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The high penetration of Renewable Energy Sources (RESs) in the modern power system poses a challenge to power system stability. This stability is affected by the stochastic, fluctuating output of RESs, which is influenced by weather conditions, and a lack of inertia resulting from reduced rotating mass. To address this issue, a new controller, referred to as Proportional-Fractional Integrator Plus Proportional-Derivative with Filter, P I λ (1+PDF), is designed for Load Frequency Control (LFC) with the support of a Hybrid Energy Storage System (HESS) for power systems with high-RES penetration. The HESS comprises a Superconducting Magnetic Energy Storage System (SMES) and a Vanadium Redox Flow Battery (VRFB) coupled with an Interline Power Flow Controller Flexible AC Transmission Systems (IPFC-FACTs) controller. The HESS, working in conjunction with the proposed LFC, injects virtual inertia and maintains power flow to expedite the frequency stability process. These systems are also integrated with Alternating Current (AC) and High Voltage Direct Current (HVDC) transmission lines to collectively enhance both the system's stability and the capacity of its transmission lines. To optimize the P I λ (1+PDF) controller parameters, Zebra Optimization Algorithm (ZOA) is employed utilizing an Integral Time Absolute Error (ITAE) objective function. The proposed controller is tested on a four-area power system integrated with a wind turbine, photovoltaic (PV) panels, a biodiesel generator, and a hydrogen aqua electrolyzer fuel cell, representing a high penetration of RESs in modern power systems. The results are compared with those obtained using Proportional-Integral-Derivative (PID) and Fractional Order Proportional Integral Derivative (FOPID) controllers. Sensitivity analysis and robustness tests are also performed to verify the stability of the power network by changing system parameters and under randomly chosen loading conditions. The proposed P I λ (1+PDF) controller tuned with ZOA outperforms PID and FOPID controllers by minimizing settling time for frequency changes by 62 %, eliminating overshoot, and reducing undershoots for frequency and tie-line power changes by 73 % and 55 %, respectively. Simulation results demonstrate that the proposed controller outperforms PID and FOPID controllers by effectively damping frequency and tie-line deviations, resulting in reduced frequency overshoots, undershoots, and shorter settling times. [ABSTRACT FROM AUTHOR]

As the penetration rate of renewable energy in new power systems continues to increase, these systems face serious frequency control issues. The limitations of traditional methods for addressing frequency control lie primarily in their reliance on the frequency regulation capability of a single battery energy storage system (BESS). This dependence not only requires a complex communication infrastructure to transmit remote control signals but also is susceptible to communication delays, leading to system instability. This paper proposes a distributed BESS robust frequency control method (load frequency control (LFC)) based on a sparse communication network, aiming to address the limitations of traditional methods in terms of communication infrastructure requirements and the impact of communication delays. Subsequently, a dual-layer model predictive control (MPC) strategy is designed. The first layer uses a nominal model for predictive control, while the second layer considers system uncertainties for auxiliary control to improve the response characteristics of the BESS, thus significantly enhancing LFC performance and achieving more effective frequency regulation. Finally, simulation results show that under different parameter conditions, such as capacity, state of charge (SoC), and time constants, the response capability and frequency regulation effect of the distributed BESS are significantly better than those of traditional methods. [ABSTRACT FROM AUTHOR]

A three-stage decentralized controller design algorithm is developed to achieve setpoint tracking and disturbance rejection in MIMO systems with communication time delay, and nonlinearities such as saturation and dead band. The first stage involves reference model formulation. The second stage comprises equating approximate generalized time moments/approximate generalized Markov parameters of closed-loop system model with reference model at certain expansion points in s-plane to obtain synthesis-like equation, concerning products of unknown controller numerator and denominator polynomials. This process yields simultaneous linear equations, whose solution provides the coefficients of the product polynomials. In the third stage, the controller parameters are extracted from the product polynomials using exact model matching. The proposed method is illustrated by designing load frequency controller in traditional and restructured power systems under scenarios like system parameter uncertainties, random load variation, and time-varying communication delays. Simulation studies reveal the efficacy of the proposed technique over existing techniques. Furthermore, the practical implementation feasibility of the decentralized controller designed for the restructured power system is validated using the TMS320F28379D controlCARD. [Display omitted] • Model matching decentralized controller design for servo and regulatory problems. • Handles communication time delay, saturation, and dead band nonlinearities. • Need for decoupler and order reduction of MIMO system is not required. • 1/2/3-DOF controller of any structure can be designed irrespective of system's order. • Real-time validation of designed controller using TMS320F28379D controlCARD. [ABSTRACT FROM AUTHOR]

In the current power landscape, renewable energy sources (RESs) have assumed a crucial role in satisfying consumer demand. However, as the deployment of renewables increases, certain challenges arise, including issues with system frequency stability, inertia, and damping reduction. To address these concerns, an innovative approach is suggested in this study. The proposed strategy aims to maintain frequency stability in a diverse-source power system that encompasses two interconnected regions incorporating RESs. The proposed strategy comprises a new multi-degree of freedom FOTID controller known as the MDOF-TI λ D μ N controller in the secondary control loop (SCL) and optimally controlled fuel cells (OFCL) to enhance the system's stability under the effect of renewable energy (RESs) fluctuations. In this context, the gains of the considered strategy (optimal MDOF-TI λ D μ N in addition to OFCL) have been picked out by using an innovative optimization approach known as the Capuchin search algorithm (CapSA). The statistical tests are used to examine the efficacy of the considered CapSA compared to those of other optimization strategies utilized in previous studies. Furthermore, the performance of the proposed controller in the SCL is verified by contrasting its performance with that of another suggested controller known as MDOF-PIDN as well as other controllers such as PD-IT, PD μ N-I λ T, 2DOF-TI λ D μ N, 3DOF-PIDN, 3DOF-TIDN, and 3DOF-PI λ D μ N. Additionally, grid nonlinearities, including Boiler Dynamics, Generation Rate Constraint, Governor Dead Band, and random communication time delay (CTD), are considered. Moreover, the proposed strategy's performance is verified in the face of system constraints and nonlinearities. Different scenarios are implemented, and the simulation outcomes emphasize the superior performance of the suggested strategy. Therefore, the suggested strategy provides consistent power system adoption wherever it is implemented. • Proposing a coordination strategy based on applying LFC and controlled optimal fuel cell (OFCL) to strengthen the performance of a hybrid two-area system under the impact of the significant penetration of RESs. • Incorporating the proposed MDOF − T I λ D μ N controller into the secondary control loop of the LFC. • Validation of the efficacy of the suggested MDOF − T I λ D μ N controller in comparison with that of another suggested MDOF − PIDN controller in addition to that of other controllers in previous literature. • Evaluating the system performance considering conventional FCL (CFCL), OFCL, and OFCL controlled by the PI controller to indicate the best system performance. • The coefficients of the suggested MDOF − T I λ D μ N as well as OFCL and PI controller coefficients are established using a novel optimization technique called CapSA. [ABSTRACT FROM AUTHOR]

This paper proposes a robust decentralized single-phase double integral sliding mode control (SMC) method combined with state observer for load frequency control of the multi-area power system integrated solar power sources. This study elaborates on how the proposed method secures the stability of the whole system as well as keeps frequency values within their safety ranges. Firstly, the designed observer ensures exact estimation of the actual states leading to convergence of estimated errors to zero. Secondly, a single-phase double integral sliding surface is designed completely based on estimated state variables achieved by the observer. A single-phase approach is employed to set up a sliding surface containing the initial point of the system trajectory and remove the reaching phase. Then, a new double integral SMC rule is developed to secure the finite time reachability as well as eliminate the oscillating and chattering issues. Finally, the effectiveness of the proposed method is validated thoroughly by simulation studies on LFC schemes in three-area power systems and the IEEE 39-Bus New England system to expose its advantages via various impact conditions. [ABSTRACT FROM AUTHOR]

In recent years, the conventional power system is becoming a hybrid power system with increments in the interconnection of Renewable Energy (RE) sources, High Voltage Direct Current (HVDC), and Energy Storage (ES). At the same time, the power system network is also becoming more flexible in managing demand and supply variability. These factors posed a challenge in achieving frequency stability when there are abrupt changes in the power system such as load increment/decrement, loss of generators, and faults. Due to this, load frequency control (LFC) has shifted from traditional controllers to hybrid controllers and from traditional optimization methods to hybrid metaheuristic optimization to achieve better stability in hybrid power systems. This paper provides a comprehensive review of load frequency control (LFC) and power system flexibility. Other frequency stability mechanisms that support further LFC i.e. application of frequency nadir and rate of change of frequency (RoCoF), control in wind turbines, and demand response are also presented. This review also highlights the research gaps and potential future research direction of LFC for multi-area hybrid power systems. [ABSTRACT FROM AUTHOR]

The purpose of automatic generation control (AGC) is to maintain a balance between the total output of the generation system against the losses at the load side in order to maintain the desired frequency and the power exchange with the neighboring areas. If there is a mismatch between generated power and the demand, the grid frequency deviates from the rated value. This high frequency offset may results in complete failure of the power system. Both load frequency control (LFC) loop and automatic voltage regulation loop (AVR) connected together in electrical systems regulates the energy flows and frequencies by AGC. The LFC system provides load control of the generator through zero frequency Steady state error and optimal transient behavior which are the goals of the LFC in an interconnected multi-zone electrical system. This paper presents a hybrid ANFIS-ANN based load frequency controller oriented by Particle Swarm Optimization (PSO) algorithm. This technique can be implemented in a two area interconnected system in order to maintain the system frequency within the nominal value and to prevents accidental exchange of power between the two areas during load changes. The proposed method is tested in the MATLAB software to estimate its performance and the results are compared with conventional PID controller, Artificial Neuro-Fuzzy Inference Systems (ANFIS) and Artificial Neural Networks (ANN) based controller to prove its supremacy. [ABSTRACT FROM AUTHOR]

This work presents design and theoretical analysis of an adaptive fractional-order sliding-mode disturbance observer (FO-SM-DOB)-aided fractional-order robust controller for frequency regulation of a hybrid wind–diesel based power system, considering endogenous/exogenous system disturbances. Adaptive FO-SM-DOB is designed to estimate unknown/uncertain lumped system disturbances, including parametric uncertainty and exogenous disturbances. Afterwards, an improved fractional-order sliding mode controller (FOSMC) augmented with the estimated output of FO-SM-DOB is designed and applied to accelerate system dynamics with minimum chattering in the control effort. The Mittag-Leffler stability theorem affirms the finite-time convergence of disturbance estimation error. Moreover, the closed-loop asymptotic stability of the overall control system has been guaranteed by applying Lyapunov argument. The effectiveness of the suggested resilient fractional-order nonlinear frequency controller is theoretically validated by performing an extensive comparative study with SMC, FOSMC (without DOB), state observer-based SMC (SOB-SMC), second-order SMC (without DOB), and conventional integer/fractional-order controllers. Simulation results establish the supremacy of the proposed resilient fractional-order nonlinear frequency controller over its other counterparts concerning fast disturbance rejection, weaker chattering, and a high degree of robustness against unknown lumped system disturbances. Further, to demonstrate the practicability and validate the effectiveness of the proposed control strategy, magnetic levitation system and IEEE 39-bus New England power system are considered and successfully tested on MATLAB platform. • An adaptive fractional-order sliding-mode disturbance observer is designed to estimate lumped unknown plant disturbances. • An improved fractional-order sliding mode controller is designed considering the estimated disturbance output. • Asymptotic convergence of estimated disturbance error and closed-loop stability of the overall system have been affirmed. • Robust closed-loop stability of the investigated hybrid power system using proposed robust controller has been guaranteed. [ABSTRACT FROM AUTHOR]

One of the crucial quantities in the power system problem is frequency, which should never exceed its nominal value. In normal conditions of load changes, the frequency is adjusted by automatic generation control. Still, in the face of special conditions, such as logging of the downstream network from the main network or a significant amount of generated power leaving the circuit, the power imbalance between generation and consumption causes a rapid frequency drop. In this case, the automatic generation control cannot stop the frequency drop, so the frequency tends toward instability. In this paper, to automatically produce a water-thermal system in two zones of discrete and continuous modes, the design of a fractional controller is discussed and investigated in different functional conditions and uncertainties. The proposed NSGA-II multi-objective method is used in this article to optimize each area's load frequency control parameters for various goals. The ideal response for the entire network will be obtained by modifying these responses using a multi-factor method. This paper defines a multi-zone frequency load control based on time objective functions and eigenvalues. Based on the speed changes for the proposed algorithm and the novel approach function method employed in the control design. The simulation performed and analyzed in different working conditions with different comparative criteria has been discussed and investigated. Compared to more contemporary techniques, the simulation results show that the system's performance is guaranteed. The main successes of the suggested method in comparison to earlier methods have been the reduction of overshoot, undershoot, and settling time. [ABSTRACT FROM AUTHOR]

Establishing robust electrical interconnections between nations is a pivotal foundation for significant investments and addressing energy shortfalls in regions grappling with generational challenges. However, developing electrical load disruptions within interconnected systems can lead to substantial variations in frequencies and energy transmission. Load Frequency Control (LFC) is a crucial mechanism to mitigate these disruptions and ensure stable operations in interconnected regions. While meta-heuristics have been employed for LFC design, some techniques face challenges like early convergence and poor accuracy due to a lack of population diversity. In this study, a novel Modified Cheetah Optimizer (mCO) is proposed to optimize the parameters of LFC system, incorporating fractional-order proportional integral derivative (FOPID) controllers within multi-interconnected system with renewable energy integration. The mCO integrates learning-from-experience and random contraction strategies to enhance convergence accuracy and overcome local optima, demonstrating superior efficiency in solving optimization problems. The proposed mCO is evaluated by solving twelve functions from the CEC2022 test suite, showcasing its effectiveness. The optimization problem involves minimizing the Integral Time Absolute Error (ITAE) of the area control error, considering changes in frequencies and exchanged power, with controller parameters λ d , k d , k i , k p , and μ to be identified. Two interconnected systems, photovoltaic (PV)-thermal and thermal-wind turbine (WT)-thermal-PV, are assessed under various load disturbances. The mCO is compared with other methods, including Modified Hunger Games Search Optimizer (MHGS), Driving Training-Based Optimizer (DTBO), Grey Wolf Optimizer (GWO), Aquila Optimal Search (AOS), and Cheetah Optimizer (CO). In the case of PV-thermal linked system, the proposed mCO succeeded in mitigating the ITAE by 19.21% compared to the reported MHGS and 8.63% compared to the conventional CO. In the four interconnected systems, the suggested approach reduced the ITAE by 89.21% and 15.26% compared to the reported MHGS and conventional CO, respectively. This confirmed the efficacy of FOPID-LFC, which was designed using the proposed mCO in all examined scenarios. • A novel mCO is proposed to fine-tune the optimal parameters of FOPID-LFC. • Learning-from-experience and random contraction strategies have been integrated into CO. • The proposed mCO is tested on twelve functions from CEC2022 test suite. • PV-thermal and thermal-WT-thermal-PV are studied in this work. • The FOPID-LFC optimized with mCO was successful in all studied situations. [ABSTRACT FROM AUTHOR]

In this paper, an objective function considering performance index and an improved gravitational search algorithm (IGSA) are proposed to optimize the parameters of fuzzy PID (FPID) controller. IGSA is obtained by combining elite strategies and the mining capability of PSO algorithm. The IGSA FPID method which integrates IGSA and FPID controller is tested in a typical two-area non-reheat system, and system responses reflect the advantages of proposed objective function and IGSA. Additionally, the proposed IGSA FPID method still has excellent effects even on the two-area multi-source system with thermal power, hydropower and gas turbines. Meanwhile, the effect of high voltage direct current (HVDC) links in suppressing fluctuations is verified. Due to the popularity of wind power, a novel three-area interconnected power system with nonlinearity connected wind turbine (WT) is designed. Under the control of IGSA FPID, the good stability and dynamic performance of mentioned three-area system are verified. Therefore, FPID controller optimized by IGSA has excellent control effects, stability and universal applicability on the different power systems with multiple area and sources. [ABSTRACT FROM AUTHOR]

Load frequency regulation is one of the most vital and complex ancillary services in a deregulated power system. Increasing penetration from renewable energy sources in an integrated power system (IPS) further escalates the related control complexity due to a considerable decrement in IPS's effective inertia. This may incur additional costs and can even lead to the destabilization of IPS. To overcome these problems in frequency regulation, this work proposes and investigates the use of an intelligent, direct adaptive control scheme, i.e., self-tuning fractional order fuzzy PID (STFOFPID) controller with and without the presence of a recently devised energy storage unit, i.e., the redox flow battery. The IPS' efficacy with the STFOFPID controller is validated for various contracts in a deregulated operation mode for considered three area IPS. Extensive simulation studies are carried out, and detailed comparative studies have been drawn with conventional PID and fractional order PID controllers for load frequency regulation in Poolco, bilateral, and contract-violation mode of operation. Robustness analysis in terms of parametric variations in different nonlinearities present in a reheated thermal power plant is also carried out, and the efficacy of the STFOFPID controller is established using a thorough quantitative comparative analysis. The real-time digital simulation validation of the investigated control structure has been carried out on OPAL-RT 4150 based on Xilinx Kintex-7 FPGA board with INTEL multi-core processor. • Implementation of the direct adaptive control scheme (STFOFPID) for deregulated IPS. • Incorporation of RFB with existing systems to improve LFC performance. • System performance study with presence of RFB under random step load perturbation. • Robustness study of studied control schemes for variations in GDB and GRC. • Real-time validation of the proposed control scheme on OPAL-RT 4150 for explored IPS. [ABSTRACT FROM AUTHOR]

Electrical power system has to operate properly even in the presence of load variations and other disturbances. One of the concepts that define this condition is frequency stability, and to deal with this issue, load frequency controllers (LFCs) have to be well designed and parameterized. The most frequent control approaches for LFC are PID controllers, with automatic tuning strategies. Recently, fractional-order PID has gained much interest due to its ability to improve closed-loop performance. This paper presents a new hybrid load frequency control strategy, called AFOPID. The main property of this algorithm is, based on a FOPID, to combine fuzzy sets and differential evolution (DE) for optimal parameter settings. The AFOPID's parameters are tuned online in such a way that, in the occurrence of a load disturbance, the fuzzy logic updates its k p , k i , and k d coefficients to adapt the closed loop to the new operating condition. Then, the fractional coefficients λ and μ are updated by using a DE strategy. The hybrid system improves the overall solution since the fuzzy system first sets a good operation point and then the DE refines the solutions acting on the fractional orders. The proposed controller and tuning method are validated on a mathematical model of a hydroelectric plant belonging to the Brazilian National Interconnected System (SIN). The strategy has been compared with other similar algorithms in the same situation presenting better closed-loop performance. For controllers evaluating, some performance indices were used, such as the analysis of overshoots/undershoots, settling times, the integral square error, the integral time square error, and the integral time absolute error. The results have shown that the hybrid method has proved to provide better closed-loop performance than similar solutions or when each method is used alone. [ABSTRACT FROM AUTHOR]

Load frequency control (LFC) serves a critical purpose in modern power systems, controlling system frequency and tie-line power flow. Nowadays, the power systems are integrated with an effective contribution of renewable energy sources (RESs). This paper broaches a modern power grid paradigm including conventional generators considering non-linearities, in addition to RESs and energy storage (ES) units for the study of LFC issue. Three forms of RESs are involved in the study, which are wind, photovoltaic and solar thermal. Besides, the system paradigm contains two types of ES units which are superconducting magnetic energy storage (SMES) and battery energy storage (BES). The controllers used for the system model analysis are proportional-integral-derivative (PID) controllers. The optimum design of the controller is established using a novel optimization approach which is a Marine Predators Algorithm (MPA). To certify the realistic credibility of the proposed algorithm, real data are imported to the RESs. The efficacy of the applied MPA-tuned controller is contrasted with that tuned by other competing evolutionary algorithms. The simulation outcomes demonstrate the credibility of the suggested control scheme. Also, the results ensure the role of ES units in enhancing the time-domain transient responses. The simulation findings are acquired through MATLAB framework. [ABSTRACT FROM AUTHOR]

This paper proposes a novel robust controller for frequency stabilization of electrical systems taken into consideration a high renewable energy sources (RESs) penetration. The suggested controller, robust PID (RPID) controller, is combination of a proportional–integral–derivative (PID) controller and a linear quadratic gaussian (LQG) controller. Furthermore, the Improved lightning attachment procedure optimization (ILAPO) technique is applied for determining the optimal setting of the parameters of the introduced RPID controller. A studied power system with RESs is used as a test system to justify the performance of the RPID controller. The superiority of the introduced robust controller is verified through a comparison of its performance under system uncertainties with those of other robust controllers presented in the literature. The results elucidate that the RPID controller can effectually enhance frequency stability and guarantee reliable performance for power grids supplied with high share of renewable energy for all studied scenarios. Consequently, the proposed RPID controller purveys creditable for modern power systems considering RESs. • A new robust control strategy for frequency stability improvement of power systems. • Considering high share of renewable energy sources. • Proposed RPID controller is based PID controller and linear quadratic Gaussian approach. • The parameters of RPID controller are optimally determined using ILAPO. • The RPID is compared with conventional PID controllers under system uncertainties. [ABSTRACT FROM AUTHOR]

This paper proposes a Cascaded PIDA (Proportional-Integral-Derivative-Acceleration) load frequency controller (LFC) for interconnected power systems with Wave Energy Conversion Systems (WECS). The proposed controller parameters are optimized using the Marine Predator Algorithm (MPA), which is a recent optimization technique known to be robust. The Cascaded PIDA controller results are compared to the results of a single structure MPA based PIDA controller and other PIDA controllers whose parameters are optimized using various optimization techniques presented in previous literature. Results show that the MPA-based PIDA-LFC has better results than other PIDA controllers optimized by other techniques, while the MPA-Cascaded PIDA-LFC has proven to have the best performance where the frequency and the tie-line power fluctuations, due to the connected Wave Energy Conversion System, are efficiently damped. Moreover, the results are presented in the form of time-domain simulation conducted via MATLAB /SIMULINK. [ABSTRACT FROM AUTHOR]

In power systems, generation must be maintained in constant equilibrium with consumption. A key indicator for this balance is the frequency of the power grid. The load frequency control (LFC) system is responsible for maintaining the frequency close to its nominal value and the power deviation of tie-lines at their scheduled levels. However, the remote communication system of LFC exposes it to several cyber threats. A successful cyberattack against LFC attempts to affect the field measurements that are transferred though its remote control loop. In this work, a data-driven, attack recovery method is proposed against denial of service and false data injection attacks, called DAR-LFC. For this purpose, a deep neural network is developed that generates estimations of the area control error (ACE) signal. When a cyberattack against the LFC occurs, the proposed estimator can temporarily compute and replace the affected ACE, mitigating the effects of the cyberattacks. The effectiveness and the scalability of the DAR-LFC is verified on a single and a two area LFC simulations in MATLAB/Simulink. [Display omitted] • Neural networks are able to recover power system automation from cyberattacks. • The control signals of load frequency control can be estimated by the generation of selected power plants. • Data-driven defence schemes can mitigate different types of cyberattacks, including denial of service and false data injection attacks. • Data-driven defence methods are scalable to power systems of varying complexity. [ABSTRACT FROM AUTHOR]

The design and control of an intelligent integrated standalone micro-grid (I-ISMG) have been proposed in this study. The ISMG system consists of solar photovoltaic (SPV), wind turbine generator (WTG), diesel engine generator (DEG) as distributed power generation (PG), and battery and flywheel as energy storage systems (ESSs). An improved incremental conductance (I-InC) maximum power point (MPP) tracking (MPPT) scheme, and a fuzzy wind power generation model (FWPGM) are utilized to obtain the power from solar, and wind energy systems respectively. The key contribution of this work is to control the power flow for synchronous micro-grid (MG) operation, which in turn resolves the problem of load frequency control (LFC). In this control strategy, an intelligent, i.e. fuzzy logic-based adaptive control scheme is proposed for the coordinated power flow among the generation, demand, and storage system. To minimize the frequency deviation (Δ f) and control of PG from WTG and DEG, frequency support (FS) fuzzy logic-based droop characteristic is employed. For the droop control in WTG and DEG, fuzzy logic-based proportional–integral–derivative (F-PID), and self-tuned-fuzzy PID (STF-PID) control schemes are utilized respectively. Apart from droop controls, a fuzzy observer (FO) is designed to manage power flow to/from the storage systems. Further, the proposed control scheme has been benchmarked using single area power system (SAPS) and modified New England IEEE 39 bus system. [Display omitted] • Developing the accurate model of ISMG system including SPV, WTG, DEG and energy storage systems. • Extraction of power from solar and wind energy using I-InC MPPT technique and FWPGM respectively. • To design frequency support FD i.e., F-PID and STF-PID droop controls for WTG and DEG respectively and compare with CDs. • Designing of fuzzy observer to enhance the storage and supply capability of energy storage systems. [ABSTRACT FROM AUTHOR]

This paper addresses the designing of an adaptive type-2 fuzzy PID (T2FPID) controller for load frequency control (LFC) of an interconnected nonlinear power system considering input time-delays. The input delay, which can commonly be raised by failure in the communication links and actuator operating lag may lead to control system instability. In the proposed adaptive T2FPID controller, output scaling factors have been chosen judiciously (according to a stable tuning algorithm) and thus improves the stability and performance of the controlled system. To perform this, the stability of the proposed method has been examined using the Lyapunov–Krasovskii (L-K) theorem, and the adaptation laws of the output scaling factors are derived. The proposed adaptation laws for the output scaling factors are simple and need a little knowledge about the structure of the power system. To demonstrate the efficiency of the proposed adaptive T2FPID controller, a comparison to the non-adaptive T2FPID and type-1 FPID (T1FPID) controllers is given for a two-area interconnected nonlinear power system with input time-delays. The obtained simulation results prove that the performance of the proposed T2FPID controller is superior compared to the other controllers in the presence of time-varying input delays, nonlinearities, and uncertainties. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive load frequency control technique in both of isolated microgrid power system and two interconnected microgrids (MGs). A modified Jaya optimization method is used to make online tuning of the area controller. The Balloon Effect (BE) modification is designed to increase the sensitivity of the Jaya algorithm to both of the system load disturbance and parameters variations. In Jaya with BE technique, the objective function (OF) is affected by the on-time system problems. Communication delay time is considered in the dynamic model of interconnected MGs. System with proposed adaptive control method has been tested in several scenarios including step and variable load demand and parameters variations. Simulation results using Matlab software show that the proposed adaptive controller tuned by Jaya + BE technique provides better performance of frequency control than other methods such as conventional controller or adaptive one tuned by classical Jaya algorithm. [ABSTRACT FROM AUTHOR]

In this article, we develop an original high order sliding mode control (SMC) method which can be used to control single input single output (SISO) system and multi-variable system. The method has the benefit of resisting unmodelled dynamics and external disturbance. However, there exist the chattering effect in the conventional control methods. For decreasing the chattering phenomenon, a new high order SMC method is raised. Firstly, the new methodology is designed. Secondly, the method is employed to control the single input single output system with two examples. Thirdly, this new scheme is applied to control the multi-variable system. At the same time, two examples are presented to testify the validity of the raised control method, then the raised new control method has been utilized to the load frequency control. Additionally, in comparison with other recently existed high order control method, the raised control method has demonstrated better control performance in terms of fast convergence and chattering phenomenon. • In this paper a novel high order sliding mode control method has been addressed. • The stability of this new method has been proved mathematically. • The proposed method has been applied to the SISO system, but also multi-variable system. Additionally, it has been used to the load frequency control based on two areas power system. The simulation results verify the effectiveness of the proposed method. • The proposed high order sliding mode control method has been compared other recently proposed high order sliding mode control method, which proves the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this paper a novel adaptive sliding mode control method has been designed and applied to the load frequency control. Firstly, a novel adaptive sliding mode control method is designed. Secondly, the stability of this method has been proved mathematically. Finally, one numerical simulation example is presented to verify the effectiveness of the proposed control scheme. At the same time, the proposed new adaptive sliding mode control method is compared with the classical adaptive sliding mode control method. From the simulation results, it is confirmed the validity of the proposed adaptive sliding mode control method in terms of external disturbances and parameter variation. It is also verified the superiority of the proposed adaptive sliding mode control method in terms of chattering, overshoot and response time in comparison with classical adaptive sliding mode control method. [ABSTRACT FROM AUTHOR]

The mathematical model of load frequency control is established in the interconnected power system of hydro, thermal, and wind for solving the problem of frequency instability in this paper. Besides, the improved grey wolf optimization algorithm (GWO) is presented based on the offspring grey wolf optimizer (OGWO) search strategy to handle local convergence for the GWO algorithm in the later stage. The experimental results show that the improved grey wolf algorithm has a superior optimization ability for the standard test function. The traditional proportional integral derivative (PID) controller cannot track the random disturbance of wind power in the hydro, thermal, and wind interconnected power grid. However, the proposed OGWO dynamically adjusts the PID controller control parameters to follow the wind power random disturbance, regional frequency deviation, and tie-line power deviation. [ABSTRACT FROM AUTHOR]

This paper presents a hybrid isolated power system modeling and Load Frequency Controller (LFC) for different penetration levels of wind power generation. The system considered here consists of a conventional diesel generator, wind generator and energy storage system for a LFC. The purpose of the considered system is to suppress the frequency deviations (balancing the real power generation and demand). An inertia control is used to obtain the best possible gain of the wind system and Fuzzy Logic Control (FLC) is used to control the frequency of the hybrid system. The results are compared with different control techniques. The dynamic performance of the system is studied at different cases by changing the wind penetration level and also by increasing the load disturbances. [ABSTRACT FROM AUTHOR]

This research work proposes a hybrid dragonfly algorithm and pattern search (hDA-PS) technique to optimize the parameters of two-degree-of-freedom proportional integral derivative controller (2dof-PID) for load frequency control of multi-microgrid (MG) system. The multi-MG contains power pool of photovoltaic (PV), wind turbine (WTG) and diesel engine generator along with different energy storage devices like battery energy storage system and flywheel energy storage system. The frequency control problem under the influence of stochastic disturbance condition is formulated as an optimization problem, and hDA-PS is implemented to search for the optimal controller parameters. To demonstrate the supremacy of the proposed 2dof-PID controller, the performances of 2dof-PID controller are compared with conventional PID and PI controllers. A comparative study with particle swarm optimization, genetic algorithm and dragonfly algorithm is done to justify supremacy of hDA-PS algorithm. [ABSTRACT FROM AUTHOR]

This article discusses a Whale Optimization (WO) controller for design analysis, stability management, application, and performance analysis of a deregulated two-area multi-source energy system. Within the power grid, the Automatic Generation Control (AGC) maintains the power balance and strengthens the sudden frequency disturbance of the grid. Various researchers are targeted many kinds of fast-acting energy-storing devices to dampen space frequency oscillations and diversion of the tie line because of unexpected load variation. To regulate the power flow between multi-areas, load frequency control (LFC) is used by keeping frequency constant. But, to design a controller for minimizing the issues of LFC remains a challenge within the deregulated atmosphere. The main objective of the proposed methodology is to design a controller for minimizing the issues in LFC within the deregulated atmosphere. A two-area deregulated hydrothermal power system is employed to analyze many LFC problems in the deregulated power grid. During this modeling, the Thyristor-Controlled Phase Shifters (TCPS) and Capacitive Energy Storage unit (CES) are placed in the tie line and its control space. To mitigate the various issues of LFC in a two-area deregulated hydrothermal power system, the CES–TCPS combination is placed between the two control areas and the transient performance of constant is evaluated. The WO controller will increase the system power size to focus on the better performance of low-frequency management tasks. In addition, the effectiveness of the WO algorithm in tuning the proportional integral controller is also compared in a different contract (unilateral, bilateral and contract violation cases) scenarios of the proposed deregulated power system. Finally, the simulation is carried out in MATLAB/Simulink platform and the results obtained for the WO controller is compared with the normal and fuzzy PI controllers. [ABSTRACT FROM AUTHOR]

Recent improvements in communications have led to the proliferation of networked control systems (NCSs). NCSs are used to increase the efficiency and reliability of these systems. However, these connectivities between agents, sensors, and centralized controllers expose NCSs to a range of faults, failures, delays, and cyber-attacks. Detection of intelligent and new types of attacks such as time delay switched (TDS) attacks is a crucial task in the design of NCSs. The injection of the TDS attack to NCSs has the potential to provoke inefficiency or even cause instability in these systems. The TDS or delay signal attack influences the system by introducing a random delay in the process of transmitting and receiving packets. Due to the connectivity between agents, especially in distributed power grids, the injection of a TDS attack on one agent can propagate to others, which can lead to catastrophic consequences. This paper uses a neural networked-based detection algorithm to estimate the TDS attack in real-time. The performance of the proposed TDS attack detection and estimation are evaluated through simulation for two area power systems. [ABSTRACT FROM AUTHOR]

The work puts an earliest effort to compare the performances of different fractional order based feed-forward type two degree of freedom (2DOF-FO) controllers optimized with Grasshopper optimization algorithm (GOA) for the study of load frequency control in interconnected system. As fractional order controllers (FOC) are gaining attention of researchers over integer order controller (IOC) in recent era, so the authors' main motive in this article is to highlight a comparative performance analysis between three different structures of feed-forward type 2DOF-FOC namely 2DOF-FO-proportional-integral-derivative (2DOF-FOPID), 2DOF-FO-integral-derivative (2DOF-FOID) and 2DOF-FOPI. These controllers are optimally designed through GOA technique. The 2DOF-FOPID controller ensured as the best one over other two controllers in GOA framework even in the presence of nonlinearities for a two area and three areas thermal system. Also, the robustness of the controllers is verified for two area system by applying different physical conditions like a random pattern of step load variations, changing the loading condition in area-1 and the system parameters within a range of ± 20%. [ABSTRACT FROM AUTHOR]

Load frequency control (LFC) is considered as one of the most important frequency-related ancillary services in a deregulated power system. In this present work, the effect of inclusion of superconducting magnetic energy storage (SMES) system along with thyristor controlled series compensator (TCSC) in a three-area deregulated power system for mitigating the various frequency-related issues in a deregulated power system is examined. For investigating the various LFC issues, optimal gain settings of the PI controllers in each area are obtained by genetic algorithm-based performance indices. The test system simulations under MATLAB/Simulink validate that inclusion of SMES–TCSC combination effectively damps out the frequency and tie-line power oscillations in an interconnected deregulated power system under three different types of contract scenarios. [ABSTRACT FROM AUTHOR]

This paper establishes an observer-based finite-time non-fragile load frequency control design using electric vehicles for power systems with modeling uncertainties and external disturbances. A state space representation of the addressed power systems together with dynamic interactions of electric vehicles is formulated. A full-order observer-based non-fragile controller is designed to ensure finite-time boundedness and satisfactory finite-time H ∞ performance of the considered system. By constructing an augmented Lyapunov–Krasovskii functional and employing Wirtinger-based integral inequality, the required conditions are obtained in terms of linear matrix inequalities. The desired non-fragile load frequency control law is presented via the observer-based feedback approach. Simulations are given to show the effectiveness of the proposed control scheme. • A load frequency controller with multiple time delays is proposed for power systems. • The proposed method does not require any information on states of the power system. • Delay-dependent stability criterion is developed for the resulting closed-loop system. [ABSTRACT FROM AUTHOR]

Abstract This paper proposes optimal load frequency control (LFC) designed by Adaptive Neuro Fuzzy Inference System (ANFIS) trained via antlion optimizer (ALO) for multi-interconnected system comprising renewable energy sources (RESs). Two systems are modeled and investigated; the first one has two plants of grid connected photovoltaic (PV) system with maximum power point tracker (MPPT) and thermal plant while the second comprises four plants of thermal, wind turbine and grid connected PV systems. ALO is employed to get the optimal gains of Proportional–Integral (PI) controller such that the integral time absolute error (ITAE) of frequency and tie line power deviations is minimized. The input and output of the optimized PI controller are used to train the ANFIS-LFC with Gaussian surface membership functions. Different load disturbances are studied and the results are compared with other reported approaches. The obtained results confirmed the accuracy and reliability of the proposed approach in designing LFC for multi-interconnected power systems. Highlights • ALO is proposed for training ANFIS for simulating LFC installed in multi-interconnected areas with RESs. • The proposed objective function is ITAE of frequencies and tie line power deviations. • Gaussian surface membership functions are presented for ANFIS-LFC. • Sensitivity analysis of the system parameters and load disturbances are studied. • The results confirmed the quality and reliability of the proposed approach in designing LFC. [ABSTRACT FROM AUTHOR]

• A SCGAC-LFC method is proposed to obtain a coordinated LFC policy. • A CMA-DMAC is proposed to achieve fast collaborative multi-task learning. • Online application of the method does not require communication between units. • The proposed method boasts lower frequency deviation and mileage payment. In a sustainable city with a large amount of renewable energy, the difficulty inherent in the coordination of the load frequency control strategies of grid units and area units lead to severe frequency fluctuations. Conventional load frequency control has difficulty overcoming the above problems due to its lack of adaptive control ability and robustness. To overcome this problem, this paper proposes a sea computing-based grid-area coordinated load frequency control (SCGAC-LFC) method, which equates each grid unit and area unit in each area as independent agents. Instead of different units relying on different strategies, all units collectively obtain the LFC policy that suits the market requirements. In its online application, no communication is needed since each unit can arrive at its own decision. In addition, this paper proposes a curriculum multiagent deep meta-actor-critic (CMA-DMAC) algorithm, which introduces meta-reinforcement learning and curriculum learning to guide the agent training to improve the robustness and quality of the obtained SCGAC-LFC strategies. Using a simulation of the four-area LFC model for the China Southern Grid (CSG), our proposed method carries significantly lower frequency error and regulation mileage payment. [ABSTRACT FROM AUTHOR]

Abstract This paper presents Modified Active Disturbance Rejection Control (MADRC) scheme and a systematic procedure to tune its tuning variables via. observer and controller gains. The problem of tuning is formulated as a constrained multi-objective optimization problem. Depending upon the application appropriate objective functions are chosen, and a unified objective is developed based on weighted sum approach. Five different weight combinations are considered, which result in five objective functions. Each objective function is individually optimized using Teaching-Learning Based Optimization (TLBO), this leads to five sets of tuning variables. Best among five alternatives will be selected based on Analytical Hierarchy Process (AHP). The effectiveness of this approach is validated through its application to a power system with load frequency control problems. Different simulation examples involving single-area and multi-area power systems are considered in the presence of sudden load disturbances, model uncertainties, and parameter variations. Further stability analyses are carried out in a standard two-degree of freedom Internal Model Control (IMC) framework. Highlights • Design of MADRC involving model assisted ESO and state feedback control law. • New tuning procedure for obtaining optimal parameters ω0 and ωc for fast estimation and improved performance. • Efficacy of the proposed method is validated through its application on single area and multi-area power system models. • Stability analysis of the proposed scheme is carried out in a standard two-degree of freedom Internal Model Control scheme. [ABSTRACT FROM AUTHOR]

This paper introduces a new powerful evolutionary algorithm called backtracking search algorithm (BSA) for solving load frequency control (LFC) problem in power system. Initially, two-area non-reheat thermal power plant is considered and gains of PI/PID controllers are optimized using BSA. This paper compares BSA’s effectiveness in solving LFC problem with the performances of other optimization techniques reported in the literature. Nonlinearities of power system such as reheater, governor dead band, boiler dynamics and generation rate constraint are included in the system modeling to identify the system stability and its performance is compared with craziness based PSO technique. Additionally, two more test systems namely three-area and four-area hydro-thermal plant with nonlinearity are considered to demonstrate the efficiency of proposed algorithm. The comparative analysis of the performances indicates that the proposed controller gives better results than other techniques available in the literature. Sensitivity analysis showed robustness of proposed controller under loading and parameter uncertainty. [ABSTRACT FROM AUTHOR]

In this paper, a hybrid algorithm is developed by incorporating the egg-laying and immigration mechanisms of cuckoo optimization algorithm (COA) into harmony search (HS) algorithm (HSCOA), to design a secondary controller for two practical models of load frequency control (LFC) problem. Initially, a two-area non-reheat thermal power system is considered and the gains of PID and fuzzy PI/PID controllers are adjusted by the proposed tuning method. The superiority of HSCOA in regulating controller gains is demonstrated by evaluation and comparison of the obtained transient outcomes over some other published approaches in literature. To prove the satisfaction of the robustness in designed LFC by means of the proposed method, the performance of HSCOA based fuzzy PID controller is extensively verified under varying loading condition and some critical parameters related to the considered power plant. To add further practical challenge, the governor dead band (GDB) is included in the concerned system modeling to study the advantages of the HSCOA tuned fuzzy PID controller in handling the properties of nonlinearity in the system model. Time domain simulation of transient responses indicates that the designed controller operates satisfactorily to deal with the GDB nonlinearity and outperform other published techniques. Furthermore, to demonstrate the effective feasibility of the proposed method, the study is extended to a two-area multi-source power system with/without consideration of HVDC link. It is observed that HSCOA optimized fuzzy PID controller gives superior quality outcomes in comparison to other reported strategies. Finally, the robustness of the controller’s gains designed for the concerned power system is investigated under various scenarios of change in size, location and pattern of step load perturbation. [ABSTRACT FROM AUTHOR]

In this paper, a robust Fractional Order PI λ D controller that contains an integral fraction action and a simple filtered derivative action, is investigated on Automatic Generation Control (AGC) of a three areas reheat-thermal system. For more realistic study some nonlinear constraints have been introduced such as Governor Dead Band (GDB), Generation Rate Constraints (GRC) and boiler dynamics. The optimal controller parameters are tuned through new evolutionary algorithm known as Differential Evolution (DE) algorithm by minimizing the Integral of Squared Error (ISE) index. Obtained results reveal clearly the superiority of the investigated controller compared to the other controllers such as PID, PID μ and PI λ D μ in terms of the performance index, peak overshoots, peak undershoots and settling time. Effectiveness and rapidity of the DE algorithm in the convergence have been shown and compared to Genetic Algorithm (GA). Finally, robustness analysis against higher degree of load disturbance and sever parametric variation demonstrates the effectiveness of the investigated controller. [ABSTRACT FROM AUTHOR]

The low inertia of electrical power networks as renewable energy penetration levels increase is regarded as a significant issue confronting worldwide ambitions for the anticipated renewable energy transition. Load frequency control (LFC) is an efficient way of improving the frequency stability and dependability of renewable energy-based power networks. Therefore, this paper introduces a novel three-degree-of-freedom (3 DoF) load frequency control method for two-area-linked power systems. To implement the suggested LFC approach, the proposed control employs an enhanced hybrid fractional order control method (namely FOTPID), and the tilt integrator differentiator with filter (TIDF) is employed in the frequency deviation and tie-line power loop feedforward compensation. As a consequence, this study proposes a novel 3DoF cascaded FOTPID-TIDF controller. Furthermore, this work proposes a modified method of the recently developed Manta-Ray Foraging Optimizer (MRFO) to optimize the parameters of the new suggested 3DoF cascaded FOTPID-TIDF controller. The paper includes extensive performance comparisons and discussions to validate the superior performance metrics of the new proposed control and optimization methods. The results reveal that by taking into account the characteristics and uncertainties of renewable sources, interconnected loads, and grid inertia, the results perfectly mitigate various existing deviations in frequency and tie-line power compared to existing contemporary LFC approaches. [ABSTRACT FROM AUTHOR]

Frequency instability has been a growing problem in recent years due to the rising penetration of distributed generating systems in the format of Microgrids (MGs), which are powered by renewable energy sources (RESs) with an unpredictable nature. The provision of an effective load frequency control (LFC) to an MG model under such conditions contributes significantly to the restoration regarding the unconfigured power system's stability. An MG structure is employed, which combines renewable energy sources like solar and wind, as well as biologically renewable sustainable energy sources like wastewater, agricultural and domestic wastes, and contains appropriate battery systems and is suited to achieve both energy and waste control in this study. In addition, redox flow battery (RFB), an innovative battery storage system with a fast dynamic response in this MG structure, has been considered as one of the energy storage devices. A nonlinear integral backstepping (NIB) controller is adopted to stabilize the frequency deviation of the integrated MG system with RFB under various level of load disturbances and randomness of RESs. In particular, a spike neural network (SNN) based on neuromorphic platform is proposed to adjust the coefficients of NIB controller. Furthermore, real time analyses are performed with OPAL-RT to validate the feasibility of the proposed strategy from a systematical viewpoint. As a result of this study, the proposed controller for load disturbance, RES power changes, and contingency circumstances in bio renewable MG is determined to be flexible enough to satisfy the efficient frequency regulation for these grids. • The real-time viability of the proposed approach is evaluated using OPAL-RT based real-time assessments. • A novel spike neural network based nonlinear integral backstepping-model free controller is developed in this research. • The microgrid structure included bio-renewable generation system and renewable energy sources is used in this study. [ABSTRACT FROM AUTHOR]

In this paper, a gain scheduling technique using type-2 fuzzy logic system has been proposed for load frequency control in restructure power system. For this purpose, at first the particle swarm optimization algorithm has been employed to obtain proportional-integral-derivative controller gains at some nominal operating points; then, a multi-input multi-output type-2 fuzzy logic system is trained in order to provide a general mapping between the operating points and the related proportional-integral-derivative gains. In addition, the same particle swarm optimization algorithm has been used to train the multi-input multi-output type-2 fuzzy logic system. In the online applications, the trained type-2 fuzzy logic system is able to infer the proportional-integral-derivative gains appropriately even in the presence of noise and uncertainties. So, the type-2 fuzzy logic system is exploited due to its ability to model uncertainties which may exist in the rules and measured data. To illustrate the effectiveness of the proposed strategy, the new controller has been compared with a type-1 fuzzy gain scheduling and the proportional-integral-derivative controllers. [ABSTRACT FROM AUTHOR]

The increase of power demand exponentially over the past decade in developing countries has necessitated the integration of different types of renewable energy sources into the utiligy grids which were earlier running with fossil fuel fired units. Renewable energy sources are integrated with these generating plants since it is economical and pollution free. Power generation through these types of generating plants comprise of a combination of intermittent renewable sources like wind, solar and other generating sources like diesel generators, fuel cells. Also, because of the weak inertial nature of the renewable sources used in microgrid, it is much more important to regulate the system frequency closer to the nominal values. This paper explores the development of an Internal Model based controller approach for better frequency regulation in a hybrid microgrid. Two different cases are examined to validate the robustness of IMC based controller design. [ABSTRACT FROM AUTHOR]

This paper proposes a distributed model predictive control based load frequency control (MPC-LFC) scheme to improve control performances in the frequency regulation of power system. In order to reduce the computational burden in the rolling optimization with a sufficiently large prediction horizon, the orthonormal Laguerre functions are utilized to approximate the predicted control trajectory. The closed-loop stability of the proposed MPC scheme is achieved by adding a terminal equality constraint to the online quadratic optimization and taking the cost function as the Lyapunov function. Furthermore, the treatments of some typical constraints in load frequency control have been studied based on the specific Laguerre-based formulations. Simulations have been conducted in two different interconnected power systems to validate the effectiveness of the proposed distributed MPC-LFC as well as its superiority over the comparative methods. [ABSTRACT FROM AUTHOR]

The present work approaches a relatively new optimization scheme called “quasi-oppositional symbiotic organism search (QOSOS) algorithm”, for the first time, to find an optimal and effective solution for load frequency control (LFC) problem of the power system. The symbiotic organism search (SOS) algorithm works on the effect of symbiotic interaction strategies adopted by an organism to survive and propagate in the ecosystem. To avoid the suboptimal solution and to accelerate the convergence speed, the theory of quasi-oppositional based learning (Q-OBL) is integrated with original SOS and used to solve the LFC problem. To demonstrate the effectiveness of QOSOS algorithm, two-area interconnected power system with nonlinearity effect of governor dead band and generation rate constraint is considered at the first instant, followed by the four-area power system showing the consequence of load perturbation. The structural simplicity, robust performance and acceptability of well-popular proportional-integral-derivative (PID) controller enforce to implement it as a secondary controller for the present analysis. The success of QOSOS algorithm is established by comparing the dynamic performances of concerned power system with those obtained by some recently published algorithms available in the literature. Furthermore, the robustness and sensitivity are analyzed for the concerned power system to judge the efficacy of the proposed QOSOS approach. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the implementation of Proportional-Integral-Observer(PI-Observer) based state feedback control for Load Frequency of single area isolated power system model. The general application of PI-Observer has been realized in areas of robotic and mechanical system. The PI-Observer is used to estimate both the original states and the unknown inputs generally disturbances, modeling errors or the other non-linearities present in the system. The estimation error of the PI-Observer is gradually reduced by the proportional and integral feedback loop that appreciably improves the observer dynamics. A single area linear power system model is taken as a test case to implement the proposed methodology which is then compared with full state Luenberger observer based state feedback control for load frequency control of power system. MATLAB/SIMULINK is extensively used for modeling & simulation of power system and observer. The dynamic responses are compared and discussed on the basis of error dynamics, system states, peak overshoot and settling time. Lastly it was found that response of PI-observer based state feedback control scheme is quite appreciable as compared to Luenberger observer based state feedback schemes. [ABSTRACT FROM AUTHOR]

Deciding the correct offensive security strategy for safeguarding the electrical physical infrastructures of smart grids is a challenging task. The offensive security training against various cyber-attacks focuses on a multitude of electrical subsystems and measurement systems like the Load Frequency Control(LFC) system. Primarily, the principal challenge is to categorize and parameterize the various possible cyber-attacks on electrical infrastructures. This is done by specifying and selecting cyber-attacks considering various main and subsystem blocks of the power structural system within each area of major installations. In this research investigation, formal modeling of security strategy is proposed using Lambda calculus with both classical and quantum perspectives. Furthermore, using a Quantum Machine Learning (QML) technique, the procedure for correct vulnerability prediction, exploitation, and execution strategy is presented with an approximated likelihood of attack and its mode. The local and non-local interactions are introduced as quantum threats and entanglement threats similar to False Data Injection (FDI) methods to induce the attack and counter-attack events through quantum causality connections. Finally, the Quirk simulator is used to validate the proposed quantum design of offensive and defensive attack models considering scenarios of exogenous and scaling attacks on the LFC systems that support the feasibility of the present research work to address the issue of cyber-attacks on the power system networks. • In this research investigation, a formal modeling of security strategy is proposed using Lambda calculus with both classical and quantum perspectives. • Furthermore, using a quantum machine learning technique, the procedure for correct vulnerability prediction, exploitation, and execution strategy is presented with an approximated likelihood of attack and its mode. The local and non-local interactions are introduced as quantum threats and entanglement threats similar to false data injection (FDI) methods to induce the attack and counter-attack events through quantum causality connections. • Finally, the Quirk simulator is used to validate the proposed quantum design of offensive and defensive attack models considering scenarios of exogenous and scaling attacks on LFC system that support the feasibility of the present research work to address the issue of cyber-attacks on the power system networks. [ABSTRACT FROM AUTHOR]

With the continuous increase in the load, the frequency of the system goes on decreasing and it reaches to its minimum allowable value after the further increase in load will result in more frequent drop resulting in the need of load shedding. To avoid load shedding and control of the frequency of the systems some approach have discussed here. The paper includes modeling of SMES with solar PV array for frequency control of three areas interconnected thermal system in deregulated environment. A comparative analysis of different load frequency control scheme such as: i) Using conventional integral controller ii) Using PID controller, iii) Using additional sources of energy (PV with SMES) on the basis of load to be shed have been discussed. The effects of bilateral contracts on the dynamics of a system including three areas, each of which consisting of two GENCOS and two Discos has been discussed. A case study of contract violation of DISCO‘s also being incorporated. For all the three strategies the critical load at which frequency of the areas tries to go below minimum allowable range also has been calculated. With the help of MATLAB software using Simulink, results have been obtained. From the comparison results indicates that on using the third strategy (with additional sources) we are increasing the efficiency of the system. When using system with PID controller and additional sources, frequency of the system doesn’t go below minimum allowable range and there is requirement of load shedding has been eliminated. [ABSTRACT FROM AUTHOR]

In this paper, a multivariable model based predictive control (MPC) is proposed for the solution of load frequency control (LFC) in a multi-area interconnected power system. The proposed controller is designed to consider time delay, generation rate constraint and multivariable nature of the LFC system, simultaneously. A new formulation of the MPC is presented to compensate time delay. The generation rate constraint is considered by employing a constrained MPC and economic allocation of the generation is further guaranteed by an innovative modification in the predictive control objective function. The effectiveness of proposed scheme is verified through time-based simulations on the standard 39-bus test system and the responses are then compared with the proportional-integral controller. The evaluation of the results reveals that the proposed control scheme offers satisfactory performance with fast responses. [ABSTRACT FROM AUTHOR]

Load frequency control is an essential component of Automatic Generation Control of power systems. Deregulated power system isa highly complex and uncertain system because of multiple bilateral transactions taking place. This necessitates the use of advanced robust controllers for load frequency control. A decentralized load frequency controller using H-infinity based loop-shaping method is suggested for a two area deregulated non-reheat thermal power system in this paper. The connections between each control area with the rest of the system as well as the contracts existing in a deregulated system are treated as input disturbance signals to achieve decentralization. Dynamic responses for three contract cases of operation in a deregulated system using the H-infinity controller are obtained. [ABSTRACT FROM AUTHOR]

The high penetration of renewable energy sources in power systems will deteriorate power quality and affect frequency stability. This issue is more severe in a small-capacity area or island power system that is weakly linked to the main grid. For the deviations of frequency and tie-line power exchange in power systems with multi-source generation units, we proposed a new robust control strategy based on linear quadratic soft-constrained differential games theory to reduce the influence from variations of wind farms output. The results of simulation testify its effect and robustness. [ABSTRACT FROM AUTHOR]

With the continuous increase in the load, the frequency of the system goes on decreasing and it reaches to its minimum allowable value after the further increase in load will result in more frequent drop resulting in the need of load shedding. To avoid load shedding and control of the frequency of the systems some approach have discussed here. The paper includes modeling of SMES with solar PV array for frequency control of three areas interconnected thermal system in deregulated environment. A comparative analysis of different load frequency control scheme such as: i) Using conventional integral controller ii) Using PID controller, iii) Using additional sources of energy (PV with SMES) on the basis of load to be shed have been discussed. The effects of bilateral contracts on the dynamics of a system including three areas, each of which consisting of two GENCOS and two Discos has been discussed. A case study of contract violation of DISCO‘s also being incorporated. For all the three strategies the critical load at which frequency of the areas tries to go below minimum allowable range also has been calculated. With the help of MATLAB software using Simulink, results have been obtained. From the comparison results indicates that on using the third strategy (with additional sources) we are increasing the efficiency of the system. When using system with PID controller and additional sources, frequency of the system doesn’t go below minimum allowable range and there is requirement of load shedding has been eliminated. [ABSTRACT FROM AUTHOR]