caused by load and renewable power disturbances, and greatly reduce the training time of the algorithm.

Distributed Observer-Based Event-Triggered Load Frequency Control of Multiarea Power Systems Under Cyber Attacks

Information and communication technology tremendously facilitates the operation efficiency and economy of modern power systems in recent years. However, risks such as bandwidth constraints and malicious attacks threaten the secure load frequency control (LFC) of power systems. To mitigate such risks, this paper proposes distributed observer-based event-triggered LFC schemes for multi-area power systems under cyber attacks. Considering the practical situation that only local system output information may be available, distributed observer-based LFC schemes are designed. Meanwhile, to reduce the communication burden, an event-triggered mechanism is adopted to design control laws, where both static and dynamic event-triggered approaches are taken and the dynamic one is proved to be more economical in terms of control cost. Verifiable sufficient conditions are established to guarantee the stability of the closed-loop system in the presence of cyber attacks and the controller gains are explicitly derived. Finally, validation studies on a three-area interconnected power system are carried out to demonstrate the proposed control schemes. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Load frequency is a crucial index for evaluating the quality of electric energy and thus LFC has brought considerable attention in the area of power systems control. Although many achievements have been made on the LFC of multi-area power systems, the risks such as bandwidth constraints and malicious attacks affect the normal operation of LFC due to the interconnection between different power systems. To deal with these risks, this paper focuses on designing event-triggered LFC to guarantee the stability of the frequency deviation while reducing the communication burden and mitigating cyber attacks. More importantly, the proposed event-triggered LFC is designed based on an observer and can be implemented in a distributed manner, which is relatively practical in real applications. The results presented in this paper aim to provide a helpful reference for stable and secure LFC design of multi-area power systems, such that the corresponding application research can be promoted.

Reliable Event-Triggered Load Frequency Control of Uncertain Multiarea Power Systems With Actuator Failures

Load frequency control (LFC) is crucial for the economic operation and safety of power systems. Therefore this paper addresses the LFC problem for uncertain multi-area power systems with actuator failures. Specifically, actuator failures, uncertainties and communication bandwidth constraints appearing in multi-area power systems are taken into account simultaneously, and novel reliable event-triggered LFC schemes are proposed to cope with these troubles. The proposed schemes can ensure the asymptotical stability of the closed-loop system when only matched uncertainty exists. For the case of coexisting matched and mismatched uncertainties, the state trajectories of the closed-loop system can be controlled within a bounded set, where the size of the bounded set is only related to the mismatched uncertainty. To illustrate the theoretical results, a numerical example of three-area interconnected power system is presented. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Load frequency directly affects the quality of electric energy and is one of the main observation states of power systems, hence LFC has been widely investigated in the literature. For multi-area power systems, the system model to be controlled may be subjected to multiple unfavorable factors in practical situations, such as limited bandwidths, model uncertainties and actuator failures. To cope with these unfavorable factors, this paper is devoted to developing a unified control framework to guarantee the stability of the frequency deviation based on the event-triggered mechanism. Considering both matched and unmatched system uncertainties may exist as well as the bound of system uncertainties can be unknown, event-triggered control schemes including static event-triggered LFC and adaptive event-triggered LFC are accordingly designed to deal with aforementioned situations such that the closed-loop system is asymptotically or boundedly stable. The research outcome of this paper provides simple but effective LFC approaches that can be used to maintain the reliable and stable operation of multi-area power systems.

Discrete-time prediction based event-triggered controller design: An application to networked multi-area power system with time delays

This work proposes a solution for power system stability by utilizing prediction-based event-triggered control (ETC) in the discrete-time domain. The proposed control method can handle a large sampling period, and the event-triggered mechanism (ETM) is applied in both controller and actuator loops to reduce the network’s computational and communication burden. Input and output (I/O) quantizers are used to avoid the quantization error that arises due to sampling and are also included in the stability analysis. The proposed control strategy is evaluated under various load scenarios using three-area interconnected power systems. The results demonstrate that the proposed approach saves 25.5%, 22%, and 23.5% of channel bandwidth in each area, as compared to the conventional time-triggered control approach. A comparative study shows that the proposed work outperforms recently reported works in terms of better event triggering number, average inter-event time, and performance indices. The effectiveness of the proposed control schemes is further validated by considering uncertainty in system parameters and typical power system nonlinearities. The study also illustrates the integration of renewable energy resources (RERs) and electric vehicles (EVs). The closed-loop system stability is proved theoretically using uniform ultimate boundedness and validated through simulations in MATLAB R2018a.

Load Frequency Control and Automatic Voltage Regulation in a Multi-Area Interconnected Power System Using Nature-Inspired Computation-Based Control Methodology

The stability control of nominal frequency and terminal voltage in an interconnected power system (IPS) is always a challenging task for researchers. The load variation or any disturbance affects the active and reactive power demands, which badly influence the normal working of IPS. In order to maintain frequency and terminal voltage at rated values, controllers are installed at generating stations to keep these parameters within the prescribed limits by varying the active and reactive power demands. This is accomplished by load frequency control (LFC) and automatic voltage regulator (AVR) loops, which are coupled to each other. Due to the complexity of the combined AVR-LFC model, the simultaneous control of frequency and terminal voltage in an IPS requires an intelligent control strategy. The performance of IPS solely depends upon the working of the controllers. This work presents the exploration of control methodology based on a proportional integral–proportional derivative (PI-PD) controller with combined LFC-AVR in a multi-area IPS. The PI-PD controller was tuned with recently developed nature-inspired computation algorithms including the Archimedes optimization algorithm (AOA), learner performance-based behavior optimization (LPBO), and modified particle swarm optimization (MPSO). In the earlier part of this work, the proposed methodology was applied to a two-area IPS, and the output responses of LPBO-PI-PD, AOA-PI-PD, and MPSO-PI-PD control schemes were compared with an existing nonlinear threshold-accepting algorithm-based PID (NLTA-PID) controller. After achieving satisfactory results in the two-area IPS, the proposed scheme was examined in a three-area IPS with combined AVR and LFC. Finally, the reliability and efficacy of the proposed methodology was investigated on a three-area IPS with LFC-AVR with variations in the system parameters over a range of  ± 50%. The simulation results and a comprehensive comparison between the controllers clearly demonstrates that the proposed control schemes including LPBO-PI-PD, AOA-PI-PD, and MPSO-PI-PD are very reliable, and they can effectively stabilize the frequency and terminal voltage in a multi-area IPS with combined LFC and AVR.

Load-Frequency Control of Three-Area Interconnected Power Systems with Renewable Energy Sources Using Novel PSO~PID-Like Fuzzy Logic Controllers

Modern era power systems may include not only traditional primary energy sources like hydro or thermal energy, but also a variety of Renewable Energy (RE) sources such as solar and/or wind power. This leads to the complexity of the electrical networks related to their design and construction as well as system stability and control issues. Considered to be one of the most crucial control issues, Load Frequency Control (LFC), must be continuously improved in order to ensure the control goals. For an interconnected power system, the control purposes are to maintain the net frequency at nominal value, e.g. 50 or 60Hz as well as to ensure that tie-line power flows are stable at scheduled values. This work proposes a novel LFC strategy applying Particle Swarm Optimization (PSO) ~ PID – like fuzzy logic–based controllers. PSO is one of the most effective optimization techniques. It is used to optimally determine four scaling factors for each LFC proposed in this study. A three-area power network consisting of a hydraulic station, a non-reheat plant, and a reheat unit along with RE sources such as wind and solar power are taken into consideration. The control performance of the proposed control strategy is compared to those of existing controllers, i.e. Genetic Algorithm (GA), Bacteria Foraging Optimization Algorithm (BFOA), Fractional Order-PID (FPID), and fuzzy logic-based PI controllers for the same interconnected power grid model with various case studies of load changes along with nonlinearities and different RE source conditions. Simulation results implemented in MATLAB/Simulink demonstrate the feasibility and applicability of the proposed control strategy.

Decentralized Detection and Mitigation of Multiple False Data Injection Attacks in Multiarea Power Systems

This article presents an observer-based decentralized detection and mitigation (ODDM) scheme for the interconnected power system subject to multiarea multichannel false data injection attacks (FDIAs). In the ODDM scheme, the FDIAs on the measurement channel and control channel of power system are modeled as unknown input and unknown output, respectively, which are described by extended states of the system. A state and attack observer (SAO) is developed using local measurements for each control area of power system, so as to simultaneously estimate the system states and attack signals in the presence of model uncertainties. During the occurrence of malicious attacks, the attack estimations provided by observer can automatically detect the FDIA on each control area. Besides, the load frequency control system is reconfigured by attack compensation based on the attack estimations of observer, thus achieving the mitigation of multiarea multichannel FDIAs. Case studies are undertaken on a three-area interconnected power system model under the conditions of single attack, multiple attack, and parameter variations to validate the performance of the proposed ODDM scheme.

Neural network aided fractional-order sliding mode controller for frequency regulation of nonlinear power systems

In this work, the performance of a fractional-order integral sliding mode controller (FOISMC) has been assessed for frequency regulation of interconnected power systems considering inherent nonlinearities, such as generation rate constraint and governor dead-band. The performance of the proposed controller has been measured on two- and three-area interconnected power systems integrated with a wind turbine generator. A Chebyshev neural network (NN)-based estimator is designed to estimate the lumped system uncertainties, including nonlinearities, unknown external disturbances, and parameter uncertainty. Afterwards, an improved FOISMC is developed, augmenting the estimated output of the NN-based estimator to cope with system disturbances effectively. To corroborate the potential benefits, the results obtained with NN-aided FOISMC (NN-FOISMC) are compared with the outputs of FOISMC and results reported in the literature. The simulation study confirms the superiority of NN-FOISMC over its other counterparts in terms of damping of power-frequency oscillations, weaker chattering, and a high degree of robustness.

Maiden Application of Fuzzy-2DOFTID Controller in Unified Voltage-Frequency Control of Power System

This article presents an amalgamated pattern of automatic load frequency control (ALFC) and automatic voltage regulator (AVR) system in a three-area interconnected power system using the Fuzzy two-degree-of-freedom tilt-integral-derivative controller (F2DOFTID). The multi-area system includes single-stage reheat thermal plants and Solar Thermal Power Plant (STPP) in Area-1 and Heavy-Duty Gas Turbines (HDGT) in Area-2 and Area-3. An incipient attempt is made to incorporate the HDGT plant in amalgamated control of the power system. Relevant generation rate constraints (GRC) and Governor Dead Band (GDB) are rendered for thermal plants. In both ALFC and AVR systems of all areas, a first attempt is made to implement an F2DOFTID controller to alleviate the frequency and voltage deviations. In this investigation, an algorithm named Harris Hawks Optimization (HHO) is efficaciously used to accomplish optimal controller parameters. Concerning all time-domain behaviors, F2DOFTID controller performance is superior relative to the TID and 2DOFTID controller. The AVR effect proclaims a substantial improvement in system dynamics. In this amalgamated scenario, the aftermath of the high voltage direct current (HVDC) tie-line and the usage of energy storage devices such as ultra-capacitors (UC) are found superlative in the amelioration of system performance. Similarly, by modifying the generator parameters and synchronizing coefficients, the robustness of the proposed controller is measured, which signifies that obtained controller parameters during nominal conditions are resilient enough and not to be altered. Eventually, the system is also studied in OPAL-RT OP 4510 RT Lab hardware set-up for real-time analysis.

Extended state observer based load frequency controller for three area interconnected power system

In this paper, we develop a new extended state variable observer based LFC scheme for three-area interconnected power systems. The extended state observerbased load frequency controllers are developed which utilize disturbance estimation techniques. The propose control approach assures that the fluctuating things of the load frequencies reaches to a safer range and the load frequencies can also be made at a very minimal not to have an effect on power quality and power flow in multi-area interconnected power system. The results of the simulations using MATLAB/SIMULINK done did not only address that the proposed newly control method works effectively but also change powerfully the parameter variations of the interconnected areas of the power system. Especially, it works very well to limit disturbances impact on interconnected areas in the system. Therefore, the performance of interconnected power system under different multi-conditions is simulated with the new control method to demonstrate the feasibility of the system.

Non-Fragile Approach for Frequency Regulation in Power System With Event-Triggered Control and Communication Delays

This article proposes a non-fragile control model approach for the design of an event-triggered control (ETC) for frequency and tie-line power regulation in a networked power system with communication delays. The proposed non-fragile control approach can tolerate controller parameter variations without any degradation in the system performance. The event condition is designed based on the relationship between the ETC and the non-fragile system. The effectiveness of the proposed design is validated with three-area interconnected power systems under load disturbances. The superiority of the proposed work is shown by comparative analysis with recently reported works. Furthermore, system robustness is validated with random step load disturbance, matched uncertainty, power system nonlinearities, communication link noise, integration of renewable energy resources, and with the IEEE 39 bus system. The closed-loop system stability is theoretically proved using the Lyapunov candidate function and verified by simulations.

Improved model predictive load frequency control of interconnected power system with synchronized automatic generation control loops

BackgroundAutomatic generation control (AGC) of multi-area interconnected power system (IPS) is often designed with negligible cross-coupling between the load frequency control (LFC) and automatic voltage regulation (AVR) loops. This is because the AVR loop is considerably faster than that of LFC. However, with the introduction of slow optimal control action on the AVR, positive damping effect can be achieved on the LFC loop thereby improving the frequency control. In this paper, LFC synchronized with AVR in three-area IPS is proposed. Model predictive controller (MPC) configured in a dense distributed pattern, due to its online set-point tacking is used as the supplementary controller. The dynamics of the IPS subjected to multi-area step and random load disturbances are studied. The efficacy of the developed scheme is ascertained by simulating the disturbed system in MATLAB/Simulink.ResultsBased on the comparative analysis on the system responses, it is established that by cross-coupling the LFC loop with AVR, reductions of 66.45% and 59.09% in the frequency and tie-line power maximum deviations respectively are observed, while the respective settling times are found to be reduced by 29.68% and 22.77% when compared with the uncoordinated control scheme. In addition, the standard deviation and variance of the integral time absolute error of the system’s responses have reduced by 23.21% and 20.83% respectively compared to those obtained in a similar study.ConclusionsThe reduction in the maximum deviations and settling times in the system states indicates that introducing the voltage control via AVR loop has improved the frequency control significantly. While the lower standard deviation and variance of the integral time absolute error signify improvement in the robustness of the developed algorithm. However, this improvement is at the detriment of the controller size and computational complexity. In the uncoordinated control scheme, the control vector is one-dimensional, while in the coordinated scheme, the control vector is two-dimensional for each CA.

H∞ Control for Network T-S Fuzzy Systems under Time Varying Delay for Multi-area Power Systems

This paper investigates the problem of Load Frequency Control (LFC) and proposes a new eventtriggered scheme for T-S Fuzzy control (TSFC) with the time-varying delay in multi-area interconnected power systems. First, we establish the mathematical model of the three-area interconnected power system. Second, a delay fuzzy-based controller is constructed by considering the same premises as in controller, and then an event-triggered scheme is considered to mitigate the effect of communication burden. Another derives of this paper are implemented to examine the prescribed H∞ or energy-to-energy performance index of the closed-loop power system. Furthermore, in this regard, by taking into account a new version of fuzzy Lyapunov-Krasovskii functional (LKF) in conjunction with free weighting matrices, containing mode-dependent non-integral term such that the resulting system is stable with the desired performance. Then, the desired Fuzzy controller is presented in the account of LMI. Finally, we validate the feasibility and the effectiveness of our results with a Three-area power systems example.

Active disturbance rejection controller for multi-area interconnected power system based on reinforcement learning

In this paper, a method of Active Disturbance Rejection Controller (ADRC) is proposed based on Q-learning of Reinforcement Learning (RL) for multi-area interconnected power system. Excessive changes in load can cause instability to the system. Therefore, the ADRC controller is used to keep the load within rated range for its strong anti-interference performance and Q-learning algorithm to select the adaptive parameters of the controller. Finally, through simulation experiments on traditional and deregulated three-area interconnected power system respectively, the effectiveness of the proposed method is proved and the results show that reinforcement learning can indeed be used to solve the problem of controller parameter adjustment.

Analysis of antlion optimizer-based ABT for automatic generation control of an interconnected power system

In this paper, a novel ant lion optimization algorithm is proposed for the recent availability-based tariff (ABT) pricing scheme for the automatic generation control of a three-area interconnected power system (IPS). The innovative ant lion optimizer (ALO) process is performed in conjunction with ABT. The real frequency and load variation are realistic to the input of ALO and minimize the objective function area control error, generation costs and marginal cost of the system. Based on the output of the ALO, the ABT is resolute and assumed as the input of the proposed controller. The dynamic performance of the three-area IPS values including hydrothermal, wind turbine and photovoltaic power systems are evaluated on the basis of limits such as frequency deviation, generation power and tie-line power. Based on these limits, the frequency deviation is controlled and the parameters of the multi-resolution PID (MRPID) controller are regulated. The proposed MRPID controller is modified with the proposed ABT-based ALO to increase the optimal resolution. A three-area IPS is modeled under numerous loads to improve the efficiency of the proposed algorithm. The performance of the this method is demonstrated and compared with existing methods including particle swarm optimization and gravitational search algorithm.

Active disturbance rejection based load frequency control and voltage regulation in power systems

An active disturbance rejection controller (ADRC) is developed for load frequency control (LFC) and voltage regulation respectively in a power system. For LFC, the ADRC is constructed on a three-area interconnected power system. The control goal is to maintain the frequency at nominal value (60Hz in North America) and keep tie-line power flow at scheduled value. For voltage regulation, the ADRC is applied to a static var compensator (SVC) as a supplementary controller. It is utilized to maintain the voltages at nearby buses within the ANSI C84.1 limits (or ±5% tolerance). Particularly, an alternative ADRC with smaller controller gains than classic ADRC is originally designed on the SVC system. From power generation and transmission to its distribution, both voltage and frequency regulating systems are subject to large and small disturbances caused by sudden load changes, transmission faults, and equipment loss/malfunction etc. The simulation results and theoretical analyses demonstrate the effectiveness of the ADRCs in compensating the disturbances and achieving the control goals.

Population extremal optimization-based extended distributed model predictive load frequency control of multi-area interconnected power systems

How to design a set of optimal distributed load frequency controllers for a multi-area interconnected power system is an important but still challenging issue in the field of modern electric power systems. This paper presents an adaptive population extremal optimization-based extended distributed model predictive load frequency control method called PEO-EDMPC for a multi-area interconnected power system. The key idea behind the proposed method is formulating the dynamic load frequency control issue of each area power system as an extended distributed discrete-time state-space model based on an extended state vector, obtaining a distributed dynamic extended predictive model, and rolling optimization of real-time control output signal by adopting an adaptive population extremal optimization algorithm, where the fitness is evaluated by the weighted sum of square predicted errors and square future control values. The superiority of the proposed PEO-EDMPC method to a traditional distributed model predictive control method, a population extremal optimization-based distributed proportional-integral control algorithm and a traditional distributed integral control method is demonstrated by the simulation studies on two-area and three-area interconnected power systems in cases of normal, perturbed system parameters and dynamical load disturbances.

Constrained population extremal optimization-based robust load frequency control of multi-area interconnected power system

This paper proposes a robust proportional-integral (PI) controller with its parameters designed by constrained population extremal optimization for load frequency control problem of multi-area interconnected. During the process of optimization, the robust performance index is used as fitness function, where linear matrix inequalities technique is employed to describe the H∞ constraint, and the taking error performance requirement such as integral time absolute error is incorporated as another constraint. Three different two-area interconnected power systems are used as test systems to demonstrate the effectiveness of the proposed controller by comparing with other PI control methods and one optimized model predictive control. In addition, in order to investigate the performance of proposed controller for the LFC problem of large scale system, a three-area interconnected power system is used as another test system. The comprehensive experimental results fully demonstrate that the proposed control scheme in this paper performs better than other control strategies on the most considered scenarios under the conditions of load disturbance and parameters uncertainties in terms of system response and control performance indices.

Multi-Area Hydrothermal Interconnected Load Frequency Control with Double-Fed Induction-Generator-Based Wind Turbine via Improved Harmony Algorithm

The main purpose of this research is to allow doubly fed induction generator (DFIG) to participate effectively in interconnected power systems load frequency control via improved harmony algorithm (IHA). In order to tune the parameters of the PI controllers without considering the complexity associated with the modeling of the power system, the corresponding optimization problem is formulated in terms of an objective function, which represents the norm of the closed-loop area control error signal. A three-area interconnected power system subjected to major disturbances is investigated to verify the effectiveness of the developed algorithm of DFIG wind turbine participation in load frequency regulation. Time domain simulation results are presented to prove the improved performance of the developed IHA-based controller compared with genetic algorithm, simulated annealing, and a conventional integral controller. The results show that the developed IHA controller has better behavior over other algorithms in terms of settling times and other indices.