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As power network complexity increases, efficient control of frequency deviations and tie-line power fluctuations becomes crucial. Load frequency control (LFC) addresses these issues by managing generation-consumption mismatches. This paper introduces a unique P-P-FOPID cascade controller for LFC, combining a proportional controller with a fractional-order PID. The marine predators algorithm (MPA), known for its benefits like being parameter-less, derivative-free, user-friendly, flexible, and simple, is employed to optimize the controller's parameters using the integral time absolute error criterion. Tested on three power systems, the proposed controller outperforms single-structure FOPID controller based on MPA and recent approaches in reducing ITAE, settling time, and frequency and tie-line power deviations. In comparative analysis, the proposed MPA-tuned P-P-FOPID controller achieves a 60% and 11% decrease in ITAE compared to the second-best DSA-optimized FOPI-FOPD controller for Systems 1 and 2, respectively, and a 25% decrease compared to the second-best MPA-tuned FOPID controller for System 3. Furthermore, the controller's robustness against parametric uncertainties is confirmed through variations in fundamental parameters. [ABSTRACT FROM AUTHOR]

As the scale of China's interconnected power grid continues to expand, traditional serial computing methods are no longer sufficient for the rapid analysis and computation of electrical networks with tens of thousands of nodes due to their small scale and low efficiency. To enhance the capability of online grid analysis, this paper introduces an accelerating batched power flow calculation method based on a heterogeneous CPU-GPU platform. This method, based on the fast decoupled method, combined with the tremendous parallel computing capability of GPUs with the multi-threaded parallel processing of CPUs, efficiently resolves the exceeding bus type conversion issues in GPU-batched power flow calculation and improves the accuracy of the power flow calculations. Then, a binary-based power flow data exchange format was introduced, which utilizes a single binary file for data exchange. This format significantly minimizes I/O time overhead and reduces file size, further enhancing the method's efficiency. Case studies on real-world power grids demonstrate its high accuracy and reliability. Compared to the traditional single-threaded power flow calculation method, this method dramatically reduces time consumption in batch power flow calculations. It proves the significant advantages of dealing with large-scale power flow calculations. [ABSTRACT FROM AUTHOR]

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]

This article emphasizes the intermittent nature of RESs and finds how virtual inertia (VI) works to enhance the operation of the automatic generation control (AGC) mechanism of the interconnected hybrid power system (HPS). The challenge of controlling frequency deviation becomes more difficult as the complexity of a HPS increases. The robustness of the controller significantly influences the stability of an HPS. Because of HPS hybridization, PID, FOPID, and TID, the basic AGC controllers, are insufficient to provide a plant with maximum performance. So, a robust controller is needed for this. To get the best performance in terms of overshoot, undershoot, and settling time, a modified TID–MPC controller has been suggested and evaluated by comparison with a few existing controllers. The suggested controller can manage the frequency deviation effectively; it can stabilize it in 7 s for area 1, 9 s for area-2, and an average of 8 s for both areas. However, the average time for MPC is 12.5 s, and 19.5 s for TID. A newly modified OSHO approach has been proposed to optimize the different controller settings. The OSHO has been compared with a few well-known, existing metaheuristic optimizations to show its superiority. Due to higher penetration of RESs reduced the system inertia, further deteriorating the frequency response in HPS. To overcome these challenges, VI is implemented with RESs. The suggested controller's flexibility and reliability have been evaluated under different scenarios, such as step, multiple load disturbances, and modified IEEE-39 bus. The comprehensive research results provide strong evidence for the effectiveness and efficiency of the suggested control techniques and demonstrate the possibility of their use in actual power systems to enhance the stability and performance of modern HPS. [ABSTRACT FROM AUTHOR]

This paper presents the design of an H∞-based Restricted Static Output Feedback (RSOF) controller with regional pole placement in Linear Matrix Inequality (LMI) framework for Load Frequency Control (LFC) of a 2-area Interconnected Power System (IPS). The motivation behind the RSOF controller is to develop a controller with a predefined structure for implementing centralized and decentralized control strategy as per need. In this work a new stabilization criterion is developed by choosing circle and strip LMI regions for pole-placement along with the use of Particle Swarm Optimization (PSO) technique to tune the scalar parameters for the feasibility of the developed LMI criterion. The designed controller (both centralized and decentralized structure) with the above modifications improves the transient response of the frequency output. The designed controller is tested on a 2-area LFC model incorporating both conventional and renewable energy sources. Simulation results validate the effectiveness of the designed controller in attenuating disturbance and also enhancing the transient response. Also, simulation studies are carried out to test the robustness against time delays and cyberattacks. A comparative analysis is presented for various controllers, highlighting their performance differences. [ABSTRACT FROM AUTHOR]

A new framework for controlling load frequency in a complex, interconnected power system with multiple sources has been developed. This framework combines a fuzzy logic controller (FLC) and a tilted integral derivative (TID) controller, creating a self-tuning fuzzy tilted integral derivative (STFTID) controller. The purpose of this controller is to conduct and reduce load frequency perturbations during the operation of a multi-area interconnected multi-source power system. The STFTID controller is optimized using a particle swarm optimization algorithm to minimize the frequency fluctuations effectively. Investigations of the proposed STFTID controller were performed for power systems with generation units of a conventional system and renewable energy sources. In the design process of the STFTID controller, various nonlinearities, uncertainties, and fluctuations are considered to simulate practical challenges. These challenges include generation rate constraints, governor deadband, and communication time delays (as the sources of nonlinearity), as well as fluctuations caused by step load switching and the connection of renewable power plants to the system. The STFTID controller is compared with the proportional integral derivative (PID), titled integral derivative, and integral tilted-derivative (I-TD) controllers. Simulation results show that the developed STFTID controller significantly enhances the system frequency control under various applied conditions, including multi-step load perturbation, renewable power plant integration, communication time delays, and generation rate constraints. [ABSTRACT FROM AUTHOR]

The load margin is an important index applied in power systems to inform how much the system load can be increased without causing system instability. The increasing operational uncertainties and evolution of power systems require more accurate tools at the operation center to inform an adequate system load margin. This paper proposes an optimization model to determine the parameters of a Physics-Informed Neural Network (PINN) that will be responsible for predicting the load margin of power systems. The proposed optimization model will also determine an optimal location of Phasor Measurement Units (PMUs) at system buses whose measurements will be inputs to the PINN. Physical knowledge of the power system is inserted in the PINN training stage to improve its generalization capacity. The IEEE 68-bus system and the Brazilian interconnected power system were chosen as the test systems to perform the case studies and evaluations. Three different metaheuristics called the Hiking Optimization Algorithm, Artificial Protozoa Optimizer, and Particle Swarm Optimization were applied and evaluated in the test system. The results achieved demonstrate the benefits of inserting physical knowledge in the PINN training and the optimal selection of PMUs at system buses for load margin prediction. [ABSTRACT FROM AUTHOR]

In this paper, a generalized decentralized controller design is presented for robust stabilization and achieving certain L $ _2 $ 2 gain of a class of nonlinear interconnected systems via dynamic output feedback control within the LMI framework. This large-scale system is composed of linear subsystems coupled by nonlinear time-varying interconnections satisfying quadratic constraints. The proposed controller design uses the available neighbouring information to design a decentralized controller that operates at each subsystem. An LMI approach is sufficiently proposed as a feasibility problem of a BMI with respect to controller gains via dynamic output feedback structure. The application of power systems shows that the proposed controller can effectively stabilize the nonlinear interconnected systems and achieve desired performance, even in the presence of disturbances and uncertainties. [ABSTRACT FROM AUTHOR]

In this study, the integration of grid‐forming (GFM) converters in power systems is discussed in terms of both the fundamental aspects of system stability and the technical possibilities of converter‐based resources. The paper provides a survey and comparison of various GFM control concepts with respect to their transient and stationary behavior. A method for black box characterization and conformity testing of GFM converters is presented and relevant results of lab and field tests with GFM converters are discussed. Finally, important system aspects are addressed. This includes an approach to consider the behavior of GFM converters in distribution grid models and investigations on the minimum share of GFM units required to ensure system stability. The findings of this paper provide valuable insights for the design and implementation of GFM converters in modern converter‐based power systems. [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]

This paper introduces the Walrus Optimization Algorithm (WaOA) to address load frequency control and automatic voltage regulation in a two-area interconnected power systems. The load frequency control and automatic voltage regulation are critical for maintaining power quality by ensuring stable frequency and voltage levels. The parameters of fractional order Proportional-Integral-Derivative (FO-PID) controller are optimized using WaOA, inspired by the social and foraging behaviors of walruses, which inhabit the arctic and sub-arctic regions. The proposed method demonstrates faster convergence in frequency and voltage regulation and improved tie-line power stabilization compared to recent optimization algorithms such as salp swarm, whale optimization, crayfish optimization, secretary bird optimization, hippopotamus optimization, brown bear optimization, teaching learning optimization, artificial gorilla troop optimization, and wild horse optimization. MATLAB simulations show that the WaOA-tuned FO-PID controller improves frequency regulation by approximately 25%, and exhibits a considerable faster settling time. Bode plot analyses confirm the stability with gain margins of 5.83 dB and 9.61 dB, and phase margins of 10.8 degrees and 28.6 degrees for the two areas respectively. The system modeling and validation in MATLAB showcases the superior performance and reliability of the WaOA-tuned FO-PID controller in enhancing power system stability and quality under step, random step load disturbance, with nonlinearities like GDC and GDB, and system parameter variations. [ABSTRACT FROM AUTHOR]

With the increasing proportion of renewable energy power generation, its accompanying intermittency and volatility problems are becoming increasingly prominent, and the frequency fluctuation of the power system is becoming increasingly severe. Participation in frequency regulation services can be economically rewarding for generating units. The flywheel energy storage system can effectively improve the frequency regulation capability of coal-fired units. In this paper, the improvement of the FM capability of coal-fired units in the operation of a two-area interconnected power system containing wind power is investigated, and a model of a two-area interconnected power system comprising a turbine generator, wind power, and flywheel energy storage is established. The enhancement of the FM capability of coal-fired units by adding a flywheel energy storage system is analyzed. The simulation results show that adding the flywheel energy storage system improves the FM capability of the coal-fired unit to a considerable extent, and the coal-fired unit can decide the flywheel capacity it needs to be equipped with through detailed economic calculations. [ABSTRACT FROM AUTHOR]

This paper focuses on the exponential stability and the resilient state feedback controller design for large‐scale networked control systems under denial‐of‐service attacks. The duration of each denial‐of‐service attack is captured by a logical processor embedded in the controller. The closed‐loop system of periodic sampled‐data control is modelled as an aperiodic sampled‐data control system associated with lower and upper bounds on the duration of the denial‐of‐service attack. Two formal results are demonstrated. The first result is the stability criterion for large‐scale networked control systems under denial‐of‐service attacks obtained by constructing a two‐sided mode‐dependent loop‐based Lyapunov–Krasovskii functional under the action of a prediction‐based controller. The second result presents a criterion based on linear matrix inequalities to design the controller against denial‐of‐service attacks. In particular, iterative algorithms are given for computing the allowable delay upper bound for the system. Finally, the effectiveness of the proposed method is verified by the interconnected power systems of the two areas. [ABSTRACT FROM AUTHOR]

The results of experimental and modeling studies of the distributed generation sources (DG) influence on the occurrence in the Interconnected Power System (IPS) of Ukraine asynchronous modes (AM) caused by accidents in its main electrical network are presented. According to simulation scenarios it was assumed that the DG power was introduced into electrical distribution networks instead of the power units of thermal power plants of the IPS of Ukraine which were destroyed as a result of missile attacks by the Russians. In the absence of information about DGs, certain generalizations and assumptions are made regarding the possibility of DG groups modeling of in the form of turbine generators with different inertia constants. Various scenarios of the accidents occurrence and the functioning of relay protection and anti-emergency automation devices were considered. Conducted studies results show that the DG introduction into distribution electrical networks does not contribute to the AM occurrence in the main electrical network of the IPS of Ukraine. References 11, figures 10, tables 3. [ABSTRACT FROM AUTHOR]

Ensuring stable power system performance is crucial for reliable grid operation. This study assesses various Load Frequency Control (LFC) strategies, including conventional PID, pole placement, Genetic Algorithm (GA)-optimized PID, Particle Swarm Optimization (PSO)-optimized PID, and an Artificial Neural Network (ANN)-based controller, in single and interconnected power grids. The results reveal that GA- and PSO-optimized PID outperform conventional methods, offering minimal overshoot and fast settling times. Pole placement strikes a balance between response time and stability, while the ANN controller demonstrates adaptability and quick rise times but exhibits higher overshoot and longer settling times compared to the optimization techniques. Tie-line bias control aids in frequency stabilization but presents challenges with overshoot and prolonged settling times. Notably, PSO-optimized PID emerges as a promising solution, effectively mitigating overshoot and achieving rapid frequency recovery. This study underscores the importance of tailored control strategies for optimal LFC, which are essential for enhancing power system stability and efficiency. Future research should explore the potential of advanced techniques, such as deep learning and reinforcement learning, to further improve control performance. [ABSTRACT FROM AUTHOR]

Recent improvements in renewable energy sources (RESs) and their extensive use in the power industry have created significant issues for their operation, security, and management. Due to the ongoing reduction of power system inertia, maintaining operational frequency at its nominal value and minimizing tie-line power variations constitute essential variables for these improvements. A novel improved frequency stabilization approach based on modified fractional order tilt controller is presented for interconnected diverse power systems with integration of sea wave energy, photovoltaic, wind, energy storage system and biodiesel generator. The fractional order tilt integral double derivative (FOTIDD2) is a novel controller that is developed to address the frequency stabilization problems of a hybrid power structure that is integrated with sources of clean energy and devices for storing energy. A recent optimization algorithm inspired by human behavior called mother optimization algorithm (MOA) is applied to adjust the coefficient of the proposed cascaded controller. The FOTIDD2 controller was compared with other control methods in terms of its transient performance, in order to determine its effectiveness. Further, the mother optimization algorithm results are compared with those of sine cosine algorithm (SCA), fox optimization algorithm (FOA), and grey wolf optimization (GWO). FOTIDD2 controller was found to be more effective than PID controller in respect of reducing overshoot (Osh) by 79.31%, 83.78% and 67.99%, improving time settlement by 33.22%, 29.87%, and 22.45% and reducing undershoot (Ush) by 79.13%, 89.34%, and 86.90% for the (∆F1), (∆F2), and (∆Ptie), respectively. [ABSTRACT FROM AUTHOR]

This paper designs a multi-agent-based intermediate observer for malfunction and state estimation of a multi-area interconnected power system. By building a simplified linear model of the power systems, a distributed malfunction observer based on intermediate variables is designed to achieve the estimation of actuator and sensor malfunction signals while considering the system's own and neighboring output estimation errors. The method overcomes the dependence of the conventional observer on the matching condition of the observer and calculates the gain of the observer by solving the linear matrix inequality. Eventually, through an example of simulation, the effectiveness of the design is verified. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This present article examines the frequency control of a dual-area interconnected hybrid power system that integrates conventional as well as non-conventional sources with additional support from electric vehicles. The complicated, non-linear behavior of the system adds to the grid's already high level of complexity. To navigate this complex environment, it becomes essential to develop a resilient controller. In this respect, a robust secondary controller is developed to handle the problem. The controller is developed while taking into account the intricate design of the contemporary power system. An extensive comparison between well-established controllers is presented to verify the efficacy of the proposed controller. An AI-based optimization technique, namely, COVID-19, is employed to obtain optimal values for different parameters of the controller. This work also investigates the effect of the FACTS device as a static synchronous series compensator (SSSC) on the dynamics of the system. Moreover, it also investigates the role of electric vehicles (EVs) and an SSSC on system stability. Further, the developed system is subjected to significant load variations and intermittent solar and wind disturbances to check the response of the optimal controller under dynamic conditions. The results demonstrate that the proposed controller reactions successfully handle system disturbances, highlighting the strength of the proposed controller design. Lastly, a case study on an IEEE-39 bus system is carried out to check the optimality of the proposed secondary controller. [ABSTRACT FROM AUTHOR]

In multi-area interconnected power systems (MAIPS), all the plant state's measurement is stiff due to the lack of a device or the cost of the sensor is expensive. To solve this restriction, a novel sliding mode control techniquebased load frequency controller (LFC) is investigated for MAIPS where the estimation states of the system is utilized fully in the switching surface and controller. Initially, a single-phase switching function is suggested to dismiss the reaching phase in traditional sliding mode control (TSMC) approach. Secondly, the MAIPS's unmeasurable variables is estimated by using the suggested observer tool. Next, a new single phase robustness load frequency sliding mode controller (SPRLFSMC) for the MAIPS is established based on the support of the observer instrument and output data only. The entire plant's stability is ensured through the Lyapunov theory. Even though the plant's variables are not measured, the obtained results in the simulation display that the frequency remains in the nominal domain under load instabilities on the MAIPS. The simulation results for a three-area interconnected electricity plant verify the preeminence of the anticipated SPRLFSMC over other current controllers with respect to settling time and overshoot. [ABSTRACT FROM AUTHOR]

The intermittent and fluctuating nature of active power output from wind power significantly affects the Load Frequency Control (LFC) in a power grid based on active power balance. To address this issue, this paper proposes a cloud-based intelligent PI controller designed to enhance the performance of LFC in smart grids with large-scale wind power integration. By using the error and the rate of change of error as the antecedent inputs of the cloud model-based controller and the tuning values of P and I as the consequent outputs of the cloud model, adaptive online tuning of the PI parameters is achieved. Based on the control rules of LFC in interconnected power grids and considering the uncertainty of wind power's active power output, the membership cloud parameters are designed, which effectively solves the problems of poor parameter robustness in traditional PI control and significant human influence on membership degrees in Fuzzy PI control. A simulation model of a dual-area interconnected power grid with wind power for LFC was built using Matlab/Simulink. Two typical disturbances, namely random fluctuations in wind power and sudden increases/decreases in load, were simulated. The simulation results demonstrate that the cloud model-based intelligent PI controller designed in this paper can effectively track the frequency variations caused by random fluctuations in wind power and exhibits strong robustness. [ABSTRACT FROM AUTHOR]

In this paper, a hybrid load frequency control (LFC) scheme is proposed for multi-area interconnected power systems to decouple the intricate double control objectives, by dividing all subareas into the responsible areas and the free areas. The LFC in the responsible area has the function of regulating both the local frequency and the tie-line power, while the control objective of the LFC in the free area is thus simplified to regulate the local frequency only. Then, addressing the complex network coupling and uncertain dynamics, an integrated LFC controller is proposed for the free areas, which consists of two parts, namely, the coupling attenuation baseline controller and the disturbance compensation controller. The coupling attenuation baseline controller satisfying the predefined bounded L2-Gain condition is derived based on the solution to a multi-player zero-sum differential game. Additionally, a novel generalized integral observer is designed to estimate the system's integrated disturbance, and the corresponding disturbance compensation controller is derived. After that, the ultimately uniformly bounded (UUB) stability of the integrated LFC controller combining baseline controller and disturbance compensation controller is proven rigorously. Finally, the performance superiority of the proposed hybrid LFC scheme is validated by the simulations in challenging operating modes. [ABSTRACT FROM AUTHOR]

Optimal power flow analysis is a calculation to minimize an objective function, namely generation costs or transmission losses by regulating the active power and reactive power generation of each interconnected power system generator by taking into account certain limits. The growth of industrial loads which are dominated by inductive loads requires a fairly large reactive power supply. This reactive power requirement will of course reduce the available power that can be transmitted to the load. Reactive power flow in transmission lines will reduce the active power distribution capacity required by the load. Reactive power flow that is too large can also cause losses. However, this reactive power is also an important component in the stability of the electric power system. For this reason, the flow of active and reactive power in transmission lines needs to be regulated so that the capacity and stability of the electric power transmission system is maintained. [ABSTRACT FROM AUTHOR]

The stable and efficient regulation of voltage and frequency is a critical issue associated with the functioning of modern power system network having renewable integration. This manuscript focuses on the concurrent regulation of voltage and frequency in a power network comprising multiple generating sources. Herein, along with conventional thermal and diesel plants, renewable generations from different sources have been considered such as wind and solar photovoltaic (PV) resources. Further, in a fresh attempt, the authors have modeled wind and solar PV generation using two different stochastic modeling methods concerning combined voltage and frequency loops in the regulated power system model. Furthermore, the novel Leader Harris Hawks Optimized Model Predictive Controller (MPC‐LHHO) has been applied to concurrently minimize the voltage and frequency deviations in the given power network. To address the intermittent nature of load and renewable generations, various auxiliary frequency controllers, such as the unified power flow controller (UPFC) and electric vehicle (EV) integration with the grid, have been implemented. The robustness of the proposed control method has been successfully validated through diverse scenarios of random loadings. [ABSTRACT FROM AUTHOR]

The paper deals with the structure of under-frequency load shedding (UFLS) relays in the interconnected power system (IPS) of Ukraine. The equivalent power system model to study the UFLS operation is developed, and UFLS configuration scenarios considering the requirements of ENTSO-E, are configured. The frequency stability for different scenarios of UFLS settings considering planned and emergency active power imbalances are studied. The plots illustrating the frequency change in the power system under these conditions are presented. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The integration of nonconventional energy sources such as solar, wind, and fuel cells into electrical power networks introduces significant challenges in maintaining frequency stability and consistent tie-line power flows. These fluctuations can adversely affect the quality and reliability of power supplied to consumers. This paper addresses this issue by proposing a Proportional–Integral–Derivative (PID) controller optimized through a hybrid Particle Swarm Optimization–Artificial Hummingbird Algorithm (PSO-AHA) approach. The PID controller is tuned using the Integral Time Absolute Error (ITAE) as a fitness function to enhance control performance. The PSO-AHA-PID controller's effectiveness is evaluated in two networks: a two-area thermal tie-line interconnected power system (IPS) and a one-area multi-source power network incorporating thermal, solar, wind, and fuel cell sources. Comparative analyses under various operational conditions, including parameter variations and load changes, demonstrate the superior performance of the PSO-AHA-PID controller over the conventional PSO-PID controller. Statistical results indicate that in the one-area multi-source network, the PSO-AHA-PID controller achieves a 76.6% reduction in overshoot, an 88.9% reduction in undershoot, and a 97.5% reduction in settling time compared to the PSO-PID controller. In the dual-area system, the PSO-AHA-PID controller reduces the overshoot by 75.2%, reduces the undershoot by 85.7%, and improves the fall time by 71.6%. These improvements provide a robust and reliable solution for enhancing the stability of interconnected power systems in the presence of diverse and variable energy sources. [ABSTRACT FROM AUTHOR]

The hybrid AC/DC grid, based on a significant share of renewable energy sources, is gradually becoming an essential aspect of the modern energy system. The integration of intermittent renewable generators into contemporary energy systems is accompanied by the decommissioning of power plants containing synchronous generators. Consequently, this leads to a reduction in system inertia and an increase in the risk of stability disruption. The abrupt disconnection of the primary generator or power line can result in an unanticipated mismatch between power generation and consumption. This discrepancy can trigger substantial and swiftly evolving alterations in power distribution, angular speed, load flow, and the frequency of generators. The risks of an energy system collapse can be mitigated through automation, enabling rapid adjustments to generation and load capacities, as well as power flows, in the electrical network. This article justifies the utilisation of a power control method for high-voltage power line interconnections. The technology of hydro storage power plants and measurements of voltage phasors are employed. The potential for easing power flow restrictions and realising substantial economic benefits is supported by the results obtained using simplified dynamic model of the Baltic power system and Nord Pool electricity market model. [ABSTRACT FROM AUTHOR]

A hybrid approach is proposed for an interconnected system's load frequency control mechanism. The proposed hybrid method combines the reptile search algorithm and honey badger algorithm methods. Commonly, it is named as the RSA–HBA technique. The proposed approach aims to reduce frequency discrepancies, improve transient response, and establish a foundation for the application of advanced optimization techniques. The overarching goal is to enhance power system stability and adaptability to dynamic conditions and contribute valuable insights to the field of power system control. Here, consider the two-area system with generation plants like distributed generation, (i.e., solar, wind turbine), thermal, hydro, and gas generation systems. The proposed method avoids faster disturbances with limited dynamics. Also, the RSA–HBA technique is used to improve the desired controller settings. Moreover, a high-voltage DC tie line is used to model the interconnected system. The proposed technique is implemented in the MATLAB software and compared with existing methods. When compared to alternative salp swarm optimization (SSA), SOA, and FFA techniques currently in use, the proposed approach performs better. From the simulation, the electric vehicle system provides a lower frequency variation and a lower variation of tie-line power, i.e., − 0.0019 MW. [ABSTRACT FROM AUTHOR]

With the integration of large-scale wind power into the power grid, the impact on system stability, especially the issue of low-frequency oscillations caused by small disturbances, is becoming increasingly prominent. Therefore, this paper proposes a damping quantitative analysis method for regional interconnected power systems incorporating large-scale wind power. Using the cross-entropy particle swarm optimization (CE-PSO) algorithm, the control parameters of wind turbines are optimized to suppress low-frequency oscillations in interconnected systems. The method begins with the state equation of the interconnected power system in two regions; it deduces the characteristic polynomial of the interconnected system, including wind farms, and takes into account the influence of wind power integration on the electrical connectivity of the system. Subsequently, the influence of wind turbine control parameters on the system is quantified, and a quantitative analysis model of the impact of wind power integration on system damping characteristics is constructed. Based on this, an optimization model for wind turbine control parameters is established, and the CE-PSO algorithm is utilized to achieve suppression of low-frequency oscillations in interconnected power grids with wind power integration. Finally, the accuracy and effectiveness of the proposed method are verified through a typical electromagnetic transient simulation model of the two-region interconnected power system. [ABSTRACT FROM AUTHOR]

The overall electricity consumption of electrolytic aluminum and ferroalloy loads is significant, and some of these loads have dispatch potential that can be used to locally absorb wind power while reducing dependence on conventional thermal power. To characterize the uncertainty of wind power, a fuzzy set of wind power forecasting error probability distribution based on the Wasserstein distance was first established, and the approximate radius of the fuzzy set was corrected under extreme scenarios. By introducing joint chance constraints, the inequalities of uncertain variables were established at the lowest confidence level to improve the reliability of the model. Next, a two-stage distributed robust optimal scheduling model for source-load coordination was developed. In the first stage, wind power forecasting information was fully utilized to schedule the electrolytic aluminum load and optimize unit commitment. In the second stage, the uncertainty of wind power output was considered to schedule the ferroalloy load and optimize unit output. The model was approximately transformed into a mixed-integer linear programming problem and solved using a sequential algorithm. The IEEE 24-bus system was used for case validation. The validation results show that the model can effectively improve wind power absorption capacity, reduce overall operating costs, and achieve a balance between low carbon emissions and robustness. [ABSTRACT FROM AUTHOR]

In the operation and control of power systems, load frequency control (LFC) plays a critical role in ensuring the stability and reliability of interconnected power systems. Modern power systems with significant penetration of highly variable and intermittent renewable sources present new challenges that make traditional control strategies ineffective. To address these new challenges, this paper proposes a novel LFC strategy that employs a cascaded fractional-order proportional integral-fractional-order proportional integral derivative with a derivative filter (FOPI-FOPIDN) as a controller. The parameters of the FOPI-FOPIDN are optimised using a variant of the particle swarm optimization (PSO) in the literature called ADIWACO. The effectiveness and scalability of the proposed strategy are validated by extensive simulations conducted on two- and three-area test systems and performance comparisons with recent LFC control strategies in the literature. The performance metrics used for the evaluation are ITAE values, deviations in the power flows in the tie-lines, and deviations in the frequencies of the control areas with the power systems subjected to diverse load and RES generation disturbances in several experimental scenarios. Governor dead band, communication time delay, and generation rate constraints are considered in one of the scenarios for more realistic evaluation. Again, the controller's robustness to uncertain model parameters is validated by varying the parameters of the three-area test system by ± 50%. The simulation results obtained confirm the controller's robustness and its superiority over the comparison LFC strategies in terms of the above performance metrics. [ABSTRACT FROM AUTHOR]

The primary goal of enhancing automatic generation control (AGC) in interconnected multi-area power systems is to ensure high-quality power generation and reliable distribution during emergencies. These systems still struggle with consistent stability and effective response under dynamic load conditions despite technological advancements. This research introduces a secondary controller designed for load frequency control (LFC) to maintain stability during unexpected load changes by optimally tuning the parameters of a Proportional–Integral–Derivative (PID) controller using pelican optimization algorithm (POA). An interconnected power system for ith multi-area is modeled in this study; meanwhile, for determining the optimal PID gain settings, a four-area interconnected power system is developed consisting of thermal, reheat thermal, hydroelectric, and gas turbine units based on the ith area model. A sensitivity analysis was conducted to validate the proposed controller's robustness under different load conditions (1%, 2%, and 10% step load perturbation) and adjusting nominal parameters (R, Tp, and Tij) within a range of ±25% and ±50%. The performance response indicates that the POA-optimized PID controller achieves superior performance in frequency stabilization and oscillation reduction, with the lowest integral time absolute error (ITAE) value showing improvements of 7.01%, 7.31%, 45.97%, and 50.57% over gray wolf optimization (GWO), Moth Flame Optimization Algorithm (MFOA), Particle Swarm Optimization (PSO), and Harris Hawks Optimization (HHO), respectively. [ABSTRACT FROM AUTHOR]

Presently, aside from conventional power, wind energy is considered an important power source in electrical power supply systems. The prime factor affecting electrical power supply systems is the blackout of electrical power for load demand-supply. Therefore, the safe operation of interconnected large power systems integrated with wind energy cannot be carried out without understanding the system’s behavior during abnormal and emergencies. In power generation systems, failure of the conventional generating units (CGUs) and wind turbine generating units (WTGUs) will lead to service interruption and subsequent disconnection of load points. This paper analyzes the impact of frequent failures of the CGUs and WTGUs on the output power systems. A Sequential Monte Carlo Simulation (SMCS) method and the Frequency and Duration (F&D) method are extremely effective for estimating the variation of risk indices when additional wind turbine generators are incorporated into the generation system. The results demonstrate the variation of reliability indices in the adequacy systems when additional WTGUs are incorporated into the generation system. [ABSTRACT FROM AUTHOR]

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Maintaining stability in modern power systems is challenging due to complex structures, rising power demand, and load disturbances. The integration of renewable energy sources further threatens stability by causing imbalances between generation and demand. Conventional load frequency stabilization methods fall short in such scenarios. This paper proposes an optimal fractional‐order proportional‐integral‐derivative‐acceleration (FOPIDA) controller, enhanced by a robust adaptive neuro‐fuzzy inference system (ANFIS), to improve load frequency control and reliability in power systems with wind and solar generators. First, the dynamical model of a multi‐area interconnected power system, including a thermal power plant, wind turbine, and solar photovoltaic generators, is developed. A decentralized ANFIS‐FOPIDA controller is then designed for load frequency control objectives. The gains of this controller are optimized using the whale optimization algorithm (WOA), focusing on frequency deviation and tie‐line power exchange. Simulations on a New England IEEE 10‐generator 39‐bus power system demonstrate the approach's effectiveness under various disturbances, including random load‐generation disturbances and nonlinear generation behaviors. Comparisons with other strategies, such as fractional order (FO) beetle swarm optimization algorithm (FOBSOA)‐FOPIDA, WOA‐PIDA, and WOA‐ANFIS‐PIDA, and recent control approaches highlight the superior performance of the WOA‐ANFIS‐FOPIDA method in enhancing power system stability. [ABSTRACT FROM AUTHOR]

Owing to the challenges of unstable generation and random load disturbance in new energy power system, this paper integrates the battery energy storage model into the traditional load frequency control (LFC) framework, and proposes a LFC scheme based on adaptive global sliding mode control to stabilize the frequency of power systems amid unpredictable load frequency deviation. First of all, the nonlinear time-varying function is added to the sliding mode surface to make the system globally robust. Then, an adaptive sliding mode control law is crafted to dynamically adjust the frequency variations caused by random load disturbance. Moreover, by utilizing the improved Lyapunov function and Bessel-Legendre inequality, the stabilization criteria of multi-area interconnected power system are built. Finally, the efficacy of the proposed method is demonstrated through single and double area LFC simulation experiments with the common system parameters. [ABSTRACT FROM AUTHOR]

The modern era is witnessing a growing demand for sustainable and eco-friendly power sources. An interconnected power system capable of seamlessly integrating electric vehicles and renewable energy resources is being considered as a viable solution. However, this technology has some drawbacks, such as its lower system inertia, which limits its ability to respond to load capabilities. To overcome this issue, a Hybrid Energy Storage System (HESS) can be integrated with new techniques to enhance performance. This paper proposes a new Quasi Opposition Arithmetic Optimization Algorithm (QOAOA) optimized Fractional Order Proportional Integral Derivative with Filter (FOPIDN) controller cascaded One Plus Tilted Derivative (1 + TD) controller with HESS of super-capacitor (SC) and Redox Flow Battery (RFB) to mitigate frequency and tie-line power variations in a multi-area restructured smart-grid system. The proposed controller's performance is evaluated under various conditions, such as load fluctuations, wind speed variations, solar irradiation, Governor Dead Band (GDB), and generation rate limitations. For unsystematic load the improvement in the performance of the proposed controller indicated by maximum variation in frequency ( Δ f 1 , Δ f 2 , Δ f 3 ) and power change on the tie-lines ( Δ P tie 12 , Δ P tie 13 ) over FOPIDN controller is (98.65%, 48.78%, 52.52%) and (75.0%, 76.1%). The system performance is also analyzed when HESS devices are integrated into the three-area system, taking into account the varying nature of wind speed and solar irradiation. The improvement in performance indicated by maximum variation in frequency ( Δ f 1 , Δ f 2 , Δ f 3 ) and power change on the tie-lines Δ P tie 23 by incorporating HESS in the system is (45.21%, 33.33%, 29.59%) and 46.95% over without energy storage system. The proposed controller's outcomes are validated using real-time hardware-in-the-loop (HIL) simulation with OPAL-RT. [ABSTRACT FROM AUTHOR]

For Years, Experts have expressed growing concerns that critical infrastructures are vulnerable to cyberattacks. Remotely transmitted malware and viruses can compromise interconnected power systems, airports, hospitals, military systems, and any Internet-connected computers used to manage critical functions. As the world becomes more digitalized, integrating new communication technologies offers unlimited possibilities for the accumulation of information, creating a fundamental dependence on proper functioning in all areas of society. As such reliance could offer great opportunities for a smart and efficient world, it also poses significant threats to the operation of critical infrastructures and vital facilities. Specifically, safety issues from illegal acts that violate the integrity, availability, and confidentiality of information in cyberspace are expected to be the central theme in the digitalized world. Exploitation of cyberspace to advance political, social, and military agendas is of particular concern. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative method for load frequency control (LFC) in multi-area interconnected power systems vulnerable to denial-of-service (DoS) attacks. The system is modeled as a switching system with two subsystems, and an adaptive control algorithm is developed. Initially, a dynamic linear data model is used to model each subsystem. Next, a model-free adaptive control strategy is introduced to maintain frequency stability in the multi-area interconnected power system, even during DoS attacks. A rigorous stability analysis of the power system is performed, and the effectiveness of the proposed approach is demonstrated by applying it to a three-area interconnected power system. [ABSTRACT FROM AUTHOR]

In this article, an event-triggered finite-time neural control strategy is proposed for nonlinear power systems with unknown disturbances and static var compensator (SVC). We first transform the power system with SVC into a three-dimensional uncertain nonlinear system and then extend it to an n -dimensional uncertain nonlinear system. The disturbance observer is established to estimate external disturbances and the unknown nonlinear terms are approximated by the radial basis function neural networks. Moreover, to avoid the complexity explosion problem in the traditional backstepping method, the command filtering technique is adopted, and the error caused by the command filters is compensated. The adaptive event-triggered finite-time controller ensures that all signals are bounded in finite time and excludes Zeno phenomena. In the end, the simulation for the two-area interconnected power system with SVC is presented to verify the availability and feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

This article aims at designing a robust wide-area damping controller (WADC) to address the problems associated with communication failures. The proposed controller is a state feedback-based controller, which uses generators' states as the controller inputs. The structure of the proposed controller's feedback gain matrix is a combination of two feedback gain matrices to achieve adequate robust performance over different disturbances and communication losses. These two feedback gain matrices are; full-scale feedback gain matrix and decentralized scale feedback gain matrix. Both models are designed by considering all generators' states are available at the controller input side. However, both matrices' structures are different from each other. The conventional LQR state feedback control technique is used to design the full-scale matrix. On the other hand, the decentralized scale matrix is computed using a structurally constrained H 2 -norm optimization technique to acquire the required structure. The full-scale model gives robust performance under different faults. Whereas, the decentralized scale matrix will result robust performance against communication failures. Therefore, to achieve superior performance under all conditions, the proposed controller can be used. To show the efficacy of the proposed controller, it is compared with different existing controllers and the results are illustrated. Simulation studies are conducted on well-known IEEE 39-bus and 68-bus test systems to validate the robustness of the proposed controller considering different faults and communication failures. [ABSTRACT FROM AUTHOR]

As the percentage of renewable energy source within the energy production mix has expanded, it is become gradually difficult to determine the appropriate values for controller gains and model parameters. Controlling system frequency of interconnected power system during sudden load disturbance requires careful consideration of the controller gain values and small signal stability model parameters. This study proposes an innovative methodology for ascertaining controller gain values and model parameters for plug-in electric vehicles (PEVs) in load frequency control (LFC) applications. Proposed method uses the root locus (RL) approach to find the suitable controller gain values and model parameters for PEVs. This paper offers a thorough mathematical description of the proposed RL approach. Routh approximation method is used for reduced-order modelling (ROM), which comprises thermal and PEV systems, to reduce complexity of higher-order system while designing controllers. Fractional-order proportional-integral-derivative controller (FO-PID) is proposed, and its parameters are adjusted using particle swarm optimization (PSO) tool. To validate the efficacy of suggested method, a comprehensive comparison of time response parameters and performance indices (PI) is carefully carried out. Also, the various PEVs state of charge (SOC) levels is investigated, and effects of these levels are studied in LFC with robustness analysis of controller. The proposed method for determining gain value is highly reliable and efficient, outperforming existing methodologies in the literature. [ABSTRACT FROM AUTHOR]

In this work, two area systems of renewable energy sources (RES), such as tidal, wind and solar, are interconnected with the deep residual network (DRN) controller in a microgrid. The DRN controller is used to control load frequency, which is optimally designed by green anaconda optimization (GAO) algorithm. The GAO algorithm is used to optimally select the DRN layers that improve the control of a two-area interconnected power system. GAO algorithm is utilized for the parameter section of a DRN controller in the interconnected power system with two areas, which provides optimal solutions based on the natural behaviour of green anacondas. The reason for choosing the GAO method is that it has high capability in the exploration and exploitation phase, thus creating effective tuning of controllers. The DRN controller is chosen because it has fewer additional parameters and increases the accuracy level, thus enhancing control of the two areas. The proposed model is implemented in MATLAB tool, and the results are compared with the existing methods of proportional-integral derivative-whale optimization algorithm (PID-WOA), PID-Harris hawks optimization (PID-HHO) and two degrees of freedom (2DOF)-PID (2DOF-PID). The comparison results indicate that the proposed GAO-based DRN controller achieves 98% efficiency and 95% frequency deviation, thus providing high-performance over counterpart methods. [ABSTRACT FROM AUTHOR]

In this paper, the issue of exponential stabilization and sampled-data controller design for Takagi–Sugeno fuzzy large-scale networked control systems is studied by using the reduction-based ordinary differential equation prediction method. For the problem that matrices cannot be multiplied directly during the process of designing the sampled-data controller in this paper, a matrix dimensional transformation method is proposed. Firstly, a type of two-sided mode-dependent loop-based Lyapunov–Krasovskii functional is constructed, which compensates for the large delay and makes fuller use of the information in sampled-data interval. Secondly, the proposed method is used to give the design scheme of an aperiodic sampled-data controller, and furthermore, an iterative algorithm to verify the effectiveness of the requested control gains is provided. Finally, two coupled vehicle pendulum systems and two-area interconnected power systems are applied to demonstrate the efficiency of the presented approach. [ABSTRACT FROM AUTHOR]

This paper aims to develop a robust (1+PD)-PID cascade controller for the frequency stabilization of a multi-area Interconnected Power System (IPS). The operational performance of the proposed controller is studied by introducing a Step Load Disturbance (SLD) of 10% in area 1 of the considered power system model. For fine-tuning the proposed controller, the Butterfly Optimization Algorithm (BFOA) is employed. The superior performance of the proposed controller is validated against other controllers available in the literature. Furthermore, to enhance power system performance, a High-Voltage DC (HVDC) line is implemented in the test system model. The simulation results confirm the improvement in system performance with the incorporation of the HVDC line. To assess the robustness of the proposed controller, a sensitivity test is conducted, which validates its robustness. [ABSTRACT FROM AUTHOR]

This paper presents a new time-domain multi-objective function approach for solving load frequency control issue in an interconnected power system. The performance of interconnected power system in each area is validated for overshoot and settling time values of frequency change and tie-line power exchange. An objective function is created with the goal of enhancing proportional integral derivative (PID) controller settings by reducing overshoot and achieving faster time-domain settling times. The efficiency of the proposed time-domain multi-objective function is evaluated in a twoarea thermal power plant using a nature-inspired cuckoo search optimization (CSA) technique. By comparing the time-domain simulation results of the test system with the existing integral error-based objective functions IAE, ISE, ITAE, and ITSE, the proposed objective function is validated. Further, a sensitivity analysis were carried out to analyze the robustness of the proposed multi-objective function under various uncertain conditions. [ABSTRACT FROM AUTHOR]