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High penetration of renewable energy-based generators increases variability in power systems. To prevent transmission lines from overloading due to such variations, advanced power flow management system should be developed. This paper proposes an Automatic Generation Control (AGC) design that mitigates power flow increase on heavy load lines. The developed method optimizes dispatching of control order from AGC so as not to increase power flow of these lines. This is achieved by considering how the output change of each control unit effects power flow in the system. The performance of the proposed method is examined by simulation study with 10-machine power system model. Furthermore, the communication infrastructure of the developed AGC system and its components are developed according to IEC 61850 communication standard. Operational instructions are mapped onto IEC 61850 messages. Simulations are performed with network emulators to validate the developed communication models and their operation. The benefit of the proposed communication system with IEC 61850 is achieving plug and play capability with universal models. The results of both simulations show that communication infrastructure is successfully developed and AGC prevents power flow increase in heavily loaded lines by making use of remained capacity of light loaded lines as proposed.

Communication plays a vital role in incorporating smartness into the interconnected power system. However, historical records prove that the data transfer has always been vulnerable to cyber-attacks. Unless these cyber-attacks are identified and cordoned off, they may lead to black-out and result in national security issues. This paper proposes an optimal two-stage Kalman filter (OTS-KF) for simultaneous state and cyber-attack estimation in automatic generation control (AGC) system. Biases/cyber-attacks are modeled as unknown inputs in the AGC dynamics. Five types of cyber-attacks, i.e., false data injection (FDI), data replay attack, denial of service (DoS), scaling, and ramp attacks, are injected into the measurements and estimated using OTS-KF. As the load variations of each area are seldom available, OTS-KF is reformulated to estimate the states and outliers along with the load variations of the system. The proposed technique is validated on the benchmark two-area, three-area, and five-area power system models. The simulation results under various test conditions demonstrate the efficacy of the proposed filter.

With the advancement of communication technologies and the development of the smart grid, today's physical power systems present an ever-growing dependency on cyber resources. It increases cyber vulnerabilities, causing safety and system stability concerns. In this article, a data-driven resilient automatic generation control (AGC) scheme is proposed under a false data injection attack (FDIA). The key idea is to identify the relationship between AGC signals and system operational conditions. This is achieved by the proposed regression-based FDIA signal predictions, including sequence-to-point prediction and the long short-term memory network-based prediction. It allows us to reconstruct the AGC control signals without being affected by FDIAs and to attenuate attacks in the closed control loop, thus alleviating the impact of FDIA on system performance. Numerical results carried out on the benchmark systems validate the effectiveness of the proposed method.

The electric power system is a complicated dynamic system with a range of operating states and parametric uncertainties, especially due to change of the network topology, load increment and generation scheduling. Under this circumstance, traditional power system transient stability analysis methods may not always be appropriate. This paper presents the development of a computational methodology for evaluating the effect of parametric uncertainties on the small-signal stability analysis of power systems. A probabilistic approach is applied as a metric for the dynamic performance of the damping ratio of critical eigenvalues. The method is based on a Monte Carlo simulation for the analysis of automatic control of generation. The methodology is used for the performance evaluation of three classical controller tuning techniques: Frequency Response, Approximate Method and Ziegler-Nichols. The results show that the methodology is valid and potentially useful for quantifying the effect of parametric uncertainties in power systems dynamics simulations.

In this paper, a cascade PI-PD secondary control scheme is presented in automatic generation control (AGC) application under a deregulated environment. Along with conventional electric power genera...

This article deals with automatic generation control (AGC) of a three-area power system having five diversified sources of generation like thermal unit, hydro unit, wind unit, diesel unit and a gas unit are interconnected together. Area-1 of the power system consists of a thermal, a hydro and a wind unit, area-2 has a thermal, a hydro and a diesel unit and area-3 consists of a thermal, a hydro and a gas unit. To make system more realistic different nonlinear components like governor dead band (GDB), generation rate constraint (GRC), boiler dynamics and communication delay are taken into account. A novel two-degree of freedom fractional order PID with derivative filter and fractional order PD with derivative filter (2-DOF-FOPIDN-FOPDN) cascaded control strategy is adopted to improve the dynamic performance of the power system. The results obtained with the proposed cascaded controller are compared with that of PID, FOPID and 2-DOF-PIDN-PDN cascaded controller to prove its superiority. To enumerate the gains of different controllers optimally, a recently developed bio-inspired optimisation algorithm named selfish herd optimisation (SHO) is capitalised. Further, the work is extended by taking a two-area hydro-thermal system to compare the result of the SHO tuned PID controller with that of modern hybrid firefly algorithm-pattern search (hFA-PS) technique. Transient analysis is carried out by applying a sudden load disturbance of 0.01 p.u in area-1 and the robustness of the controller is examined by varying both system parameters and applying a randomly varying load in area-1. From the investigation it is concluded that the 2-DOF-FOPIDN-FOPDN controller gives a flawless and a distinct performance.

Maintaining a generation-demand balance becomes more challenging nowadays due to the limited availability of traditional automatic generation control (AGC) and spinning reserves. In response to this concern, the purpose of the proposed paper is to bridge the gap by introducing battery energy storage system (BESS) control loop in the load frequency control (LFC) system. Furthermore, a minimum variable share of demand response (DR) is utilized as an additional mean to regulate the system frequency. The growing intermittency of controllable loads calls the awareness to incorporate frequency-sensitive loads by considering a variable load-damping coefficient in LFC problem. The presented control scheme demonstrates a stable power operation with the optimal sharing of BESS, dynamic DR, and the supplementary control loop. Moreover, because of the continuous and sudden variations in the demand, adaptive LFC controller is designed using fuzzy logic based on particle swarm optimization (PSO) tuning method. The proposed controller ensures a stable and robust frequency regulation of the system under load fluctuations. In this paper it is revealed that adding the BESS control loop is very effective in enhancing the performance of LFC as it can deliver fast power compensation. The obtained results prove the capability and effectiveness of the proposed method in an isolated power system.

The purpose of this paper is to show that the software ScicosLab can be used as an interesting and effective computational tool to analyze the automatic generation control of electric power systems. Firstly it is presented the software and, afterwards, the concepts and definitions of rotational movements in order to develop mathematical models for the generators equipped with steam turbines or hydraulic turbines and speed governors, and for their electrical loads. For the studies it is used a system comprised by two distinct interconnected areas where a load increase in one area is simulated without/with the tieline, ignoring, and then considering the primary and supplementary controls. Finally, it is analyzed a more realistic system with three distinct areas extracted from the Brazilian power system. The computational results show graphically the variations of the two main quantities of interest: the frequency of each area of the system and the tieline power. These quantities allow the evaluation of the system behavior after a disturbance that affects the generation-load balance. Within the above context, it is verified that the ScicosLab computer package effectively models and simulates the load-frequency control of power systems, qualifying, therefore, as an excellent alternative to replace any similar program which requires license payment. A proposta deste trabalho é mostrar que o software ScicosLab pode ser utilizado como uma ferramenta computacional, interessante e eficaz, para analisar o controle automático de geração de sistemas elétricos de potência. Inicialmente é apresentado o software e, em seguida, os conceitos de movimentos rotativos que permitem desenvolver os modelos matemáticos para os geradores equipados com turbinas a vapor ou hidráulica e reguladores de velocidade, e para suas cargas elétricas. Para possibilitar os estudos é utilizado um sistema constituído por duas áreas distintas interligadas, onde é simulado um aumento de carga em uma destas áreas, sem e com a linha de interligação, desconsiderando e, em seguida, considerando os controles primário e suplementar. Finalmente, analisa-se um sistema mais realístico com três áreas distintas extraído do sistema elétrico brasileiro. Os resultados computacionais mostram graficamente as variações das duas principais grandezas de interesse: a frequência de cada área do sistema e a potência da linha de interligação. Estas grandezas permitem avaliar o comportamento do sistema após uma perturbação que afeta o balanço geração-carga. Considerando o exposto acima, constata-se que o pacote computacional ScicosLab modela e simula eficazmente o controle carga-frequência de sistemas elétricos de potência, qualificando-se, portanto, como uma excelente alternativa para substituir qualquer programa similar que exige pagamento de licença. Mestre em Ciências

This paper presents an automatic generation control algorithm applicable for a multi-area power system. A more practical models is used to represent the main components of the power system. The frequency bias factor (B) is set optimally by using an artificial intelligence technique. The generation rate constraints (GRC) are taken into consideration with dead band characteristics of the governor. For the first time, a sequential optimization of the fractional order (PID) control parameters, the governor speed regulation (R) and the frequency bias factor (B) is proposed. The objective function to be minimized is the updated integral time absolute error (UITAE). The tuning of the control parameters is dependent on minimizing the objective function by using the Grey wolf optimization (GWO) algorithm. The proposed algorithm is tested on an interconnected three power pools different system (Reheat, Gas and Hydro) with varying degrees of load step change. The simulation results of the presented process are compared to those achieved by using the particle swarm optimization method. The results obtained reveal the robustness of the proposed algorithm in terms of settling time and peak overshoot.

In this article, Particle Swarm Optimisation (PSO) algorithm is used to obtain the controller gain for Automatic Generation Control (AGC) of the representation of an Interconnected Power System (IP...

This paper reviews on the function of Automatic Generation Control (AGC) as an intelligent mechanism in enhancing electrical power systems dynamic performance at various perturbations; by sustainin...

This work proposes a novel frequency regulation paradigm for multi-area interconnected power systems. The developed approach capitalizes on phasor measurement units (PMUs) advanced monitoring to overcome design limitations imposed by legacy supervisory control and data acquisition (SCADA) systems. For this, a novel measurement-based controller integrating primary and secondary regulation is proposed. First, taking advantage of PMUs synchronized measurements, novel centralized corrective actions are developed using dynamic data aggregation. These actions provide a foreknowledge of generators expected steady-state during the system dynamics, significantly improving the system frequency rebound and steady-state realization while ensuring null area control errors (ACE). Next, a new local power system stabilizing perspective is developed. This controller provides local counterweighting actions allowing for faster corrective actions without compromising the system dynamic response, i.e., mitigating oscillations and overshoots. The proposed approach design considers monitoring and communication system non-idealities, such as: latency, processing and waiting time, measurements synchronization and sampling resolution. In addition, stability and steady-state objectives are mathematically demonstrated, and comparative simulation case-studies developed. Obtained results indicate a meaningful improvement of power systems frequency regulation and reliability, including faster steady-state realization and rebound, mitigation of oscillations and overshoot, improved service capacity and higher reliability to cascade events.

Reflecting the uncertainty of renewable energy generations and loads, power system AGC signals are essentially random processes. For the sake of the optimal operation and control of the AGC participant, such as energy storage systems (ESSs) in a performance/mileage-based regulation market, taking the uncertain nature, especially the temporal correlation, of the AGC signals into consideration can be beneficial; hence, random process models of the AGC signals are needed. However, a continuous random process model of the AGC signal that jointly considers the probability distribution and the temporal correlation is still lacking. To fill this gap, this paper first presents a systematic methodology for modeling the continuous random processes of AGC signals based on stochastic differential equations (SDEs). It is shown that AGC signals may have a saturated stationary probability density function and a biexponential temporal correlation, which are very different from the renewable generations. To capture these special characteristics, SDEs are then carefully constructed, which are easy to use in optimization and control. Using the PJM traditional and dynamic regulation (RegD and RegA) signals and the signal received from a battery ESS (BESS) plant in Jiangsu, China for example, simulation shows that the SDE is able to simultaneously capture the probability distribution and temporal correlation accurately.

This paper proposes a novel Improved Artificial Electric Field Algorithm (IAEF)-based AGC in a multi-area power system to minimize the area control error and to obtain an optimal solution. Here, fo...

In the incessantly growing size and structure of the modern power system having different load demand uncertainties, the use of intelligent, proficient and robust automatic generation control (AGC) strategy is indispensable to deliver decent superiority of power supply to the consumers. This research presents a fuzzy-tilt-fractional order integral-filtered derivative (FTIλDN) controller as a novel control tool to improve AGC recital of multi-area interconnected power systems (PSs). The imperialist competitive algorithm (ICA) is employed to optimize the FTIλDN controller parameters. To boost FTIλDN controller performance, asymmetrically spaced membership functions (MFs) are utilized, where MFs adjoining to zero are meant for fine-tuning and MFs far of zero are used for coarse-tuning. Firstly, a well adopted linear 2-area reheat thermal PS (RTPS) is explored critically and then to signify the virtue and scalability of the approach, the analysis is conducted on a 5-area unequal RTPS comprising deadband and generation rate constraint nonlinearities. The supremacy of the approach is established by contrasting the results with ICA/bacterial foraging optimization algorithm optimized FTIDN and various existing controllers. Investigation of results affirms the better performance of FTIλDN over other controllers regarding minutest error criteria and undershoot/overshoot/settling time of frequency/tie-line power deviations at disturbances. Additionally, robustness analysis validates the robust conduct of FTIλDN controller under variations of parameters, load disturbances and in the incident of temporary/permanent tie-line outage. At last, a real-time hardware-in-the-loop (HIL) simulation test is performed to authenticate the viability and effectiveness of the method for practical applications.

The rapid advancement of electric consumer demand enforces challenging situations to manage high penetration of Solar PV and Wind Power into the hydrothermal system resulting in load frequency cont...

The amalgamation of the various renewable energy sources to the grid reduces the dependence on non-renewable energy sources for power requirements. The introduction of electric vehicles (EV), not only further reduces the burden on these non-renewables and renewables but also provides better stability fluctuated by load demands. This paper presents automatic generation control (AGC) of a two-area thermal system with a stab for incorporating EV within them and analyze its impact alongside other renewables. The performances of proportional integral-proportional derivative (PI-PD), proportional plus Integral (PI), proportional plus integral plus derivative (PID) and fractional-order proportional integral-fractional-order proportional derivative (FOPI-FOPD) controller are evaluated in the system without incorporation EV. The supremacy of FOPI-FOPD is limpidly revealed over others during the analysis. The superior FOPI-FOPD controller is then used to analyze the system with incorporation EVs. Extensive simulations and comparisons are provided to justify the competency of the EVs when incorporated in the system with other renewables. The optimization of controller parameters is performed using the Sine Cosine Algorithm, and the system is analyzed considering a step load perturbation of 5% in area1. All simulation works are performed in MATLAB/Simulink platform.

This paper presents the integration of renewable energy resources into the Automatic Generation Control (AGC) of two area power system under deregulation. Area-1 includes the combination of thermal system, gas power system, aggregate Electric Vehicle (EV), and Dish-Stirling Solar Thermal system (DSTS) whereas area-2 contains thermal system, gas power system, aggregate electric vehicle, and Wind Turbine System (WTS). To achieve the realistic approach, nonlinearities such as Generation Rate Constraint (GRC), Governor Dead Band (GDB), and Boiler Dynamics (BD) are explored in proposed test system. AGC's main aim is to keep the balance between load and generation and to achieve this balance secondary frequency regulation mechanism play an important role. Therefore, a tilt proportional integral derivative controller has been used to achieve desired dynamic response of the system. A new Quasi Opposition Lion Optimization Algorithm (QOLOA) has been suggested for studied system to get the optimum values of controller and system parameters. Integral Square Error (ISE) is considered as an objective function for the optimization of the anticipated AGC mechanism. Furthermore, Hybrid Energy Storage (HES) is used to damp the oscillation of the considered AGC system. Hence, for this investigation, it consists of the hybridization of the Redox Flow Battery (RFB) and Superconducting Magnetic Energy Storage (SMES) system. Additionally, the sensitivity analysis is also performed to evaluate the robustness of the proposed QOLOA based control scheme. The suggested control mechanism is compared with previously published work on the same platform to show the effectiveness and its superiority of presented work.

In this article, a robust model predictive control (MPC) is proposed for the gate-controlled series capacitor (GCSC) to contribute to load frequency control. The proposed control model consists of a two-layer MPC in which a nominal MPC produces an initial control signal together with a prediction of system frequency response in a nominal system without uncertainty. An ancillary MPC then produces a control command for the actual system with uncertainty based on measurements, and signals provided by the nominal system. The control signals are provided in such a way that the error in the frequency response of the actual system is minimized with respect to that of the nominal system. Optimization procedures are also conducted to attain optimal values of weighting coefficients associated with the input, and output in the objective functions. Constraints associated with system, and GCSC control are also taken in providing the control signals into consideration. A linear model is presented to formulate the contribution of GCSC control to the power flow of tie-line. The effectiveness of the proposed method in dealing with uncertainties is compared with a conventional MPC, a scheme with proportional-integral controllers, and a system without GCSC. The method robustness is also illustrated by case studies with load uncertainty, and wind power fluctuations, and also uncertainty of parameters. The impact of the delay in communication links on the performance of the control scheme is also evaluated.

This paper reveals Automatic Generation Control (AGC) strategies of power systems including diverse type power generating sources and comprehensive literature review is also presented. These diverse type energy sources considered conventional power sources like thermal, diesel, nuclear, etc. and Renewable Energy Sources (RESs). RESs are solar energy, wind energy, hydro energy, etc. A variety of AGC schemes based on hard, soft and artificial intelligent computation techniques is presented here. The benefits and their limitations of these energy generating units are also taken in this article. In the present scenario, deregulation, smart micro-grid and grid concept is also utilized with interconnection of the considered energy generating sources. The literature of this review article fulfills the gap of recent and previous decades research work and provides future exploration in AGC techniques.

The present work focuses on the power oscillation damping of an interconnected multi-area multi-source power system depicting the load fluctuations issue in reference frame of automatic generation control (AGC). In real-time, the load profile characteristic is un-deterministic and uncertain in nature. Therefore, a diverse perspective of area load profiles such as step load disturbance, pulse load perturbation, sinusoidal load pattern, random load pattern and uniformly distributed random load are taken into study. The investigated power system model is a two-area system, classified by reheat thermal, hydro and gas generating units, lumped together in a control area with the impacts of governor deadband and generation rate constraint. AGC performance work is propagated by proportional-integral-derivative (PID) controller with filter and, then, fractional order PID (FPID) controller. Also, a fast-acting thyristor controlled series compensator (TCSC) device modified by the Taylor theorem is incorporated as a damping controller to pursuit its significances in AGC tool. In an additional work, a lead-lag compensator block is also incorporated to the basic TCSC controller to show its impact on AGC. Sensitivity analysis of both the basic and the advanced TCSC damping controller is investigated under loading and model parameter variations. The design problem i.e., the constrained optimization problem is tuned by employing the quasi-oppositional harmony search (QOHS) algorithm. From the mathematical point of view, calculations eigenvalues, performance indices and transient parameters, and sensitivity analysis are presented in support of the designed TCSC-QOHS controller. Graphically, the simulation results are presented. The obtained simulation results showed that the realization of TCSC in series with the tie-line with the FPID controller can be an effective approach for the AGC tool.

This work pertains to integration of supercapacitor energy storage system with wind-penetrated two-area power system. A small-sized SCES device is incorporated in automatic generation control of each area. For robust and optimum usage of SCES, a customized neuro-adaptive predictive control model is developed using level 1 S-function coding. This model feeds reference power command to the converter of storage system with its voltage used as feedback loop. A step load disturbance reflecting load outage is introduced back to back in the power system. It is seen through simulation studies carried out in MATLAB Simulink Environment that there is significant improvement in frequency response and tie power deviations. SCES converter power limits are fully maintained; besides, SCES voltage and power response is also depicted.

The PID controller still remains a widely used and very effective means of achieving stability in control systems. Generally, the performance of the controller is determined by the proportional, integral and derivative gains of the controller. The classical techniques: ZieglerNichols (ZN) open loop method; ZN closed loop method; Chien-Hrones-Reswick (C-H-R) load rejection method; and meta-heuristic technique: the fuzzy logic algorithm, are used to determine the tuning parameters of the PID controller in this study. The performance comparison of these controllers is done for automatic generation control (AGC) of a multi-source single-area hydrothermal-gas power system. In such power systems, each source has a participation factor that determines its contribution to total power generation. The root mean square error (RMSE) is deployed to determine the proportionate balance of each generator’s output with its corresponding participation factor. The performance comparison of the controllers using Simulink/MATLAB shows that the fuzzy-PID controller achieved the most proportionate generation balance. http://dx.doi.org/10.30572/2018/kje/100310

As the conventional automatic generation control (AGC) is inadequate to deal with the strong random disturbance issues induced by the ever-increasing penetration of renewable energy to the power grids, this article proposes a deep-reinforcement-learning-based three-network double-delay actor-critic (TDAC) control strategy for AGC to handle the above problem, which is mainly developed by multiple neural networks to fit the system action strategies and evaluate the value. The proposed strategy can increase the exploration efficiency and the quality of AGC and improve the system control performance using the modified actor-critic (AC) method with incentive heuristic mechanism, while a novel iterative way of the value function is also used to reduce the bias of optimization effectively for achieving optimal coordinated control of the power grid. The simulations are provided in the work to show the control performance of the strategy. Compared with other smart methods, the simulation study demonstrates that TDAC has excellent exploratory stability and learning ability. Meanwhile, it also can improve the dynamic performance of the power system and achieve the regional optimal coordinated control.

Previously linearised plug-in electric vehicle (PEV) models are adopted in automatic generation control functioning. However, lesser attention is given towards the exact designing of a PEV unit con...

To enable power supply in rural areas and to exploit clean energy, fully renewable power systems consisting of cascaded run-of-the-river hydropower and volatile energies such as pv and wind are built around the world. In islanded operation mode, the primary and secondary frequency control, i.e., hydro governors and automatic generation control (AGC), are responsible for the frequency stability. However, due to limited water storage capacity of run-of-the-river hydropower and river dynamics constraints, without coordination between the cascaded plants, the traditional AGC with fixed participation factors cannot fully exploit the adjustability of cascaded hydropower. When imbalances between the volatile energy and load occur, load shedding can be inevitable. To address this issue, this paper proposes a coordinated tertiary control approach by jointly considering power system dynamics and the river dynamics that couples the cascaded hydropower plants. The timescales of the power system and river dynamics are very different. To unify the multi-timescale dynamics to establish a model predictive controller that coordinates the cascaded plants, the relation between AGC parameters and turbine discharge over a time interval is approximated by a data-based second-order polynomial surrogate model. The cascaded plants are coordinated by optimising AGC participation factors in a receding-horizon manner, and load shedding is minimised. Simulation of a real-life system with real-time pv data collected on site shows the proposed method significantly reduces load loss under pv volatility., Comment: Accepted by IET Renewable Power Generation; 13 pages

The paper addresses the Automatic Generation Control (AGC) of the interconnected two-area power system under deregulated environment. Area 1 includes thermal system, Distributed Generation (DG), an...

This letter proposes a novel decentralized event-triggered control algorithm to replace the conventional periodic sampling/communication mechanism of automatic generation control (AGC) for multi-area power systems. For each control area, event-triggering rules that only rely on local measurements are designed to decide the sampling/communication instants. Further, a strictly positive dwell time is introduced to exclude Zeno behaviours. The $\mathcal {L}_{\infty }$ -stability of the multi-area power system with the developed event-triggered control law and essentially bounded net load disturbances is studied, and a sufficient stability criterion is established. Finally, case studies demonstrate the effectiveness and efficiency of the proposed method.

Automatic generation control (AGC) is an automation scheme that regulates the output of several generators employed at different areas of an interconnected power system simultaneously in response to load variation in the most economical way. This article implements a fuzzy-two degree of freedom-PID controller considering derivative filter (F-2D-PIDF) optimally tuned through grasshopper optimization algorithms (GOA) for AGC of a three unequal area interconnected power system. Initially, comparative performance analysis is carried out for conventional PID controllers optimally designed by particle swarm optimization, teaching learning-based optimization and GOA techniques. After ensuring better performance from GOA based PID controller, the study extended to establish dominance of the proposed F-2D-PIDF controller over others like PID, PID with derivative filter (PIDF), two degree of freedom-PIDF, and fuzzy-PIDF for the same power system in presence and absence of nonlinearities with GOA framework. In all these above studies, a load perturbation of 0.01 p.u. is applied in area-1. Comparative performance analysis reveals that GOA based F-2D-PIDF controller outperforms other controllers in all aspects. Finally, robustness of the proposed controller verified by varying system parameters and loading condition.

For dynamic performance improvement of modern power systems, the use of fast acting energy systems like superconducting magnetic energy storage (SMES) is imperative. In this paper, incorporation of a small rating SMES in a solar and wind power penetrated multi-area power system is proposed. A non-linear neural adaptive predictive controller is used to generate an optimal power command taking into account the converter rating and energy level constraints of SMES unit. The SMES is represented by a control relevant model comprising of a first order lag compensator cascaded by an integrator to translate the hardware constraints pertaining to its coil current into modified power constraints. Moreover for avoiding the sudden SMES outage, the power thresholds are forcibly varied as the SMES current reaches near its maximum and minimum values. The uprightness of the designed scheme is illustrated by simulation studies performed on a three area power system.

The load frequency control (LFC) system is an essential component of the smart grid and is located between cyberspace information and the physical infrastructure. Because the operation of LFC depends on the modern network communication technology, it is vulnerable to network attacks. The false data injection attack (FDIA) injects attack data into the data collected by the LFC system, affecting the control center’s calculation and causing errors in the control signals, which affects the stable operation of the power system. For the LFC system, this article builds a cyber–physical model. Based on the model, an FDIA detection and defense mechanism based on the GAN network is proposed. By calculating, contrasting, and replacing the control signals, the proposed method can detect and defend against FDIAs. The experimental results on the two-area interconnected power system, the IEEE 39-bus, and IEEE 118-bus power system show that the proposed defense method can ensure the power system frequency and tie-line power deviation remain within the set value when suffered from FDIA.

This article deals with the Automatic Generation Control (AGC) mechanism for an interconnected, deregulated hybrid power system. The physical generation constraints such as boiler dynamics, governor dead band (GDB) and generation rate constraints (GRC) are included for a more realistic approach. The integration of distributed generation (DG) systems is also considered to match with present scenario. The intermittency nature of the DGs ruins the system's inertia and dynamic behaviour. A novel cascaded fractional order controller configuration 2-DOF (FOPIλDN)-PDN is proposed for the AGC mechanism and a new quasi opposition based volleyball premier league (QVPL) algorithm is employed to optimize the controller gains. On the other hand, the inertia emulation strategy (IES) based modified HVDC tie-line is used parallel to the AC tie-line to retrace the power system's inertia. The impact of the proposed controller and IES based modified HVDC tie-line has been analysed by subjecting to several case studies. The effectiveness of the QVPL based proposed controller has also been tested by comparing it with the previously published works on the same platform.

This paper proposes an event‐triggered distributed networked control scheme and its robust stability analysis strategy for the automatic generation control of multi‐area interconnected power system with wind turbines. First, for the large‐scale distributed networked control systems, considering the networked control systems with parameters uncertainty, effective transmission bandwidth, and time‐varying networked‐induced delays, a new distributed networked control systems model is proposed. Then, by constructing Lyapunov–Krasovskii functional method, the sufficient conditions for asymptotical stability of the system are obtained, a design method of event‐triggered distributed networked control law based on linear matrix inequality is proposed. In order to verify the effectiveness of the proposed scheme, a multi‐area power system with wind turbines is considered, and the system performance under different load disturbances is simulated. The simulation results show that the scheme has reliable robust performance for multi‐area distributed networked power system and improves the anti‐interference ability of the power system.

In this study, an adaptive fuzzy-based PID (AFPID) controller has been suggested for frequency regulation of power systems where the parameters of the proposed controller are optimised by a simplif...

This paper introduces an innovative approach for automatic generation control (AGC) of multi-area diverse-sources of the interconnected systems under a restructured scenario. In this work, proporti...

The introduction of variable renewable energies, such as photovoltaic systems (PV), into electric power systems will increase the amount of resources necessary to balance supply and demand in terms of both quality and quantity. Thus, a planned power generation that matches the planned values submitted in advance with the actual values of PV power generation is required by installing battery energy storage systems (BESS). Currently, since the cost of BESS is still high, eliminating the imbalance which equals to the difference between planned and actual values of PV power generation by BESS is not economically feasible, and appropriate cooperation is required to share the role of balancing with regulating generators. However, variable renewable energies can cause steep imbalances which cannot be compensated by regulating generators due to their relatively slow response times. To address this problem, this paper proposes a planned power generation method that can reduce the burden on regulating generators by introducing a strategy to mitigate the changing rate of imbalance, (hereinafter called “imbalance leveling”) by determining the optimal scheduling of BESS using the short-term forecast of PV power generation. Numerical simulations were conducted using a model based on Japanese frequency control to compare the proposed method with the conventional method without imbalance leveling. The results confirmed that the proposed method can improve the capacity value per unit of BESS in supply and demand adjustment owing to the effect of leveling the imbalance. Additionally, it can improve the performance of supply and demand adjustment with the same capacity.

In this article, an Improved Frequency Regulation (IFR) for an interconnected hybrid power system under a deregulated scenario is proposed. The analyzed test system comprises of a thermal power system, biogas plant, and Distributed Generation (DG). The impact of the integration of Renewable Energy Sources (RES) has been examined by considering DG system with solar and wind power generation. In order to make the system more realistic, appropriate non-linearities are incorporated into the thermal and biogas system. Electric Vehicle (EV) is also employed to take care of some portion of uncontracted demand. A maiden hybridized fuzzy-Proportional Integral (FPI)-Linear Active Disturbance Rejection Control (LADRC) is proposed and successfully implemented for IFR. Also, a new Quasi-Opposition-based Artificial Electric Field Algorithm (QO-AEFA) is proposed to acquire the optimal controller gain parameters of the tested system. A pertinent performance analysis is also examined for other employed algorithm in this study, to figure out the eminence of the proposed control algorithm. A comprehensive examination and comparison of the proposed controller with other controllers shows its effectiveness for the proposed test system. In order to ensure the reliability of the proposed controller, sensitivity analysis is also carried out for system parameters that reveal its robust nature. Further, case studies for random load variations and comparison with the works in previous literature also manifest the puissance of the current research work. Moreover, the improved results under random weather conditions illustrate the effectiveness of the proposed IFR under deregulation.

As the world’s population grows and energy demand increases, it is necessary to increase the scale of the electrical system, which is more complicated. Consequently, adopting automatic generation control (AGC) scheme to meet the demand becomes inevitable. In this article, the fusion of flower pollinated algorithm (FPA) and pathfinder algorithm (PFA), named hereafter as $h$ FPAPFA, is proposed to achieve maximum control efficiency by combining the exploitation of FPA with the exploration capacity of PFA. The proposed $h$ FPAPFA is meant to regulate two unequal multi-area interconnected power system with different generating units such as thermal, hydro, wind power and diesel plants. The proposed control scheme aims to achieve this by using the new algorithm to optimize the fractional-order set-point weighted PID (FOSWPID) parameters under time domain-based fitness functions namely, integral time square error (ITSE) and integral time absolute error (ITAE) while simultaneously minimizing the power losses. Employing the same interconnected power systems, a comparative study with some recent approaches in renowned journals is conducted. The performance of the proposed method is observed under diverse load conditions scenarios. Moreover, three nonlinearities including boiler dynamics, the governor dead band (GDB) and generation rate constraints (GRC) are further integrated into the system from a pragmatic context. Finally, sensitivity tests involving various parameter changes and the introduction of random step load perturbations are carried out. From the results, the proposed approach outperformed other approaches under different load condition scenarios, incorporation of nonlinearities and random load perturbation, demonstrating the proposed technique’s efficacy and reliability.

For the dependable, safe, and stable operation of electric systems, frequency should be regulated continuously employing appropriate intelligent controllers. Hence, this paper proposes a Chaotic Ha...

The frequency control is the mandatory task in a modern power system because of load demand variation and the integration of renewable energy sources (RESs). The main objective of automatic generation control (AGC) scheme is to maintain the balance between generation and load demand. This study proposes a graphical robust characteristic ratio assignment (RCRA) approach for PIDA controller tuning based on maximum sensitivity ( M s ) for AGC. The basic feature of this graphical approach is that characteristic ratios ( γ i ) in RCRA scheme are calculated in terms of M s . The important part of this design is that the analytical expressions for coefficient gains of PIDA controller are derived in terms of γ i and system parameters. Here, the non-reheat steam-turbine and hydro-turbine based single and multi-area power systems are considered for validation of the proposed control scheme. The critical issue in controller design for a hydro-turbine based power system is the non-minimum phase behaviour. The robustness and performance of RCRA-PIDA controller are examined under system non-linearities, parametric uncertainty and disturbances. Further, the performance of proposed approach is evaluated in the presence of RESs. Finally, it is observed that the proposed control approach performs better in comparison to the recently published control schemes.

Background Automatic 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. Results Based 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. Conclusions The 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.

Energy storage systems (ESSs) have been applied in power systems for a long time. It participates in the grid frequency control at two levels, the primary frequency control and the secondary frequency control. In this paper, a control strategy that integrates one synchronous generator (SG) and ESS as one single generation unit named flexible generator (FG) is proposed, allowing ESS to participate in primary frequency control. The main trick is that the proposed control strategy not only adopts SG's frequency as the ESS control input but also feeds back FG's total output power to control the ESS. FGs have more substantial damping and stability than SGs. The proposed control strategy has a superior performance compared to traditional PID control and fuzzy control strategies of ESSs. The flexible control parameters are determined by the linear quadratic regulator (LQR) with disturbance suppression. The ESS's capacity is discussed and determined. Simulation results of the New England 39-bus system verify the advantages of FGs both in load changes and faults. The HIL experiment results also illustrate the applicability and effectiveness of the flexible control.

Frequency disturbances caused by load perturbations of multi area interconnected power system are reduced by using proper control schemes provided via secondary control loop along with primary control of generation plants. These secondary controllers provide simultaneous control signal to individual machines of a particular area when the control scheme is area centralized. This area centralized mechanism provides quick control action with less computational burden since control problem dimensions gets reduced even the area consists multiple plants/machines. Such centralized new cascade control scheme is proposed in this paper to supervise the secondary control mechanism and it is implemented with parallel connection of 2-Degree of Freedom Proportional-Integral-Derivative (2-DOF PID) controller combined with regular PID controller. The performance of this new controller is studied on multi area multi machine interconnected power system with participation factor concept and later its relative performance in terms of dynamic and steady state specifications are compared with conventional PID and 2-DOF PID controllers. These control parameters are tuned by Invasive Weed Optimization (IWO) algorithm to achieve better system outputs. Case studies presented in this paper show the advantages of proposed control scheme.

LFC (Load Frequency Control) difficulty is created by load of power system variations. Extreme acceptable frequency distinction is ±0.5 Hz which is extremely intolerable. Here, LFC is observed by PID controller (PID-C), Fuzzy and ANFIS controller (ANFIS-C). To control different errors like frequency and area control error (ACE) in spite of occurrences of load disturbance and uncertainties of system is checked by MATLAB/SIMULINK software. Proposed Controller offers less, and small peak undershoot, speedy response to make final steady state. LFC is mandatory for reliability of large interconnected power system. LFC is used to regulate power output of generator within specified area to maintain system frequency and power interchange. Here, two area multi source LFC system is analyzed. ANFIS is utilized for tie-line power deviation and controlling frequency. Proposed controller is compared with other controller and it is found that proposed controller is better than other controller. Proposed controller is better in terms of Robustness. The output responses of interconnected areas have been compared on basis of peak-undershoot, peak-overshoot and settling time (Ts). Result of FLC is compared to that of with classical controller such as proportional derivative plus integral (PID) controller which suggests that conventional controller is slow. Keywords: LFC, Fuzzy, PID, ANFIS, LFC; FLC; ACE; PID-C, AGC.

In most of the automatic generation control (AGC) studies proposed so far, area control error (ACE) signal is derived considering fixed step size load disturbance which does not represent the real ...

The present research article has proposed a robust type-2 fuzzy PID (T2-FPID) controller to obtain automatic generation control (AGC) of a diverse energy source-based multiarea power system under v...

Objectives: To simulate automatic generation control (AGC) operation in a deregulated power system under availability based tariff (ABT) mechanism to regulate grid frequency during peak and off-peak hours. Method: For the simulation, the two areas, an isolated power system with Area1, which has thermal - hydropower plants with two DISCOs, and Area2 having a thermal – thermal power plant with two DISCOs have been considered. DISCO participation matrix (DPM) has been used for the visualization of bilateral contract by distribution companies (DISCOs) in the restructured environment. An AGC operation of two area power system with 10% load variations during peak hour and off-peak hour has been presented for the 24 hours in graphical form. Findings: The deviations in the grid frequency and Unscheduled Interchange (UI) charges or deviation settlement mechanism (DSM) rates of ABT due to sudden load changes and renewable power found. The frequent AGC operation of generators against load variation to stabilize the grid frequency is increasing wear and tear losses which finally increases maintenance cost and sometimes tripping of generators. Also, in peak hours and off-peak hours the drastic change in UI charges found during AGC operation so, there is a need to regulate grid frequency from the load side using distributed energy sources. Novelty: In proposed work, at the distribution side, Electric vehicle has been considered to regulate grid frequency during peak and off-peak hours. Work has been justified by appropriate data and simulated results. Keywords: AGC; deregulation; peak hours; offpeak hours; ABT