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ABSTRACT The paper proposes a novel model‐free adaptive robust controller for load frequency control in multi‐area interconnected power systems. The controller combines model‐free control based on a nonlinear disturbance observer (NDOB) and adaptive integral sliding mode control. The main aim of the controller is to maintain the power system frequency close to the nominal value and achieve a balanced power exchange between tie‐lines, considering the system's nonlinearities and disturbances. The proposed controller comprises four components. First, model‐free intelligent PID control is implemented to overcome the complexity of the current controller, introduce the required dynamics, and reduce higher‐order output derivatives. Second, a nonlinear disturbance observer is utilized to estimate the system dynamics considering uncertainties and load fluctuations. Third, fast convergence is achieved by employing an integral sliding surface. Finally, an adaptation gain dynamic is used to achieve high accuracy. The advantage of the proposed model‐free adaptive robust controller lies in its simple structure and ease of regulation. The closed‐loop system's stability and finite‐time convergence are examined using Lyapunov stability theory. A comparison with recently published papers is conducted to validate the proposed controller's effectiveness. Additionally, robustness testing of the proposed method is performed in different scenarios. [ABSTRACT FROM AUTHOR]

The penetration of offshore wind farms (OWFs) in city‐close power systems is rapidly increasing. System inertia will be further reduced. Active frequency support of wind power is essential to solve the load frequency control (LFC) problem. Here, the dynamic virtual inertia control (VIC) method is employed to enhance frequency stability within the permitted operating states of OWFs. An adaptive distributed model predictive control (DMPC) method is proposed and applied to an interconnected power system. The dynamic VIC‐based LFC model is derived and used to construct the predictive model of DMPC. To expand the adaptation of the analytical linearized model of OWFs in different operating points, the adaptive law is further designed to dynamically adjust the parameters of DMPC. The simulation results demonstrate the effectiveness of the proposed control method. The frequency fluctuations can be well‐restrained under different disturbances. [ABSTRACT FROM AUTHOR]

ABSTRACTRenewable generation plays an important part in today's power system. With the inclusion of the inverter interfaced renewable energy sources (RESs) into a microgrid, the total system inertia decreases and it leads to increased frequency deviation in presence of a disturbance. This paper proposes a cascaded Integral Minus Tilt Integral Derivative with Filter (I–TDN)‐Proportional‐Integral (PI), [(I‐TDN)‐PI] controller for frequency stabilization of a hybrid microgrid in presence of electric vehicles (EV). The microgrid model includes reheated thermal power plant with high degree of non‐linear system such as inverter based RESs like photovoltaic and wind generation systems. A diesel engine generator is incorporated for load frequency control during perturbation in the system frequency. Virtual inertia controller (VIC) with inverter based energy storage system (ESS) is commonly used to improve system inertia and frequency stability of the microgrid. In addition to the ESS, this paper proposes inclusion of the EVs in this VIC. The optimal gains of the proposed cascaded I‐TDN‐PI controller are determined using Mountain Gazelle Optimizer (MGO), a modern metaheuristic optimization algorithm. Sensitivity of the proposed controller is investigated in presence of system nonlinearities, load perturbations, time delay, system parameter variation and RES power fluctuations. The simulation results justify the robustness of the proposed control structure for frequency stabilization of the microgrid. [ABSTRACT FROM AUTHOR]

In the paper, the maiden application of Tilted Integral Fractional Derivative with Filter plus Fractional Derivative controller (TIDμ1NDμ2$TI{D^{{\mu _1}}}N{D^{{\mu _2}}}$), called TIFDNFD controller, is proposed to achieve load frequency control (LFC) of two area‐multi source power system. In the study, both areas include thermal power, hydropower, and gas turbine power systems. In this study, generation rate constraint and governor dead‐band are integrated into the power system to evaluate the performance of the controller in a non‐linear environment. The wild horse optimizer (WHO) is used for controller parameter tuning in the LFC problem for the first time. The performance of the proposed controller is demonstrated by comparing it with the recently published studies including different controllers. In this study, to obtain more realistic results, solar photovoltaic (PV) power, wind power, and load demand with stochastic form have been added to the power system. In addition, the dynamic effect of the hydrogen storage system, consisting of an electrolyser and a fuel cell, is considered a grid supporter. The superiority of the WHO algorithm in optimization has been verified by comparing it with three optimization algorithms recently proposed. Finally, the resilience and robustness of the power system are evaluated in perturbed system parameters. [ABSTRACT FROM AUTHOR]

Load variation, distributed power output uncertainty and multi‐microgrids network complexity have brought great difficulties to the frequency stability of the whole microgrid. To address this problem, this paper uses a multi‐agent deep reinforcement learning(DRL) algorithm to design the controllers to control the frequency of the multi‐microgrids. Firstly, a load frequency control (LFC) model for multi‐microgrids was built. Secondly, based on the centralized training and decentralized execution (CTDE) multi‐agent reinforcement learning (RL) framework, the multi‐agent soft actor‐critic (MASAC) algorithm was designed and applied to the multi‐microgrids model. The state space and action space of multi‐agent were established according to the frequency deviation of every sub‐microgrid and the output of each distributed power source. The reward function was then established according to the frequency deviation. The appropriate neural network and training parameters were selected to generate the interconnected microgrid controllers through multiple training of pre‐learning. Finally, the simulation study shows that the MASAC controller proposed in this paper can quickly maintain frequency stability when the system is disturbed. Sensitivity analysis shows that the MASAC controller can effectively cope with the uncertainty of the system parameters. [ABSTRACT FROM AUTHOR]

This paper proposes a hybrid technique for load frequency control (LFC) in an inter‐connected deregulated power‐system. The proposed method is the combination of a gannet optimization algorithm (GOA) and spiking neural network (SNN), hence, it is named as GOA‐SNN technique. The objective of the proposed method is to minimize frequency deviations within the power system (PS). By lessening the frequency‐deviation and tie‐line power variation, this approach ensures system frequency‐control under the effect of load disturbances. The GOA method is utilized to generate the set of control signals of the controller. The SNN method is used to predict the optimum gain parameter of the controller. By then the proposed method is run in MATLAB software and evaluated their performance with various existing approaches. The proposed method shows better results than other existing methods, such as Ant Lion Optimization (ALO), particle swarm optimization (PSO), and Salp Swarm Algorithm (SSA). The GOA‐SNN approach shows a low Area control error is 0.48% and a high efficiency is 96% compared with other existing approaches. [ABSTRACT FROM AUTHOR]

In today's electrical grid, frequency cannot be ignored. The proliferation of renewable energy sources into a power system degrades its frequency; hence, the need for frequency regulation has been increased as a result. The second major factor is the perturbation in the load that originates the frequency fluctuation which needs to be suppressed in minimum time to avoid any system collapse. The designing of an optimal controller is indispensable because of increasing power system complexity. In order to maintain the stability of the power system, this paper presents the cascaded design of the model predictive controller with fractional order PID controller (MPC‐FOPIDN) to mitigate the frequency oscillations due to disruption in load. The combination of the predictive capabilities of model predictive control (MPC) and fractional order control enhances control abilities, making it an optimal control strategy for load frequency control (LFC). The grasshopper optimization algorithm (GOA) is applied to obtain optimal gains values for the FOPID controller. The efficacy of the controller has effectively mitigated frequency fluctuations caused by a change in demand or any uncertainty in the power system. [ABSTRACT FROM AUTHOR]

In regards to present power system setup, this article presents a frequency stabilization of hybrid power system (HPS) assimilated with distributed generation (DG) resources, conventional thermal, geo‐thermal and electric vehicle (EV). The insertion of appropriate system non‐linearities in addition to the intermittency in renewable based generation sources leads to a more practicality into the developed HPS. For such systems, a vigorous control action with swift responding controllable device are an instantaneous requirement. In this view, a cascaded fractional order proportional‐derivative (foPD)‐multi‐stage fractional order proportional integral derivative (MSfoPID) (cascaded foPD‐MSfoPID) as secondary controller is explored for frequency stabilization of HPS. Further, the established power system is provided with erratic load deviations. The influence of EVs on frequency and tie‐line power fluctuations are examined comprehensively. Moreover, the outcome of unified power flow controller (UPFC) device as flexible AC transmission system (FACT) device for system dynamic control are illustrated. Further, sensitivity examination is exhibited to examine the resiliency of proposed cascaded foPD‐MSfoPID controller parameters for deviances in solar irradiance and number of vehicles. Finally, a proposed secondary controller is tested in case studies on standard IEEE‐39 bus system and four‐area hybrid power system. [ABSTRACT FROM AUTHOR]

Although there have already been many works on the model predictive control (MPC) for load frequency control (LFC) of modern power systems, limited works can be found in the literature related to the output feedback MPC. This article studies an N‐step synthesis approach of output feedback MPC for LFC systems considering the problems of communication efficiency and network security. First, to improve the communication efficiency, an adaptive event‐triggering (AET) scheme involving two adaptive laws is designed to reduce the number of transmitted data packages which offers more flexible compared with existing event‐triggering schemes; Second, to handle the network security, a new model of LFC power system combining the AET scheme and random deception attack under an unified framework is established; Moreover, a synthesis approach of output feedback MPC with N‐step strategy is addressed for LFC of power system by parameterizing the infinite control moves into a series of output feedback laws. Compared with the existing predictive load frequency control methods, the present technique is shown as an useful way to improve the control performance since more degrees freedom is introduced by the N‐step strategy. Finally, the simulation experiment is carried out to verify our technique. [ABSTRACT FROM AUTHOR]

This paper proposes a novel load frequency control (LFC) strategy for power systems based on distributed model‐free adaptive predictive control. First, a power system dynamic model is established by the input and output signals of the power system. Then, a distributed model‐free adaptive predictive control algorithm is established for the power system under denial‐of‐service attack by the established power system dynamic model, and a predictive compensation algorithm is designed to compensate the impact of DoS attack. Based on the designed distributed model‐free adaptive predictive control algorithm, the frequency tracking error of the multiarea power system is bounded. The scheme is independent of the structure of the power system and does not need to measure any state signals of the power system, relying only on the input and output data of the power system. The results of simulations demonstrate the effectiveness and superiority of the design. [ABSTRACT FROM AUTHOR]

Significant number of renewable sources when integrated with distributed generations and energy storage components form a sustainable power system called hybrid power system (HPS). But the stochastic nature of the sources and continuous variation of load cause serious issues in the power systems like frequency instability. Our work proposes a novel approach for load frequency control (LFC) of the proposed system. For the work, both frequency deviation and control signal are used to give the input signal to energy storage components. A new fuzzy‐based controller called fractional order fuzzy precompensated PDPI (FO‐FPPDPI) controller for LFC of the mentioned HPS is suggested in this paper. The controller is optimized by a nature inspired multi‐objective salp swarm algorithm (MSSA). The comparison of the proposed approach with the classical PID controller and Fuzzy PID (FPID) controller is carried out by taking several system operating conditions. Robustness of the FO‐FPPDPI controller is also validated for system parameter variations and the superiority of the proposed control strategy over PID and FPID controllers is validated for all the situations. Finally, the control strategy is realized in OPAL‐RT to measure its fidelity with the simulation results. [ABSTRACT FROM AUTHOR]

This article presents a novel load frequency control (LFC) approach using colliding bodies optimizer (CBO) for frequency stabilization of interlinked multiarea electric power systems. The optimal parameters of the suggested CBO‐based proportional–integral–derivative‐filter controller ascertain an effective LFC solution. First, a well‐known and widely used linearized two‐area nonreheated thermal power system is examined to demonstrate the efficacy of the proposed approach. The effectiveness of the proposed method is analyzed by comparing the outcomes of several recently presented LFC schemes. The performance analysis shows a settling time improvement of 3.10%, 14.29%, and 18.66% in the case of area‐1 and area‐2 frequencies and tie‐line power deviations compared with an imperialist competitive algorithm (ICA)‐based controller. The robustness of the proposed scheme is also evaluated in the presence of various operating scenarios. Additionally, the work is extended to a two‐area nonreheated hydrothermal power system. The proposed method shows an improvement of over 60% in the performance index compared with several existing techniques‐based controllers such as optics‐inspired optimization, gray‐wolf optimization, quasi‐oppositional differential search algorithm, bacterial foraging optimization algorithm, and ICA. [ABSTRACT FROM AUTHOR]

The constant changes in the load power lead permanently to a power mismatch between the power generation and the power consumption. So, the system frequency due to the power imbalance deviates from the nominal value. Consequently, a control loop should be implemented to stabilize the system frequency whenever a load change occurs. This paper presents a new super‐twisting sliding mode control methodology for obtaining an optimal frequency performance in a multi‐pool system. The paper presents a three‐pool system for frequency deviation problems using an optimal gain Super Twisting Sliding Mode Controller (STSMC), which regulates the frequency change and the line power change to zero in a minimal time. The extent of the excellence of the study proposed is evaluated by comparing it with three Benchmark classical controllers, which are the Tilt‐Integral‐Derivative (TID), Proportional‐Integral‐Derivative (PID), and Fractional‐Order PID (FOPID). The parameters of the four controllers are determined by a proposed physical meta‐heuristic optimization technique called Transient Search Optimizer (TSO), inspired by the dynamic behaviour in the electrical circuits comprising storage elements such as capacitors and inductors during the switching actions. The system simulation is performed, and the STSMC proved overwhelming superiority over other controllers, as it deals better with the transient interval of the system response. Renewable Energy sources (RESs) like photovoltaic and wind energy systems are established, and the STSMC is tested with industrial and residential load models. Finally, energy storage devices such as batteries and superconducting magnetic energy storage are implemented to suppress the rapid fluctuations in the system response, and it succeeded in doing that as the system oscillations are greatly damped with the energy storage devices. [ABSTRACT FROM AUTHOR]

A load frequency controller is essential to counter load disturbances and minimize unscheduled power flow between interlinked areas of a power system. Hence, this paper proposes a fractional‐order proportional‐integral derivative (FOPID)‐based dual‐loop control approach for load frequency control of multi‐area nonreheated thermal power systems (NRTPS) using teaching–learning optimization (TLO). A stability equation‐based predictive model is used with internal model control in the internal loop of the proposed approach, whereas the external loop contains TLO‐based FOPID controller. The proposed method is tested on two‐area and three‐area NRTPSs under various operating conditions. It is validated from the simulation results that the proposed approach improves the system response substantially compared to the well‐known existing techniques. The robustness of the proposed method is also demonstrated by performing sensitivity analysis with parametric uncertainties, random load disturbances, generation rate constraints, and governor dead zone. [ABSTRACT FROM AUTHOR]

The emergence of micro‐sources in the energy market to reduce carbon emissions and exploit more renewable generations increases the frequency oscillations of the system. Hence, this paper attempts to develop a robust nonlinear fractional order proportional integral derivative (NLFOPID) controller for frequency regulation of restructured energy systems. A hybrid atom search‐particle swarm optimization (AS‐PSO) is proposed to optimize the gain values of the NLFOPID controller. The proposed control approach enhances flexibility by providing robustness against the RE intermittency. The optimization technique is coded in MATLAB and applied for frequency regulation of a multi‐area energy system developed in Simulink. Initially, the effectiveness of the hybrid algorithm is validated for standard benchmark functions and then implemented for frequency control. The results demonstrate that the proffered AS‐PSO technique performs significantly for various types of transactions in a deregulated energy market than state‐of‐the‐art. The real‐time applicability of the proposed controller is validated using hardware‐in‐the‐loop simulation of the open energy market in OPAL‐RT. The frequency response obtained from the AS‐PSO optimized NLFOPID controller is remarkable compared to other techniques. Furthermore, the closed‐loop stability of the system is examined using bode analysis through an improved Oustaloup approximation technique. [ABSTRACT FROM AUTHOR]

This paper proposes a modified optimal control strategy for enhancing the frequency stability of a power grid. The considered grid includes different generation sources and renewable energy distributed in two interconnected areas. This strategy is based on applying a modified control configuration based on two‐degree of freedom for an improved tilt‐integral‐derivative controller entitled (2DOF−TnIλDμN$2{\rm{DOF}} - {{\rm{T}}^{\rm{n}}}{{\rm{I}}^{{\lambda}}}{{\rm{D}}^{{\mu}}}{\rm{N}}$) for load frequency control (LFC). This study considers the effect of the automatic voltage regulator (AVR) and its effect on the frequency stability. The modified 2DOF‐TIλDμ${{\rm{I}}^{{\lambda}}}{{\rm{D}}^{{\mu}}}$ controller is based on utilizing the merits of the two degree of freedom (2‐DOF) structure, and applying the fractional order. Also, an improved gradient‐based optimizer (GBO) is proposed to optimally adjust the gains of the developed control technique. For robust design of the proposed control strategy, the system constraints are considered besides the high renewable power penetration. The effectiveness of the proposed 2DOF−TnIλDμN$2{\rm{DOF}} - {{\rm{T}}^{\rm{n}}}{{\rm{I}}^{{\lambda}}}{{\rm{D}}^{{\mu}}}{\rm{N}}$ controller in LFC has been confirmed by comparing its efficiency with other control strategies' efficiency in previous studies such as modified TID (ITnD), and FO‐PID (PIλDμ${\rm{P}}{{\rm{I}}^{{\lambda}}}{{\rm{D}}^{{\mu}}}$) controllers. Furthermore, in cases of high renewable penetration, the AVR with LFC is superior to conventional LFC in terms of decreasing the value of fluctuations while maintaining voltage and frequency stability. [ABSTRACT FROM AUTHOR]

This article proposes a novel control methodology employing a fractional‐active‐disturbance‐rejection‐controller for the combined operation of load frequency control and automatic voltage regulator of a hybrid power system. A two area hybrid power system with diverse energy sources like solar‐thermal, conventional‐thermal and wind sources equipped with appropriate system nonlinearities is investigated. In order to ascertain the role of modern‐day electric‐vehicle (EV), the hybrid power system is incorporated with EVs in both the areas. To establish an effective frequency, voltage and tie line power control of the hybrid power system, a second order fractional‐active‐disturbance‐rejection‐controller with fractional‐extended state observer is modeled as secondary controller. Magnetotactic‐bacteria‐optimization (MBO) technique is applied to obtain optimal values of the controller gains and the hybrid system parameters. The robustness of the controller gains is tested under different system parameter changes from their nominal values. In addition, the effect of incorporating a power system stabilizer on the hybrid power system is evaluated. Further, the impact of integrating renewable sources and EVs in the hybrid power system is explored. Moreover, the stability of the hybrid power system is monitored with the inclusion of FACTS device. The developed controller operates encouragingly with reference to system stability, rapidity and accuracy in comparison to testified control strategies available in the literature. The robustness test under load‐perturbation, solar‐insolation, wind input variations also proves the efficiency of MBO optimized second order fractional‐active‐disturbance‐rejection‐controller gains. [ABSTRACT FROM AUTHOR]

In recent decades, inclusion of renewable resources is considered as one of the most promising options for the long run uninterrupted power supply without depending on conventional resources. Thus, the renewable energy generation will get more attention and massive growing, so that the goal of 40% share of electricity in the worldwide energy portfolio in 2050 would be realized. But during replacement of renewable energy by conventional energy, engineers are facing a lot of problem due to solar generation, wind generation change their characteristic rapidly with weather condition, which may cause large synchronizing imbalance between different units and generate large system delay or communication delay in large interconnected grid. In this article, the authors propose linear matrix inequalities techniques to developed margin of allowable delay for delay dependent stable hybrid system. Initially, to judge the efficacy of proposed chaotic atomic search optimization (CASO) algorithm over other evolutionary algorithms with PID controller, a thermal‐hydro gas system is considered. The second part of this article is motivated by the fact that proposed CASO algorithm with P‐I controller is superior in contrast to bacterial foraging algorithm technique. In addition to this, some energy storage devices such as fuel cell, aqua electrolyzer, and ultra‐capacitor are used to achieve a better dynamic response within specified delay margin. Moreover, to study the impact of communication delays (delay margin) due to the loss of synchronism between solar‐wind (for their unpredicted environmental features) and thermal unit (nonlinearities like generation rate constraints, boiler dynamics, and governor with the dead band) are considered in thermal unit and the simulation results verify with the effectiveness of the proposed approach on providing a balance between the delay margin and the damping performances is evaluated under deregulated environment. The simulation results help to make an inter‐relation between the delay margin and the controller gain (P‐I) which help the system operator in designing controllers gain for stable operation of the proposed hybrid system. [ABSTRACT FROM AUTHOR]

With the rapid development of renewable energy, the primary frequency control (PFC) is becoming more critical and significant to ensure the stability of the electrical power system. As the main role of PFC, the thermal power unit tends to in a wide operation interval, and the changes in PFC characteristics along with working conditions are inevitable. By decomposing and quantifying the dynamic energy conversion process, this paper proposes a novel mechanism to evaluate the PFC capability for the supercritical thermal power plants that covered 30%–100% of the rated load. In the mechanism, a refined steam turbine model is established to reflect the short‐term dynamic response of PFC by combining it with the coupling characteristics of the main steam valve and main steam pressure in the later phase. Meanwhile, as a new prior assessment index, the equivalent electricity has been put forward to quantify the PFC capability for the power plant. In a case study of a 600 MW supercritical power plant, the capacities of PFC under 30%–50% of the rated load are quantified for the first time. Comparison results between theoretical calculation and real PFC test show that the proposed PFC capability assessment mechanism has acceptable accuracy of 96.1%, which could be effective to assess the frequency response reserve and stability margin in the grid. [ABSTRACT FROM AUTHOR]

This article addresses a model predictive control (MPC) technique for load frequency control (LFC) system in the presence of wind power, communication delay, and denial‐of‐service (DoS) attack. In this article, communication delay is incorporated into a single area control error transmission for simplicity, wind power and load disturbance are regarded as Lipschitz nonlinear terms, as for the randomly occurring DoS attack, it is modeled as Bernoulli processes with known conditional probability. Thinking all these adverse factors to stability and the limitation of input constraint synthetically, the stability of LFC system can be guaranteed by delay‐dependent Lyapunov function lemma and a state feedback MPC controller is designed to solve the LFC problems by minimizing the infinite‐horizon objective function. Although some scholars have studied the performance degradation and instability of LFC system caused by cyber attack and/or communication delay and some very nice results have been addressed, limited works have considered the MPC approach to deal with both the problems of cyber attack and communication delay which explicitly considers the physical constraints. In addition, the delay‐dependent Lyapunov function is adopted to deal with the problem of communication delay, which results in less conservatism of the presented method. Finally, the optimization problem with input constraint is solved and proven to be recursive feasibility, and the closed‐loop system turns out to be stable. The reasonability and validity of the provided strategy is verified through several groups of simulation experiments. It illustrates that the proposed control method can keep the system frequency steady in the standard range in spite of various attack conditions. [ABSTRACT FROM AUTHOR]

Modern power systems are very complicated and have more obligation to uphold the supply of power be reliable, stable, and of decent quality at both the transmission and distribution phases. Preserving grid balance is a significant concern if there is an unforeseen generation deficit or grid disturbance, or intermittent renewable energy sources, such as bio‐diesel, electric vehicles (EVs), and solar power are incorporated into the energy mix. To compensate for this imbalance and enhance the power system's reliability and stability, the energy storage systems (ESS) can be regarded as an appropriate measure. Thus, ESS contributes to greenhouse gas (GHG) emission reductions by successfully integrating more renewable energy sources into the grid. This article presents multiple ESSs, such as pumped hydroelectric storage (PHS), accurate flywheel energy storage (AFES), battery energy storage (BES), capacitive energy storage (CE), and superconducting magnetic energy storage (SMEs) and their comparative performance analysis in unified voltage and frequency control of power system. The proposed interconnected power system includes thermal, solar‐thermal, bio‐diesel‐engine generator, and EVs. In both control systems, a maiden attempt was made to utilize Harris' Hawks optimization‐based fuzzy‐fractional‐order‐tilt‐integral‐derivative (FFOTID) controller. The repercussion of PHS proclaims a substantial amelioration in system performance than other ESSs. Likewise, the system exhibits better dynamics with the coalition of PHS and power system stabilizer (PSS) of AVR compared to their separate intervention. Lastly, sensitivity analysis of proposed controller is analyzed by alteration of load perturbation and nonlinearity of thermal plants, which ensures optimal controller parameters accomplished at nominal conditions are resilient enough. [ABSTRACT FROM AUTHOR]

Communication of interconnected power system components with each other and with control centers is provided by using various communication links. However, these links can cause significant time delays (TD) depending on the types, distance and conditions of the communication channel. In addition to temporary time delays caused by the time constants of the components due to system failures, this article draws attention to the negative effects that may be caused by permanent communication time delays in particular, as different from the literature. The communication time delays can disrupt the stable operation of power systems and even cause the whole system to breakdown by making it unstable, when combining with other delays. In the study, the fiber‐optic (F/O) links are assumed to commonly use in supervisory control and data acquisition (SCADA) systems and the communication time delays are calculated based on this scenario. However, it is no doubt that less used radio frequency (RF)‐links will create more time delays. Moreover, to eliminate the negative effects of these types of time delays, a novel neural network based‐heuristic fractional order hybrid adaptive proportional‐integral‐derivative (ML‐H‐PIλDμ) controller for multi area load frequency control (LFC) scheme is developed and analyzed. [ABSTRACT FROM AUTHOR]

One of the significant problems in demand response (DR) participation in the smart power system is calculating how much electrical power is required to extract from DR (∆PDR) to keep the power system frequency in the allowable range. Calculating the precise amount of this value is impossible due to the random nature of load disturbance (LoD). In this paper, a new method is presented to control the DR participation in the load frequency control considering communication time delay. Extended State Observer is used to estimate the magnitude of the LoD, considering the structural uncertainty of the power system parameters. Then, the DR program is implemented in load frequency control to compensate the whole or part of LoD considering the available electrical power at the aggregators (PAV‐AGG) and communication time delay. Afterward, Active Disturbance Rejection Control is modified and adopted to control the uncompensated LoD. The salp swarm algorithm is employed to design the parameters of the proposed method, which is verified in comparison with the previous methods. The results demonstrate that the presented approach has potentially significant performance, assisting the power system frequency to be damped immediately with the small overshoot and undershoot. [ABSTRACT FROM AUTHOR]

This paper presents a load frequency control (LFC) design using the variable structure model predictive controller (VSMPC) for gain scheduling (GS) of PI controller in PV connected thermal for multi‐area system. Due to the increasing impact of renewable energy sources into the grid system, the system frequency deteriorates. The proposed PV connected thermal system is evaluated under varying load conditions under increased penetration of the PV source. The combination of renewable energy into the thermal power system aggravates the frequency and it is indispensable to mitigate such a problem by introducing an optimal controller. Perturbation in load greatly affects the system frequency and this problem is addressed by using VSMPC based gain scheduling knowing the effect of proportional and integral in transient and steady‐state conditions. The oscillations in frequency are controlled by a proposed controller and the impact of frequency under penetration of PV is monitored. Further verification of the proposed technique is accomplished through communication delay in the governor and turbine. The Hardware in the loop (HIL) which validates the accuracy and real time performance of the controller. Finally, the validation of the proposed controller is compared with MPC to tune PI controller and renowned evolutionary tuned techniques like particle swarm optimization (PSO), genetic algorithm (GA) and firefly algorithm (FA) to optimize PI controller. The VSMPC with GS of PI controller shows promising results. [ABSTRACT FROM AUTHOR]

Recently the raise in interconnection of the power system leads to vigorous change of power flow, as well as load in tie‐line. Hence, there is a need of robust control in both tie‐line power flows and systems frequency. This research work aims to design a dual‐mode switch controller‐based load frequency control in multi‐area interconnected power system (MAIPS). In this, the incremental control action's influence is taken along with the constraints of the system dynamic such as Governor with Dead Band, Capacitive Energy Storage, and Generation Rate Constraint. This work on the proposed controller of the multisource‐MAIPS (MS‐MAIPS) is operated on the basis of dual mode switching function. For this purpose, a threshold value ξ$$ \xi $$ is evolved. The control on MPC and optimized hysteresis modulation based sliding mode control (HMSMC) is varied according to this switching function. For attaining the fascinating performance, the optimal tuning of switch threshold ξ$$ \xi $$ and the gain of HMSMC controller K$$ K $$ is exploited by a new Self‐Adaptive Sea Lion algorithm. To the end, variation of control parameters like Tr$$ {T}^r $$,Trb$$ {T}^{rb} $$, Cg$$ {C}^g $$, as well as TCD$$ {T}^{CD} $$ for reducing unwanted variances in power flows among control areas is used to verify the effectiveness of the implemented scheme. [ABSTRACT FROM AUTHOR]

This article considers the load frequency control of multi-area power system-based multi-agent system method under false data injection attacks. The research can provide better solutions for multi-area power system load frequency control under false data injection attacks. First, an event-triggered mechanism is introduced to decide which data should be transmitted in the controller to save the limited network bandwidth. Besides, a model of cyberattacks is built using the Bernoulli random variables. Then, conditions are given for maintaining the system asymptotic stability under attack. Finally, simulations are performed to demonstrate the validity of the theory proposed in this article. [ABSTRACT FROM AUTHOR]

This article proposes a novel asynchronous advantage actor‐critic (A3C) learning‐based dynamic event‐triggered mechanism for the decentralized load frequency regulation to alleviate the local‐area communication burden and influence of the load fluctuations. The proposed dynamic event‐triggered mechanism applies the A3C algorithm to optimally adjust the threshold of the event‐triggered function in real time. In the A3C algorithm framework, the long short‐term memory (LSTM) network is used to estimate the policy function and value function. First, for each control area, a novel model of the decentralized load frequency control (LFC) system is established to design the event‐triggered communication mechanism and deal with the communication delay simultaneously. Then, based on the Lyapunov stability theory, the controller gain parameters of the decentralized LFC system and the margins of the even‐triggering thresholds are derived by solving a series of linear matrix inequalities (LMIs). Finally, a three‐area and four‐area power systems are used to evaluate the proposed decentralized LFC method. Simulation results show that the proposed method can greatly reduce the data transmission times and preserve a satisfactory system performance. [ABSTRACT FROM AUTHOR]

In this article, load frequency control has been studied in an unequal three‐area system under a deregulated environment. The area 1 comprises thermal and biodiesel units, area 2 has thermal and solar thermal power plant (STPP), and area 3 has thermal with biogas, wind turbine system (WTS) along with pumped hydro energy storage (PHES) units. A new secondary controller called three degree‐of‐freedom tilt‐integral‐derivative with filter (3DOF‐TIDN) controller has been proposed, and its performance is compared with integral, tilt‐integral‐derivative with filter, and two degree‐of‐freedom‐TIDN controllers. The investigation reveals 3DOF‐TIDN controller provides better dynamic performance in terms of settling time, peak deviation, and magnitude of oscillations in both generating and motoring mode of PHES. The stability analysis has been performed for the proposed system using different secondary controller. The controller parameters are optimized using novel optimization technique called Mine Blasting Algorithm. In this study, real‐time OPAL‐RT digital simulator has been used to effectually execute the considered power system under various scenarios, and the obtained results are compared with MATLAB/Simulink results. Further, a comparative study of dynamic responses of the system has been carried out considering different mechanical energy storage devices like PHES, flywheel energy storage device, and compressed air energy storage, and the analysis shows that PHES gives superior performances than others. Robustness analysis of proposed controller gains is also conducted, considering different uncertainties. [ABSTRACT FROM AUTHOR]

Summary: The present paper proposes a novel state‐observer (SO) based integral‐double‐derivative controller for simultaneous frequency‐voltage control operation of a hybrid power system. The hybrid system consists of solar‐thermal, conventional‐thermal, diesel‐plant, and modern day electric vehicle (EV), establishing a concurrent system frequency, voltage, and the corresponding tie‐line power control. In order to exhibit realistic approach, the hybrid system is provided with appropriate system non‐linearities. For the desired performance of the presented hybrid power system, controller gain parameters are optimized by means of a highly effective magnetotactic‐bacteria‐optimization (MBO) technique. The objective function to be minimized is such formulated, resulting in optimized system performance. The reduction of objective function values by 13.6% for the proposed controller is exhibited. Similarly, the demerit index shows a reduction of 25% as compared with other controllers. Sensitivity test pertaining to extensive variations of system parameters from the nominal values confirms the robustness of the optimal controller gains. The proposed control strategy is tested on a more complex three‐area hybrid power system, and the simulation results further validate the effective regulation approach of the optimal controller with a reduction of 12.9% in objective function value. The fact that EVs assist in improving system stability is also demonstrated. An innovative study related to the effects of large penetration of EVs on the system load demand is presented herewith. [ABSTRACT FROM AUTHOR]

Summary: This paper studies the distributed load frequency control problems for the multi‐area interconnected power system in smart grid. Compared with current results, we develop a new model transformation for traditional interconnected systems with unknown communication time delays and uncertainties. The load frequency control problem becomes the state synchronization problem of multi‐agent system (MAS) consisting of linear double‐integrator system with uncertainties and delays. Then, the H∞ distributed controller is designed based on the new MAS model, which weakens the impact of communication delays, parametric uncertainties, and load disturbance. Meanwhile, the proposed distributed controller only needs its neighbors' information and some rough information about the communication network to achieve the frequency's synchronization. In addition, the power flow in the power system can achieve the power scheduling and peak regulation with the changes of each area's load, which can cause unacceptable frequency deviation. The switching topologies are used to express this new power flow distribution. The corresponding distributed controllers are designed to achieve the frequency's synchronization. Finally, simulation result shows the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Summary: Renewable sources are deployed to meet the growing needs of the energy demand. Integration of these renewable sources in a power system leads to increased complexity due to which it is essential to adapt new control strategies to retain system stability by preserving frequency in a nominal value. Therefore, the objective of the work is to control the load frequency of an interconnected hybrid (wind, solar, thermal) power system by optimizing generator cost while implementing the demand management technique. Deviation in the frequency and tie‐line power due to fluctuation of renewable energy sources and load is addressed. For cost optimization, demand management technique was applied to the distribution system comprising flexible loads such as electric vehicle and heat pump. Voltage constraints and network congestion in the system are considered. The cascaded control technique is proposed for load frequency control and firefly based controller for cost optimization in the thermal power system. In the cascaded controller, proportional integral derivative (PID) and atom search optimization algorithm‐tuned PID controller are recommended. Performance of the projected approach is compared with a PID controller and fuzzy logic controller‐based load frequency control. Simulation studies and the result of various test cases considered clearly show the effectiveness of the controller implemented in the proposed system. [ABSTRACT FROM AUTHOR]

Summary: In this manuscript, the load frequency control (LFC) of multiple area hybrid power system (PS) integrated with renewable energy sources (RESs) using energy storage system (ESS) is proposed. The proposed hybrid method is the joint execution of Meta‐heuristic Anopheles Search Algorithm (MASA) and artificial intelligence (AI) technique and hence it is named as MASAAI technique. The main aim of the proposal is "to diminish the load frequency deviations in 3‐area hybrid PS." The thyristor controlled phase shifter (TCPS) and ultra‐capacitor (UC) application are used in LFC. During the operation of power system, the power distribution quality is suffered owing to continual and random changes in load. Hence, the PS control is necessary for maintaining a continual balance amid the power generation and load demand. The proportional integral derivative (PID) is agreed to LFC mode. Here, the 3‐area system is incorporated with conventional RESs like solar, biomass, and fuel cell. UPFC is joined in series with tie‐line, ensures the stabilization of the system and also presents more service and the quality of power is sustained by the subordinate control of super capacitor energy storage. With the help of MASAAI method, suppressing the peak value of the frequency deviation by power modulation control is a way to lessen this issue. With this proper control, the MASAAI method efficiency becomes optimum in deregulated environment that is agreed to LFC mode. Finally, the proposed method is activated in MATLAB/Simulink site and the performance is compared with existing methods. Finally, the simulation outcomes demonstrate that the efficiency of MASAAI method is more efficient compared to the existing methods. [ABSTRACT FROM AUTHOR]

Summary: The doubly fed induction generators based wind power plant is extensively used as a renewable energy source; however, their integration with interconnected power systems may cause equal challenges as well. Since such WPPs are decoupled from the grid frequency to operate at maximum power point tracking, hence they cannot participate in effective load frequency control and cause severe deterioration in the frequency regulation of the nonlinear IPS. To address these issues, this article proposes a novel dual‐layered tilt fuzzy control structure (DLTFCS), which comprises of a fuzzy tilt integral derivative with a filter as the first layer working in coherence with a fractional order proportional derivative controller as the second layer, together with an inertial frequency support scheme for WPP. The DLTFCS is developed with an intention of efficient handling of nonlinearity and parametric uncertainty of considered IPS in the presence of WPP. Further, a curated hybrid objective function is also proposed, which consists of a weighted combination of integral of time‐weighted absolute error and oscillatory measure with the help of an analytical hierarchy process and is optimized by a recently devised salp swarm algorithm. The control performance of the proposed controller has been validated by extensive simulation studies under various scenarios ranging from system parametric variations, uncertainties in generation rate constraint, and governor deadband to significant variations in wind penetration levels. Extensive comparative studies suggested that the proposed control structure provides superior performance over fractional order proportional integral derivative (FOPID) and Fuzzy FOPID controller. [ABSTRACT FROM AUTHOR]

Summary: This paper is concerned with the robust H∞ load frequency control (LFC) of power systems with two time delays in the presence of load disturbance. Firstly, the original power systems with the proportional‐integral (PI)‐type LFC are converted into an output feedback control system with two time delays. Secondly, an improved reciprocally convex inequality is proposed, and a less conservative robust H∞ criterion is derived, which can be used to design the PI‐type LFC with robust H∞ performance. Then, based on the robust H∞ criterion, an algorithm is provided to obtain the PI‐type LFC gain and the time delay margin, which effectively convert the coupled nonlinear terms into linear items without solving the inverse of the matrix with row full rank. Finally, simulations are shown to verify the superiority of the presented method. [ABSTRACT FROM AUTHOR]

Summary: Hydro power plants are in general more stable to the load demands and thus the change in frequency can be easily controlled. Whereas in multi‐source interconnected power system the stability of the system is marginal. In certain conditions the system is also unmeasurable to implement the load frequency control. Linear Quadratic Regulator with output feedback design forms a familiar optimal choice to tackle this problem, but the technique is dependent on the choice of the weighting matrices Q and R for the performance index. Particle swarm optimization technique is commonly used in power system applications for obtaining the weighting matrices. In this paper, an output feedback‐based LQR‐PID technique is used to obtain an improved response for the multisource systems. Due to integral action, the steady‐state value achieved for the change in frequency is minimized. In addition, if the system is unmeasurable LQR technique cannot be applied, in the literature, Linear Quadratic Gaussian is used for the same. Here a balanced truncation model order reduction is used on the original system to convert it to a measurable system. In addition, a comparative analysis is included to highlight the efficacy of the proposed control technique. [ABSTRACT FROM AUTHOR]

Summary: Recently, there has been a growing trend of large proliferation of electric vehicles (EVs) due to its various merits like minimum emission of greenhouse gases, high‐energy efficiency, less maintenance, cost, and so on. Electric vehicles are now seen as an environment friendly and cost effective alternative to the fuel vehicles. This article presents an effective load frequency control of a multi‐area interconnected power system connecting EV fleets along with diversified sources such as Archimedes wave energy conversion (AWEC), geothermal power plant, wind power plant turbine generator, hydro power plant, and thermal power plant. A cascaded controller, combination of tilt integral derivative filter (TIDN) and 1+proportional‐integral (1+PI) (ie, TIDN‐(1+PI)), has also been proposed in this article as a secondary controller to improve the system performances. The real‐time simulation of the considered power system has been effectually executed under different scenarios, using OPAL‐RT's digital simulator. The result shows that the proposed TIDN‐(1+PI) controller along with EV fleets are capable to significantly minimize the frequency and tie‐line power oscillations rapidly and it also provides better dynamic performance of the system as compared to other conventional controllers such as integral, proportional‐integral and so on. In addition, variable and irregular AWEC power, load disturbances in all areas, and multiple nonlinearities have been considered to study the effect of EV fleets in the proposed system. Also, stability of the system has been studied by using Eigen value analysis method. [ABSTRACT FROM AUTHOR]

Summary: Load frequency control (LFC) is an effective method to maintain frequency stability in power systems. With the large‐scale application of wide‐area measurement system (WAMS), impacts of unexpected physical faults and malicious cyber attacks on the frequency deviation damping performance of LFC systems cannot be ignored anymore. Different from the traditional robust‐based design methods, which assume that the operating parameters vary within a small range, physical and cyber failures may cause the significant structural or parametric changes in LFC system. Hence, a system parameter‐free active fault‐tolerant control (AFTC) strategy for LFC is proposed. First, a bank containing a series of controllers is predesigned to stabilize all the possible operation scenarios. Second, a zero trial‐and‐error selection scheme, which does not depend on prior system parameters is well‐designed to select the most matching controller. To enhance the fault‐tolerant ability in case of unmodeled faulty situations, an expansion scheme without any prior faulty information is proposed. Finally, simulation results of a three‐area‐interconnected power system show that our proposed method can ensure the smooth transition of LFC system under physical/cyber failures, thereby the reliability of power grid operation can be enhanced. [ABSTRACT FROM AUTHOR]

This paper investigates dynamic event‐triggered H∞ load frequency control for multi‐area power systems with communication delays. A novel co‐design method of trigger parameters and H∞ controller based on output feedback is proposed. Unlike routine multiplication operations, this method eliminates rank constraints on the input and output matrices, and avoids the processing of nonlinear terms related to the trigger parameters. Furthermore, under the presented dynamic event‐triggered mechanism, the threshold parameters are dynamically regulated according to the dynamic variation of the system. Therefore, the average data releasing rate can be adjusted in real time to better coordinate the use of network bandwidth resources and requirements of system dynamic performance. Specially, the usage of the infinite‐series‐based inequality and reciprocally convex combination inequality effectively reduces conservatism of the criteria. Finally, some simulations and related comparisons are carried out to demonstrate superiorities of the proposed method. [ABSTRACT FROM AUTHOR]

Summary: This paper presents an initial work to design frequency stabilization strategies through, I, PI, PID, ID, and IDD calculated via the JAYA optimization process for load frequency control (LFC) framework of photovoltaic (PV) and thermal generators linked via AC tie‐line. Firstly, a comparative analysis of all LFC designs is conducted for typical load alterations, and the LFC recital is evaluated on basis of pick‐up value, inverse absolute error (IAE), inverse time multiplied by absolute error (ITAE) and the interpretation of graphical results. Additionally, the effects of an ultracapacitor combined with a redox flow battery and an ultracapacitor in each zone of the PV‐thermal system is also investigated and evaluated to improve the results of the PV‐thermal system. Finally, the effectiveness of the proposed plan is assessed for nonlinearity, continuous load alteration, and broad parametric varieties from the ordinary plant values. The application results are presented to show the novelty and benefits of the proposed work. [ABSTRACT FROM AUTHOR]

Summary: The increasing integration of regional power grids, rising penetration of multi‐generation sources, and day‐ahead power agreements have raised the operational challenges on deregulated modern electric energy systems. Among various challenges, frequency regulation becomes more prominent in the restructured power system (RPS) due to increased uncertainties and intricacies among other operational challenges. A minor deviation in system frequency affects the safety, quality, stability, and operation of the interconnected power system (IPS). An appropriate control mechanism and energy storage device are essential to regulate the system's dynamic responses during continuously varying loading conditions. This study proposed a novel Salp swarm algorithm (SSA) optimized fuzzy‐based proportional‐integral‐derivative filter (FPIDF) controller with redox flow battery (RFB) to regulate the frequency of a realistic multi‐area multi‐source (thermal‐hydro‐gas) interconnected power system. All probable contract transaction scenarios are simulated that can be possible in a deregulated power industry. Various nonlinearities such as time delay (TD), governor dead band (GBD), and generation rate constraint (GRC) are incorporated to resemble the realistic operational conditions of the IPS. The effectiveness of the suggested controller has been validated by comparing the system performances with a recently published sine‐cosine algorithm (SCA) based proportional‐integral (PI) controller and SSA‐PID controller. The investigation has been further extended by incorporating RFB in the proposed system. The study reveals that the suggested controller provided superior system control under various system uncertainties in all contact scenarios of the competitive electricity market. Additionally, the system performances have been significantly enhanced due to quick response and precise control offered by RFB. [ABSTRACT FROM AUTHOR]

Summary: Zero‐carbon multienergy sources (ZCESs) integration into a power system becomes mandatory to reduce energy production costs and fuel‐burning emissions. Although, the energy mix of ZCESs with high penetration levels arises at moderated frequency as well as voltage response deterioration of the interconnected power systems. These response deteriorations stem from the fluctuation nature of ZCESs. Therefore, the necessity for overcoming these performance degradations is not an option for power system planners and operators. Thanks to fractional order (FO) mathematics in conjunction with metaheuristic optimization algorithms (MOAs) as they can be employed to enhance the damping of ZCESs oscillations under energy mix uncertainties. Three‐area solar thermal‐wind‐hydro (STWH) power system, including system's uncertainties such as data telemetry delays and governor dead bandsand generation rate constraints, is considered to accomplish this study. The performance of STWH system equipped with FOPID‐based load frequency controllers tuned by various modern MOAs (FOPID‐based LFCs) has been compared to the classical PID‐LFC controllers governed by the same MOAs, to demonstrate the superior efficiency of the FOPID‐based LFCs. The efficacy of FOPID‐based LFCs and their effectiveness compared to the predecessors are verified during simulation results. [ABSTRACT FROM AUTHOR]

Summary: This paper suggests a novel cascade fractional‐order controller (CC‐FOC) comprising of three degrees of freedom proportional‐integral‐derivative (3DOF‐PID) and tilt‐integral‐derivative (TID) controllers for solving the load frequency control problem of an interconnected power system integrated with DFIG‐driven wind power system. In the proposed CC‐FOC, 3DOF‐PID and TID controllers are used as slave and master controllers, respectively, to alleviate system oscillations and to improve system stability in the wake of sudden perturbations. A novel meta‐heuristic technique, namely equilibrium optimizer (EO), has been adopted and successfully implemented for concurrent tuning of the proposed controller's different parameters. Simulation outcomes of the EO have been evaluated with those attained by gravitational search algorithm, grey wolf optimization, and the results are reported in the literature. The efficacy of the proposed CC‐FOC is established by contrasting its responses with the outcomes of 3DOF‐PID, 2DOF‐PID, TID, and conventional controllers. The mastery of the proposed controller is further assessed, including system nonlinearities like GRC and GDB. The results obtained through extensive simulation reveals that the suggested approach significantly enhances system performance compared to the prevalent controllers of the existing literature. Finally, the robustness of the test system having CC‐FOC integrated is demonstrated against wide variation in system parameters by employing Kharitonov's theorem. [ABSTRACT FROM AUTHOR]

Background: The unprecedented growth in human population and industrialization, the present‐day energy demands have soared dramatically. Therefore, it is essential to integrate renewable energy resources with the conventional ones to keep the energy demand and supply at equilibrium. Aims: While integrating these two energy resources, it is important that the power generated through renewable energy resources should be able to sustain inherent variability and uncertainty of conventional resources. The interaction of renewable into thermal power system degrades the frequency and it is important to mitigate such a problem by introducing an optimal controller. Materials & Methods: In this paper, an optimized Adaptive Fuzzy Logic Controller based Proportional‐Integral (AFLC‐PI) is proposed for Load Frequency Control (LFC) for a multi‐area system. The proposed controller has the capability to tune the Proportional‐Integral (PI) controller on the basis of frequency error, frequency oscillations and minimize the LFC problem for Photovoltaic (PV) connected thermal system. Moreover, the Adaptive Fuzzy Logic Controller (AFLC) response under different real‐time load changing conditions is simulated and analyzed along with the uncertainty in governor and turbine time‐constant. Finally, the comparison analysis with Fuzzy Logic Controller tuned PI (FLC‐PI), Genetic Algorithm tuned PI (GA‐PI) and Firefly tuned PI (FA‐PI) based optimized controllers is carried out. Results: We have analyzed our proposed controller response at various load variations, under critical load variation and observed how fast our proposed technique mitigates the frequency oscillations. Discussion: The results clearly depict that the proposed controller is meeting the critical targets (undershoot, overshoot and settling time) under varying load conditions, sudden variation in a turbine, and governor where AFLC‐PI has the ability to deal any ambiguity in a system effectively. Conclusion: The proposed controller mitigate the frequency oscillation in a robust way as compared to other state of the art controllers. [ABSTRACT FROM AUTHOR]

Summary: In this study, the impacts of non‐integer order controller on the stable parameter space of the microgrid (MG) frequency control system with fixed communication time delay are investigated and discussed with the help of the stability boundary locus (SBL) method. This study proposes a non‐integer order controller for the load frequency control (LFC) of the MG systems. To that end, the load frequency model of the MG is formulated and then the characteristic equations of this model are obtained. Then, with the help of this characteristic equation, the stable parameter space of the non‐integer controller is determined with regard to different time delay (τ) and fractional integral order values (α) using the SBL method. In order to show the accuracy of the obtained stable parameter space, time domain and generalized modified Mikhailov (GMM) criterion studies are carried out for different values of (τ) and (α). According to the results obtained, the areas of stable parameter space according to different α values and τ = 1.6 are calculated as 444.8860 for α = 0.4, 342.9728 for α = 0.7, 259.3578 for α = 1, 216.2541 for α = 1.3 and 159.6826 for α = 1.6. In addition, the areas of stable parameter space according to different τ values and α = 1.4 are calculated as 784.5222 for τ = 1, 106.3219 for τ = 2, 29.6959 for τ = 3 and 11.5946 for τ = 4. Despite the extreme variability arising from nature of resources that make up the MG, the designed non integer order controller with the values selected within the stable parameter space stably carries out LFC control of the MG. [ABSTRACT FROM AUTHOR]

Summary: In this present contribution, an attempt has been taken to design and analyze the performance of elephant herding optimization (EHO) based controller for load frequency control (LFC) applications of interconnected power system. The studied system is a two‐area nonreheat thermal interconnected system which is widely used in literature. A proportional‐integral‐differential controller is utilized for LFC of the studied system. EHO technique is applied to obtain the tuned set of controller parameters. The objectives considered for design of the controller are the minimization of settling times and integral‐time‐multiplied‐absolute‐error of frequency deviations (FDs) and tie‐line power deviation (TPD). The design objectives are integrated together to form a function with single objective by assigning equal weights after normalization. Several test cases of diverse set of disturbances are taken into account to test the performance of the proposed controller and the obtained results are compared with other controllers designed with differential evolution, gray wolf optimization, particle swarm optimization, teacher‐learner‐based optimization, and whale optimization algorithm. Furthermore, the time‐domain simulations of FDs and TPD are illustrated to support the tabulated results. In addition, comparative statistical analysis is presented to validate the robust behavior of the proposed controller. [ABSTRACT FROM AUTHOR]

Resilient dynamic event‐triggered control design problem is concerned for frequency stabilisation of multi‐area power systems with renewable energy penetration under transmission delay and denial‐of‐service (DoS) attacks. The main works are presented as followings: (1) A novel state‐space model is established to describe multi‐area power systems with solar and wind generation disturbance under load frequency control and virtual inertia control (LFC‐VIC). (2) The influence of DoS attacks is considered and first modelled by model‐based average dwell time (MDADT). A criterion of preserving desired exponential H∞ performance is obtained about the required lower bound of average dwell time (ADT) of sleep intervals, namely τF>ln⁡λ0/α1 and the tolerable upper bound of ADT of attack intervals, namely τD<−(ln⁡λ1+(α0+α1)dM)/α0. (3) To reduce communication load, a dynamic event‐triggered mechanism (DETM) is proposed and designed jointly with resilient LFC‐VIC scheme by using piecewise Lyapunov–Krasovskii functional method and LMIs technique. (4) To defence DoS attacks actively, based on the resulting MDADT criterion, a dynamic prediction strategy is proposed to compensate the packet drops with unknown bound subjected to attack strategy. Finally, a numerical example for a two‐area power system is carried out to verify the designed resilient LFC‐VIC scheme and the DETM. [ABSTRACT FROM AUTHOR]

To facilitate the frequency regulation, here an adaptive artificial neural network (ANN) tuned proportional‐integral‐derivative (PID) controller is suggested for load frequency control (LFC) investigation in a system with distributed generation (DG) resources. The various DG resources include wind turbine generators (WTG), battery energy storage system (BESS), aqua electrolyzer (AE), diesel engine generators (DEG), and fuel cell (FC). Initially, an isolated thermal generating system is considered with DG. Then an interconnected two‐area thermal power system with DG is considered for LFC analysis. The implemented PID controller parameters are achieved using two methodologies. In the first case, the PID controller parameters are tuned by a recent optimization technique known as grasshopper optimization algorithm (GOA). In the second case, the PID controller parameters are tuned by an ANN. The dynamic behavior of the two categories of the system is inspected with GOA tuned PID controller and ANN tuned PID controller and it is established that ANN tuned PID controller exhibits superior performance as compared to GOA tuned PID controller in terms of time‐based performance evaluative factors such as minimum undershoots, settling time and maximum overshoots. Also, the robustness of the recommended ANN tuned PID controller is verified by applying random loading in the system. [ABSTRACT FROM AUTHOR]

One of the used areas of wave energy conversion systems is shipboards. In shipboard microgrid with wave energy conversion systems, load frequency control is very important because of the over‐variable nature of the energy generated by wave energy conversion system. In this study, new controller design for load frequency control of the shipboard microgrid with wave energy conversion systems is proposed. With the proposed controller design, the system is operated in suitable stable parameter space in order to guarantee the desired gain and phase margins and the system is more stable against the uncertainties of parameters that will occur. A virtual phase and gain margin tester is added to the shipboard microgrid with wave energy conversion systems in order to take into account the gain and phase margin in the stability region calculations. First, the characteristic equation of this system is obtained. After the appropriate conversion operations on the obtained characteristic equation, the stable parameter space of the controller is calculated by taking into account time delay, gain and phase margin. Eigenvalue and time‐domain analysis studies are performed on the system to show the accuracy of the stability region results. [ABSTRACT FROM AUTHOR]

Load frequency control in modern-complex-uncertain power systems (PSs) assumes significance due to their challenging nature of the operation and hence utilisation of robust controllers is indispensable. In the industry, conventional single-loop controllers may not offer robust behaviour under changed operating conditions. Alternatively, two-loop cascade fuzzy structured controllers can show significant robust performance in dynamic conditions and best suited in systems having non-linearities. Hence, a novel optimal cascade fuzzy-fractional order integral derivative with filter (CF-FOIDF) controller is utilised for 2-area thermal and hydrothermal PSs considering various physical constraints from a practical point of view. As physical constraints mandate an energy storage system, hence in this study, batteries of electric vehicles (EVs) are employed to assist power plants to swiftly arrest oscillations in the system frequency following load demands. A combined model of EV fleets is incorporated in the control areas of PSs. Numerous simulations are conducted to authenticate the robustness and excellence of EVs and the suggested control strategy over existing methods. [ABSTRACT FROM AUTHOR]

Summary: In this paper, load frequency control of photovoltaic (PV)‐thermal‐thermal interconnected three area power system is proposed with fuzzy gain scheduling controller. Grid‐connected PV power system has quick rising annual rate and is rapidly becoming a significant part of the energy balance in the power systems. Reduction in the PV modules cost increases the application of PV. In recent days, increase in load demand necessitates the interconnected power systems. Power quality concerning frequency plays a major role in life and efficiency of the load. The fuzzy logic controller is an efficient controller to deal with the unknown data; in the LFC, the load demand is unpredictable; hence, fuzzy is applied for LFC in this analysis. Proportional integral (PI) controller plays a significant role in real‐time LFC. Therefore, in this article, fuzzy gain scheduling controller is proposed to tune gains of PI controller to improve performance of interconnected power systems. To validate the performance of proposed system, it is compared with the conventional PI controller‐based LFC. The entire system is analyzed using Matlab with various loads. [ABSTRACT FROM AUTHOR]