Decentralized Resilient H_∞Load Frequency Control for Cyber-Physical Power Systems Under DoS Attacks

This paper designs a decentralized resilient H_(∞)load frequency control(LFC)scheme for multi-area cyber-physical power systems(CPPSs).Under the network-based control framework,the sampled measurements are transmitted through the communication networks,which may be attacked by energylimited denial-of-service(DoS)attacks with a characterization of the maximum count of continuous data losses(resilience index).Each area is controlled in a decentralized mode,and the impacts on one area from other areas via their interconnections are regarded as the additional load disturbance of this area.Then,the closed-loop LFC system of each area under DoS attacks is modeled as an aperiodic sampled-data control system with external disturbances.Under this modeling,a decentralized resilient H_(∞)scheme is presented to design the state-feedback controllers with guaranteed H∞performance and resilience index based on a novel transmission interval-dependent loop functional method.When given the controllers,the proposed scheme can obtain a less conservative H_(∞)performance and resilience index that the LFC system can tolerate.The effectiveness of the proposed LFC scheme is evaluated on a one-area CPPS and two three-area CPPSs under DoS attacks.

Load Frequency Control of Multi-interconnected Renewable Energy Plants Using Multi-Verse Optimizer

A reliable approach based on a multi-verse optimization algorithm(MVO)for designing load frequency control incorporated in multi-interconnected power system comprising wind power and photovoltaic(PV)plants is presented in this paper.It has been applied for optimizing the control parameters of the load frequency controller(LFC)of the multi-source power system(MSPS).The MSPS includes thermal,gas,and hydro power plants for energy generation.Moreover,the MSPS is integrated with renewable energy sources(RES).The MVO algorithm is applied to acquire the ideal parameters of the controller for controlling a single area and a multi-area MSPS integrated with RES.HVDC link is utilized in shunt with AC multi-areas interconnection tie line.The proposed scheme has achieved robust performance against the disturbance in loading conditions,variation of system parameters,and size of step load perturbation(SLP).Meanwhile,the simulation outcomes showed a good dynamic performance of the proposed controller.

Load Frequency Control of Small Hydropower Plants Using One-Input Fuzzy PI Controller with Linear and Non-Linear Plant Model

This study presents an intelligent approach for load frequency control (LFC) of small hydropower plants (SHPs). The approach which is based on fuzzy logic (FL), takes into account the non-linearity of SHPs—something which is not possible using traditional controllers. Most intelligent methods use two- input fuzzy controllers, but because such controllers are expensive, there is economic interest in the relatively cheaper single-input controllers. A non- linear control model based on one-input fuzzy logic PI (FLPI) controller was developed and applied to control the non-linear SHP. Using MATLAB/Si- mulink SimScape, the SHP was simulated with linear and non-linear plant models. The performance of the FLPI controller was investigated and compared with that of the conventional PI/PID controller. Results show that the settling time for the FLPI controller is about 8 times shorter;while the overshoot is about 15 times smaller compared to the conventional PI/PID controller. Therefore, the FLPI controller performs better than the conventional PI/PID controller not only in meeting the LFC control objective but also in ensuring increased dynamic stability of SHPs.

Coefficient Diagram Method Based Load Frequency Control for a Modern Power System

increasing penetration of renewable energy sources with a wide range of operating conditions causing power system uncertainties, conventional controllers are incapable of providing proper performance to keep the system stable. However, controllable or dispatchable loads such as electric vehicles （EVs） and heat pumps （HPs） can be utilized for supplementary frequency control. This paper shows the ability of plug-in hybrid EVs, HPs, and batteries （BTs） to contribute in the frequency control of an isolated power system. Moreover, we propose a new online intelligent approach by using a coefficient diagram method （CDM） to enhance the system performance and robustness against uncertainties. The performance of the proposed intelligent CDM control has been compared with the proportional-integral （PI） controller and the superiority of the proposed scheme has been verified in Matiab/Simulink programs.

Integral Performance Criteria Based Analysis of Load Frequency Control in Bilateral Based Market

Performance index based analysis is made to examine and highlight the effective application of Particle Swarm Optimization (PSO) to optimize the Proportional Integral gains for Load Frequency Control (LFC) in a restructured power system that operates under Bilateral based policy scheme. Various Integral Performance Criteria measures are taken as fitness function in PSO and are compared using overshoot, settling time and frequency and tie-line power deviation following a step load perturbation (SLP). The motivation for using different fitness technique in PSO is to show the behavior of the controller for a wide range of system parameters and load changes. Error based analysis with parametric uncertainties and load changes are tested on a two-area restructured power system. The results of the proposed PSO based controller show the better performance compared to the classical Ziegler-Nichols (Z-N) tuned PI and Fuzzy Rule based PI controller.

Load Frequency Control of a Two Area-Power System with Non-reheat Turbines by SMC Approach

Load frequency is an important issue in power system operation and control. In this paper, load frequency control for suppression frequency deviation in an interconnected power system with nonlinearities using SMC （sliding mode control） is studied. The governor dead band and GRC （generation rate constraint） is considered in this article. Digit simulations for both two areas and three areas power system with non-reheat turbines are provided to validate the effectiveness of the proposed scheme. The results show that, the robustness of the control method under parameters variation and different load disturbances with the SMC technique.

Ant Lion Optimization Approach for Load Frequency Control of Multi-Area Interconnected Power Systems

This work proposes a novel nature-inspired algorithm called Ant Lion Optimizer (ALO). The ALO algorithm mimics the search mechanism of antlions in nature. A time domain based objective function is established to tune the parameters of the PI controller based LFC, which is solved by the proposed ALO algorithm to reach the most convenient solutions. A three-area interconnected power system is investigated as a test system under various loading conditions to confirm the effectiveness of the suggested algorithm. Simulation results are given to show the enhanced performance of the developed ALO algorithm based controllers in comparison with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Bat Algorithm (BAT) and conventional PI controller. These results represent that the proposed BAT algorithm tuned PI controller offers better performance over other soft computing algorithms in conditions of settling times and several performance indices.

A Novel Flower Pollination Algorithm to Solve Load Frequency Control for a Hydro-Thermal Deregulated Power System

Load frequency control plays a vital role in power system operation and control. LFC regulates the frequency of larger interconnected power systems and keeps the net interchange of power between the pool members at predetermined values for the corresponding changes in load demand. In this paper, the two-area, hydrothermal deregulated power system is considered with Redox Flow Batteries (RFB) in both the areas. RFB is an energy storage device, which converts electrical energy into chemical energy, that is used to meet the sudden requirement of real power load and hence very effective in reducing the peak shoots. With conventional proportional-integral (PI) controller, it is difficult to get the optimum solution. Hence, intelligent techniques are used to tune the PI controller of the LFC to improve the dynamic response. In the family of intelligent techniques, a recent nature inspired algorithm called the Flower Pollination Algorithm (FPA) gives the global minima solution. The optimal value of the controller is determined by minimizing the ISE. The results show that the proposed FPA tuned PI controller improves the dynamic response of the deregulated system faster than the PI controller for different cases. The simulation is implemented in MATLAB environment.

Detection and Defense Method Against False Data Injection Attacks for Distributed Load Frequency Control System in Microgrid

In the realm of microgrid(MG),the distributed load frequency control(LFC)system has proven to be highly susceptible to the negative effects of false data injection attacks(FDIAs).Considering the significant responsibility of the distributed LFC system for maintaining frequency stability within the MG,this paper proposes a detection and defense method against unobservable FDIAs in the distributed LFC system.Firstly,the method integrates a bi-directional long short-term memory(Bi LSTM)neural network and an improved whale optimization algorithm(IWOA)into the LFC controller to detect and counteract FDIAs.Secondly,to enable the Bi LSTM neural network to proficiently detect multiple types of FDIAs with utmost precision,the model employs a historical MG dataset comprising the frequency and power variances.Finally,the IWOA is utilized to optimize the proportional-integral-derivative(PID)controller parameters to counteract the negative impacts of FDIAs.The proposed detection and defense method is validated by building the distributed LFC system in Simulink.

Heuristic-Based Optimal Load Frequency Control with Offsite Backup Controllers in Interconnected Microgrids

The primary factor contributing to frequency instability in microgrids is the inherent intermittency of renewable energy sources.This paper introduces novel dual-backup controllers utilizing advanced fractional order proportional integral derivative(FOPID)controllers to enhance frequency and tie-line power stability in microgrids amid increasing renewable energy integration.To improve load frequency control,the proposed controllers are applied to a two-area interconnectedmicrogrid system incorporating diverse energy sources,such as wind turbines,photovoltaic cells,diesel generators,and various storage technologies.A novelmeta-heuristic algorithm is adopted to select the optimal parameters of the proposed controllers.The efficacy of the advanced FOPID controllers is demonstrated through comparative analyses against traditional proportional integral derivative(PID)and FOPID controllers,showcasing superior performance inmanaging systemfluctuations.The optimization algorithm is also evaluated against other artificial intelligent methods for parameter optimization,affirming the proposed solution’s efficiency.The robustness of the intelligent controllers against system uncertainties is further validated under extensive power disturbances,proving their capability to maintain grid stability.The dual-controller configuration ensures redundancy,allowing them to operate as mutual backups,enhancing system reliability.This research underlines the importance of sophisticated control strategies for future-proofing microgrid operations against the backdrop of evolving energy landscapes.

Robust Load Frequency Control for Isolated Microgrids Based on Double-loop Compensation

Frequency is an important indicator for the oper-ation of microgrids.However,the randomness and uncertainty of renewable energy and load variability may lead to frequency undulation.So,a robust load frequency control(LFC)is pro-posed for isolated wind-diesel microgrids considering time delay and parameter uncertainty.The control strategy can suppress frequency fuctuation and optimize frequency dynamic response.First,the double compensation loop,including feedforward control and integral sliding mode control(SMC),is devised to provide anti-disturbance compensation for the diesel generator system and ameliorate the frequency stability of independent microgrids.Secondly,a dynamic fuzzy controller,composed of wind speed and load demand,is designed to provide real-time response reference power for doubly fed induction generator systems(DFIGs),which can promote the effective participation of a wind turbine system for frequency regulation.Then,the proportional differential(PD)parameters of a dynamic fuzzy controller and the frequency adjustment compensation of DFIGs can be obtained by using a particle swarm optimization(PSO)algorithm.Thirdly,load demand is an important index of the robust dynamic load frequency control method;the radial basis function(RBF)neural network observer(NNO)based on the LFC model is presented to obtain more accurate load deviations and improve the control precision of LFC.The performance of the proposed LFC method is tested under different operation cases.Index Terms-Load frequency control,microgrid,neural network observer,sliding mode,time delay and parameter uncertainty.

Age-of-information-aware PI controller for load frequency control

Open communication system in modern power systems brings concern about information staleness which may cause power system frequency instability.The information staleness is often characterized by communication delay.However,communication delay is a packet-centered metric and cannot reflect the requirement of information freshness for load frequency control(LFC).This paper introduces the age of information(AoI),which is more compre-hensive and informative than the conventional communication delay modeling method.An LFC controller and com-munication are integrated into the design for LFC performance improvement.An AoI-aware LFC model is formulated first,and considering each allowable update period of the smart sensor,different AoI-aware PI controllers are then designed according to the exponential decay rate.The right AoI-aware controller and update period are selected according to the degree of frequency fluctuation of the power system.Case studies are carried out on one-area and two-area power systems.The results show the superior performance of the AoI-aware controllers in comparison to the delay-dependent controllers.

Adaptive H_(∞) event-triggered load frequency control in islanded microgirds with limited spinning reserve constraints

Using an islanded microgrid(MG)with large-scale integration of renewable energy is the most popular way of solving the reliable power supply problem for remote areas and critical electrical users.However,compared with traditional power systems,the limited spinning reserves and network communication bandwidth may cause weak frequency stability in the presence of stochastic renewable active outputs and load demand fluctuations.In this paper,an adap-tive event-triggered control(ETC)strategy for a load frequency control(LFC)system in an islanded MG is proposed.First,a bounded adaptive event-triggered communication scheme is designed.This not only saves on network resources,but also ensures that the control center has a sensitive monitoring ability for the MG operating status when the frequency deviations have been effectively damped.Secondly,by fully considering the spinning reserve con-straints and uncertain communication delays,the LFC system is described as a nonlinear model with saturation terms.Design criteria for ETC parameters are strictly deduced based on Lyapunov stability theory.Finally,an ETC parameter optimization algorithm based on random direction search is developed to reconcile the bandwidth occupancy and control performance.The effectiveness of the proposed method is verified in an MG test system.

Robust Stabilization of Load Frequency Control System Under Networked Environment

The deregulation of the electricity market made the open communication infrastructure an exigent need for future power system. In this scenario dedicated communication links are replaced by shared networks. These shared networks are characterized by random time delay and data loss. The random time delay and data loss may lead to system instability if they are not considered during the controller design stage. Load frequency control systems used to rely on dedicated communication links. To meet future power system challenges these dedicated networks are replaced by open communication links which makes the system stochastic. In this paper, the stochastic stabilization of load frequency control system under networked environment is investigated. The shared network is represented by three states which are governed by Markov chains. A controller synthesis method based on the stochastic stability criteria is presented in the paper. A one-area load frequency control system is chosen as case study. The effectiveness of the proposed method for the controller synthesis is tested through simulation. The derived proportion integration （PI） controller proves to be optimum where it is a compromise between compensating the random time delay effects and degrading the system dynamic performance. The range of the PI controller gains that guarantee the stochastic stability is determined. Also the range of the PI controller gains that achieve the robust stochastic stability is determined where the decay rate is used to measure the robustness of the system.

Detection and Estimation of False Data Injection Attacks for Load Frequency Control Systems

False data injection attacks(FDIAs)against the load frequency control(LFC)system can lead to unstable operation of power systems.In this paper,the problems of detecting and estimating the FDIAs for the LFC system in the presence of external disturbances are investigated.First,the LFC system model with FDIAs against frequency and tie-line power measurements is established.Then,a design procedure for the unknown input observer(UIO)is presented and the residual signal is generated to detect the FDIAs.The UIO is designed to decouple the effect of the unknown external disturbance on the residual signal.After that,an attack estimation method based on a robust adaptive observer(RAO)is proposed to estimate the state and the FDIAs simultaneously.In order to improve the performance of attack estimation,the H¥technique is employed to minimize the effect of external disturbance on estimation errors,and the uniform boundedness of the state and attack estimation errors is proven using Lyapunov stability theory.Finally,a two-area interconnected power system is simulated to demonstrate the effectiveness of the proposed attack detection and estimation algorithms.

H_(∞) Load Frequency Control Design Based on Delay Discretization Approach for Interconnected Power Systems with Time Delay

This paper proposes a delay discretization based H∞load frequency control strategy for interconnected power systems.The effect of time delay is considered in the system for the design of stabilizing controller.To improve the tolerable delay margin of the system,a two-term state feedback controller structure is used.The controller requires delayed state information as control input.In the proposed approach,the amount of delay introduced in the state of the system,i.e.,artificial delay,for taking control action is assumed to be constant.The approach is based on the discretization of this delay interval.In order to define a simple Lyapunov-Krasovskii(LK)function for each of the discretized interval,a stabilization criterion is developed in such a way that a single one satisfies the requirement of all the intervals.The developed criterion is computationally simple and efficient.

Detection of False Data Injection Attacks on Load Frequency Control System with Renewable Energy Based on Fuzzy Logic and Neural Networks

Load frequency control(LFC)system may be destroyed by false data injection attacks(FDIAs)and consequently the security of the power system will be impacted.High-efficiency FDIA detection can reduce the damage and power loss to the power system.This paper defines various typical and hybrid FDIAs,and the influence of several FDIAs with different characteristics on the multi-area LFC system is analyzed.To detect various attacks,we introduce an improved data-driven method,which consists of fuzzy logic and neural networks.Fuzzy logic has the features of high applicability,robustness,and agility,which can make full use of samples.Further,we construct the LFC system on MATLAB/Simulink platform,and systematically simulate the experiments that FDIAs affect the LFC system by tampering with measurement data.Among them,considering the large-scale penetration of renewable energy with intermittency and volatility,we generate three simulation scenarios with or without renewable energy generation.Then,the performance for detecting FDIAs of the improved method is verified by simulation data samples.

Optimal load frequency control through combined state and control gain estimation for noisy measurements

Combined estimation of state and feed-back gain for optimal load frequency control is proposed.Load frequency control(LFC)addresses the problem of controlling system frequency in response to disturbance,and is one of main research areas in power system operation.A well acknowledged solution to this problem is feedback stabilization,where the Linear Quadratic Regulator(LQR)based controller computes the feedback gain K from the known system parameters and implements the control,assuming the availability of all the state variables.However,this approach restricts control to cases where the state variables are readily available and the system parameters are steady.Alternatively,by estimating the states continuously from available measurements of some of the states,it can accommodate dynamic changes in the system parameters.The paper proposes the technique of augmenting the state variables with controller gains.This introduces a non-linearity to the augmented system and thereby the estimation is performed using an Extended Kalman Filter.This results in producing controller gains that are capable of controlling the system in response to changes in load demand,system parameter variation and measurement noise.

Effects of fractional-order PI controller on delay margin in single-area delayed load frequency control systems

This study aims to determine the improvement effect on the delay margin if fractional-order proportional integral(PI) controller is used in the control of a singlearea delayed load frequency control(LFC) system. The delay margin of the system with fractional-order PI control has been obtained for various fractional integral orders and the effect of them has been shown on the delay margin as a third controller parameter. Furthermore,the stability of the system that is either under or over the delay margin is examined by generalized modified Mikhailov criterion.The stability results obtained have been confirmed numerically in time domain. It is demonstrated that the proposed controller for delayed LFC system provides more flexibility on delay margin according to integer-order PI controller.

Design of a 2-DOF-PID controller using an improved sine-cosine algorithm for load frequency control of a three-area system with nonlinearities

This paper proposes an improved sine-cosine algorithm(ISCA)based 2-DOF-PID controller for load frequency control.A three-area test system is built for study,while some physical constraints(nonlinearities)are considered for the investigation of a realistic power system.The proposed method is used as the parameter optimizer of the LFC control-ler in different scenarios.The 2-DOF-PID controllers are used because of their capability of fast disturbance rejection without significant increase of overshoot in set-point tracking.The 2-DOF-PID controllers’efficacy is observed by examining the responses with the outcomes obtained with PID and FOPID controllers.The simulation results with the suggested scheme are correlated with some of the existing algorithms,such as SCA,SSA,ALO,and PSO in three dif-ferent scenarios,i.e.,a disturbance in two areas,in three areas,and in the presence of physical constraints.In addition,the study is extended to a four-area power system.Statistical analysis is performed using the Wilcoxon Sign Rank Test(WSRT)on 20 independent runs.This confirms the supremacy of the proposed method.