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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]

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]

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]

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]

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]

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]

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]

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]

As renewable energy resource (RES) penetration levels increase within a grid, power networks become more vulnerable to low inertia issues. Additionally, the proliferation of electric vehicles (EVs) has already made a substantial impact on grid dynamics. To ensure reliable frequency regulation in networked microgrid systems, this study introduces a fractional-order controller that integrates tilt-integral-derivative with filter and hybrid fractional-order controllers into a unified entity. The proposed controller adeptly manages various disturbances and frequency control within interconnected microgrid systems, comprising renewable resources, energy storage units, and synchronous generators. Furthermore, the utilization of the particle swarm optimization algorithm is used for optimizing controller settings in microgrid systems. Existing EVs contribute additional functionality to interconnected microgrid systems. A case study is conducted considering installed photovoltaic (PV) panels, wind turbines, and distributed EVs in a multi-area interconnected microgrid. Simulation results underscore the effectiveness of the proposed controller, demonstrating its superiority over existing controllers in the literature in terms of enhancing system dynamic performance. [ABSTRACT FROM AUTHOR]

To systematically analyze the impact of the DC frequency limit controller (FLC) configuration scheme on the frequency characteristics of asynchronous interconnected power grids with renewable energy integration, a comprehensive frequency analysis model for three-area asynchronous interconnected power grids including the FLC is proposed. The model is based on the SFR model considering renewable energy integration and includes a simplified model of the DC FLC. A rigorous validation of the rationality and stability of the model is achieved through detailed mathematical calculations and pole-zero analysis. Taking the local power grids as an example, the established model is used to study the difference between single- and double-sided configuration of the DC FLC, the relationship between the increase in the renewable energy penetration rate and the frequency characteristics of each regional power grid, and the influence of DC FLC configuration on the maximum acceptance ratio of renewable energy. Through data comparison and theoretical analysis, the influence of FLC configuration on the frequency characteristics of each region of the asynchronous power grid under renewable energy integration is obtained. The results show that the configuration of a bilateral FLC on the DC line has more advantages in alleviating the complementary power disturbance at both ends and obvious limitations on the non-complementary power disturbance at both ends. Compared with the configuration of the bilateral FLC, the configuration of a unilateral FLC on the weak grid has a larger proportion of renewable energy acceptance. When the DC FLC power transmission capacity is sufficient, the weak grid and the adjacent two asynchronous grid DC tie lines are configured with a single-sided FLC, and the weak grid is theoretically connected to the renewable energy penetration rate of up to 100%. [ABSTRACT FROM AUTHOR]

In the modern era, the demand for an interconnected power system, which can integrate electric vehicles and renewable energy sources is increasing day by day. The primary goal of this demand is to make a sustainable and green power source, which can be fulfilled by utilizing Electric vehicles and renewable energy sources. However, there are some demerits of this technology, its lesser system inertia and hence it is not sufficient to respond to the required load capabilities. Further, the approach of electric vehicles with moving batteries can enable higher performance and resolve the issue. In this current analysis, the vehicles to grid idea (V2G) technique has been discussed, which can react as automatic generation control (AGC) in a three-area deregulated environment including hydro, thermal, and gas turbine units. In this type of power grid, all the sources such as Solar, wind, geothermal, and DEG power is also incorporated. To grip various ambiguities, the current study proposed a cascade combination of Interval type-2 fuzzy and Fractional Order Proportional-integral-derivative (FOPIDN) controllers. Further, the current work proposed a modified quasi-opposition Arithmetic Optimization Algorithm (QOAOA) to tune the scaling factor and membership function of an interval type-2 fuzzy FOPIDN controller. To discuss the significance of the anticipated controller, the estimated outputs have been compared with previously reported controllers and optimization techniques. The effect of constant and variations in DG, the penetration level of (PEVs) in various operating modes, subjected to step and random load disturbances have been focused on. Finally, to validate the outcomes of the proposed controller, a real-time (RT) hardware-in-the-loop (HIL) simulation has been adopted by using OPAL-RT. [ABSTRACT FROM AUTHOR]

Network frequency is considered to be one of the most crucial parameters that strongly affect the stability and economic achievements of interconnected electric power grids. System frequency usually fluctuates and deviates from the nominal values due to random and continuous load changes over time, affecting the electric equipment to significantly decrease efficiency and increase instability. A Load-Frequency Control (LFC) strategy has been proposed to solve this problem. This study compared several different control strategies, namely Fuzzy Particle Swarm Optimization (Fuzzy-PSO), Proportional Integral Derivative (PID), Fuzzy-PID, Fuzzy-Proportional Integral (PI), PSO-PI, and FPID to investigate the effectiveness of intelligent hybrid LFC controllers. The above controllers were simulated on a three-area interconnected power network with the participation of renewable energy sources. Taking into account different load cases, the Fuzzy-PSO-PID controller obtained frequency deviations in the range of 0.0015 to 0.002 Hz. The settling time was about 10 s to reach zero frequency error in each area. With the above controller quality parameters, the Fuzzy-PSO-PID controller provided better quality than the other controllers. A comparative numerical simulation in MATLAB/Simulink for various load change scenarios revealed the effectiveness of hybrid smart controllers, such as the Fuzzy-PID-PSO, outperforming the traditional ones. [ABSTRACT FROM AUTHOR]

Available transfer capability (ATC) is an important measurement index to evaluate the security margin of interconnected power grids and serve as a reference for the transmission right transaction. In modern power systems, ATC is affected by the transmission network topology, renewable power output uncertainty, and load demand uncertainty. Traditional works usually model the power source-load uncertainty by using robust optimization, interval optimization, or chance-constraint optimization, which cannot fully reflect the probabilistic distribution of the daily source-load uncertainty. This paper proposes an ATC assessment methodology based on the typical stochastic scenarios of renewable output and load demand of multiarea power systems. Furthermore, the conditional generative adversarial network (CGAN) algorithm is adopted to generate and select representative scenario sets based on historical raw data, which can fully reflect the usual operating condition of a system with high renewable energy penetration. The scenario set that is fed into the ATC assessment model can fully characterize the impact of source-load uncertainty on daily ATC. Finally, the proposed method is verified by a modified three-area IEEE 9-bus system and a real-world provincial power system. [ABSTRACT FROM AUTHOR]

Modern power systems are confronted with widespread concern on the frequency stability issue due to the widespread integration of randomly fluctuating renewable resources. To address the above concern, this work introduces a load-frequency-control (LFC) scheme based on a parameter tuning strategy for fractional-order proportional–integral–derivative (FOPID) controller. Firstly, a two-area interconnected power system (IPS) model, including thermal, hydro, solar, wind, and gas power generator and a hydrogen-based energy-storage unit, is established. Then, a FOPID controller is designed for this IPS model, and an improved gradient-based optimizer (IGBO) is developed to adaptively regulate the parameters of the FOPID controllers. Finally, the effectiveness of the offered LFC scheme is tested through load disturbance and renewable energy fluctuations test scenarios and provides a comparison and robustness analysis among different schemes. The test results validated that the offered LFC scheme can effectively suppress the frequency fluctuations of the IPS and has excellent robustness. [ABSTRACT FROM AUTHOR]

This document is a guest editorial from the journal IET Generation, Transmission & Distribution. It emphasizes the need to improve the reliability and resilience of modern power systems in the face of various threats. The editorial highlights the importance of modeling, assessing, and enhancing the reliability and resilience of power grids that are increasingly incorporating grid-edge resources. The document also provides a summary of the papers included in a special issue of the journal, which cover topics such as planning reliable energy systems, analyzing power grid operations, and enhancing service restoration and grid-support load response. Additionally, the text discusses the issue of equity in power distribution system restoration processes and proposes a model called the equity-aware power distribution system restoration model. The model aims to balance equity and resilience in restoring power after outages by focusing on fair distribution of energy resources while maintaining operational efficiency. The text also includes brief biographies of several authors who have contributed to the field of power electronics and power system reliability. [Extracted from the article]

This article emphasizes the intermittent characteristics of renewable energy sources (RESs) and explores the role of forecasting in improving the performance of the automatic generation control (AGC) mechanism of the interconnected power system. Due to hybridization of power system basic AGC controller (PID, TID, and ID‐T) are insufficient to stabilized the system parameters. So, a new type of fractional order integral tilted derivative controller (FIDN‐T) has been proposed, which give better performance in terms of settling time, undershoot and overshoot in case of RESs with real data forecasting also. FIDN‐T has been compared with some existing controller which give the results better than basic controller. In order to optimize the different parameters of the proposed controller, a new modified Opposition‐based Sea‐horse Optimization (OSHO) algorithm has been proposed. The OSHO is compared with a few existing, well‐known meta‐heuristic algorithms to show its superiority. The analysis has been conducted under different operating conditions, including step and random disturbances as well as the IEEE‐39 bus, to verify the robustness as well as adaptability of the suggested controller. The comprehensive results of the studies provide strong evidence in support of the effectiveness and efficacy of the suggested control methods and suggest that it has the potential to be implemented in real‐world power systems for improved performance and stability. [ABSTRACT FROM AUTHOR]

Summary: As the share of wind power keeps on increasing, the interaction between synchronous and wind generators pose a challenging issue on power system stability. In order to investigate the impact of wind penetration on stability of power system, appropriate modeling of wind energy conversion systems (WECSs) is necessary. Moreover, it is needed to comprehensively study the impact of wind penetration on power system oscillations. This paper presents a didactic approach for integrating a doubly fed induction generator (DFIG)‐based wind farm from SimPower Systems library to a five‐area 68‐bus power system modeled in Simulink. Inter‐area oscillations with and without wind power penetration are investigated for their characteristics. Renewable energy sources are connected to the grid via power electronics converters at the cost of a reduction in inertia. The concept of virtual synchronous generator (VSG) produces virtual inertia by exchanging active power with the power system. The impact of superconducting magnetic energy storage (SMES) and DFIG on enhancing damping performance of inter‐area is investigated. The increase in damping ratios of inter‐area oscillatory modes verifies the enhancement in small signal stability by connecting SMES and DFIG to the power system. The usage of SMES operating in VSG mode to improve the dynamic stability with highly erratic wind profile is also investigated. The developed MATLAB/SIMULINK‐based DFIG model is simple to use and can be expanded to build efficient controllers. The fidelity of the DFIG model and VSG technology is verified in real time by Opal‐RT (OP4510). [ABSTRACT FROM AUTHOR]

In interconnected modern power systems, renewable energy sources, HVDC transmission lines, and energy storage devices are growing after being installed globally with development in power electronics and communication technology. Low-frequency inter-area oscillations (0.2–0.8 Hz) have a severe influence on the operation of an interconnected power system due to the numerous generators. This paper provides a comprehensive literature review of the wide-area measurement system-based wide-area damping control systems with operational uncertainties, including signal communication effects, such as time delay, packet loss, noise, and disorder, , on damping control performance. Different wide-area damping control techniques are investigated, emphasizing their advantages inadequacies and categorized according to vital features. In recent years, the resilience of wide-area damping control systems to cyber-physical attacks has recently been brought back to the researcher's consideration because of the opportunities produced by information-communication technologies and the renewed interest in installing renewable energy sources. This paper provides recent developments in methods of damping performance enhancement that deserve further study in cyber-physical power systems. Overall, the present study is helpful for academicians and researchers to identify the objectives in the area of cyber-physical power systems to enhance the wide-area damping performance. [ABSTRACT FROM AUTHOR]

In recent years, the use of renewable energy in power systems has increased significantly. This affects the inertia of the system. Also, the intermittent nature of renewable energy sources causes voltage and frequency fluctuations. This study suggests electric vehicles (EVs) as energy storage options for the diverse sources of an interconnected power system to resolve these issues. This paper also introduces the internal model control controller for load frequency control of an interconnected power system considering flexible AC transmission system and energy storage devices. The present study considers a two-area interconnected power system with thermal, hydro, and gas-generating units. The gain of the proposed controller is optimized using the particle swarm optimization technique. The advantages of the proposed controller have been highlighted by analyzing the results with conventional proportional–integral–derivative and proportional–integral–derivative with filter controller. The model includes superconducting magnetic energy storage (SMES), capacitive energy storage (CES), and redox flow batteries to support the voltage and frequency changes. A static synchronous series compensator compensates the tie-line. The performance of the SMES and CES units is compared with the proposed EVs used as energy storage units in this paper. The simulation results show that system performances improve significantly in the presence of the proposed energy storage unit. The behavior of the proposed controller is also analyzed under equal and unequal apf values. Finally, the sensitivity of the proposed controller is examined by varying the system parameters in a wide range. [ABSTRACT FROM AUTHOR]

This article discusses the intermittent nature of renewable energy sources and electric vehicles for improved load frequency control mechanism of interconnected power system. This research also looks at the impact of communication latency on system stability and sustainability. The mathematical modelling and analysis of the studied proposed system, a two-area interconnected hybrid power system, includes a thermal plant, hydro plant, and gas plant in each area. Moreover, both control areas also incorporate sporadic solar and wind power plants as well as electric vehicles for case study purposes. A novel cascade fractional-order integral-derivative and tilt controller has been designed for the analysed system. A new modified Quasi-Opposition Reptile Search Algorithm (QORSA) is also proposed to optimise the different parameters of controller. To demonstrate its superiority, the QORSA is compared with some recent prominent meta-heuristic algorithms. Furthermore, the effectiveness and efficacy of the proposed control approach has been analysed in comparison with existing controllers as well as some other research work under diverse conditions like step and random disturbances. The comprehensive results studies show the overall better and improved dynamic performance analysis for anticipated hybrid power system. Finally, the proposed methodology is validated through real-time experimental analysis by means of Opal-RT platform for its practical feasibility. [ABSTRACT FROM AUTHOR]

This paper proposes an approach for segmentation of power systems to prevent uncontrolled islanding. With the development of microgrids (MGs) and increased penetration of renewable energy sources (RESs) in the power system, it is necessary to consider the effect of MGs and the stochastic behaviour of RESs in the controlled islanding process. First, the enormous search space for finding the boundary points is reduced by the clustering of the coherent generators and the buses which are placed in sections that cannot be separated from the coherent groups. Then, linear AC power flow is defined as a sub‐problem and solved by linear programming to satisfy the power system and MG constraints. In this step, an optimization model is defined, and a mixed‐integer linear programming (MILP)‐based model is suggested to find cut‐sets and islands arrangement with reduced load shedding. In view of the fact that the fluctuation of RESs may have the significant effects on the power imbalance, to cover the uncertainties a scenario based stochastic simulation is considered. Finally, the effect of uncertainties on cut‐sets and load curtailment is evaluated. The effectiveness of the proposed methodology is demonstrated by the simulation on the test system. [ABSTRACT FROM AUTHOR]

In the modern power system, the use of renewable energy sources is increasing rapidly, which makes the system more sensitive. Therefore, it requires effective controllers to operate within the allowable ranges. The existing techniques based on cascaded controllers implemented so far for load frequency control have the advantage of improving the system response. However, this makes the system a more complex and time-consuming process. This makes the system more straightforward, makes it easy to optimize PID parameters, and provides results in acceptable ranges. This paper attempts to solve the load frequency control (LFC) problem in an interconnected hybrid power system with a classical PID controller employing the tunicate swarm algorithm (TSA). This algorithm is used for two areas of an interconnected hybrid power system: thermal, hydro, nuclear, and wind. The PID controller parameters are optimized by tunicate swarm algorithm using integral time absolute error (ITAE) based objective function. To show the robustness of the proposed TSA algorithm, a sensitivity analysis is performed for four case studies ranging from 20% to 30% load increments and decrements. The performance of the proposed TSA algorithm has been compared with the well-known optimization algorithms, particle swarm optimization (PSO), artificial bee colony (ABC), and arithmetic optimization algorithm (AOA) in terms of overshoot, undershoot, and settling time. The simulation results show that the proposed TSA has better optimization capability than PSO, ABC, and AOA in terms of overshoot, undershoot, and settling time. [ABSTRACT FROM AUTHOR]

This paper aims to present an optimization method for the best bus selection (BBS) in the large‐scale power systems in order to send the input signals to the damping controllers. In this regard, a submodular function is first defined to calculate the distance between the unstable vectors of the system and the controllability Gramian leading to find a set of buses for installation of the damping controllers. Based on the results obtained from the BBS approach, the number of candidate buses will be increased to deal with the inter‐area oscillations by introducing an event‐triggered based auxiliary scheme. According to the candidate buses and the power system operating condition, the most critical buses of the candidate set is allowed to participate as the input signals of damping controllers to reduce the inter‐area oscillations. The proposed algorithm is implemented on an interconnected large power system in the presence of wind and solar farms. These renewable energy resources are connected to the power system through the multi‐terminal DC network, so that their power products can be damped and injected into the power grid by designing the damping controllers. The simulations have been analysed using MATLAB software under different scenarios. [ABSTRACT FROM AUTHOR]

The frequency stability of interconnected power systems becomes quite challenging when incorporating renewable energy sources (mostly wind power). Distributed model predictive control (DMPC) is an effective method to maintain stable grid frequency and realize power system load frequency control (LFC). This paper proposes a two-layer robust DMPC for the LFC of an interconnected power system. In the scheme, the wind power penetrating the power grid is largely affected by the environment condition, and it is taken as an uncertain disturbance to the power system. The two-layer robust DMPC consists of a nominal DMPC controller and an ancillary DMPC controller. The nominal DMPCs coordinate with each other in achieving the systemwide LFC objective, where the systemwide objective is a strict convex combination of the local LFC objectives. The nominal optimization problems are solved supposing the wind power fluctuation is zero. The ancillary DMPC generates the actual control signal for each generation unit based on signals which are transmitted from the nominal DMPC controller. The simulation on a four-area interconnected power system demonstrates the effectiveness of the proposed algorithm in alleviating the frequency deviation caused by varying the load and uncertain wind power fluctuation. [ABSTRACT FROM AUTHOR]

Nowadays, most of modern power systems integrate concentrated renewable energy resources power plants like solar and wind parks in addition to central conventional plants. The output power from these concentrated renewable energy resources varies continuously according to weather conditions like solar irradiance value or wind speed and direction, the variation for their output power may be in mega watts. In this work, Robust secondary load frequency controller (LFC) based on one of artificial intelligent technique which called interval type-2 fuzzy logic controller (IT2FLC) has been proposed for two-area multi-source interconnected power system with central solar park power plants in each area while considering non-linearities in the power system. IT2FLC has accommodated vagueness, distortions and imprecision for the power system input signals which caused by weather fluctuations and system non-linearities. In addition to LFC, another controller based also on IT2FLC has been proposed to control the output power from the central solar parks in each area of generation during cloudy periods instead of maximum power point tracking method (MPPT) in order to enhance the stability for the power system during disturbance periods. In order to enhance the performance of the proposed LFC, particle swarm optimization technique (PSO) has been utilized to optimize the proposed LFC gains to minimize the steady state error, over/under shooting value, settling time and system oscillation for the investigated power system frequency. The performance and the superiority of the proposed PSO tuned IT2FLC is evaluated and compared with another LFC based on PSO tuned cascaded PID controller while applying severe demand load and solar irradiance changes. the simulation has been carried out using matlab/simulink program. [ABSTRACT FROM AUTHOR]

The challenge of controlling frequency becomes greater as the complexity of a power network increases. The stability of a power system is highly dependent upon the robustness of the controller. This paper presents automatic generation control (AGC) of a four-area interconnected power system along with integrated renewable energy sources of PV and wind energy. The designed model is a challenge given the increased penetration levels of PV and wind along with a thermal-hydropower system. The addition of a hydropower system as a fourth type results in the pole of the open loop system of the hydropower system being located at the right half side of the s-plan. This demands a robust control. A novel MPC-(1 + PIDN) is designed for high-order interconnected areas (HOIA) to stabilize the frequency in a robust way. The salp swarm algorithm is adopted to optimize the parameters of the PIDN controller. The performance of the proposed controller under HOIA is tested in a unbalanced load environment with uncertainty in the power system. The proposed controller can effectively handle the frequency disruption by stabilizing it in 0.86 s for Area-1, 1.08 s for Area-2, 0.81 s for Area-3, and 0.84 s for Area-4 with an average time of 0.89 s for all the areas, whereas the average time for GWO: PI-PD, MPC/PI and GA-PI is 3.48 s , 10.36 s and 18.47 s , respectively. The results demonstrate the effectiveness of the controller when compared to other controllers. [ABSTRACT FROM AUTHOR]

Existing interconnected power systems (IPSs) are being overloaded by the expansion of the industrial and residential sectors together with the incorporation of renewable energy sources, which cause serious fluctuations in frequency, voltage, and tie-line power. The automatic voltage regulation (AVR) and load frequency control (LFC) loops provide high quality power to all consumers with nominal frequency, voltage, and tie-line power deviation, ensuring the stability and security of IPS in these conditions. In this paper, a proportional integral derivative (PID) controller is investigated for the effective control of a four-area IPS. Each IPS area has five generating units including gas, thermal reheat, hydro, and two renewable energy sources, namely wind and solar photovoltaic plants. The PID controller was tuned by a meta-heuristic optimization algorithm known as a gradient-based optimizer (GBO). The integral of time multiplied by squared value of error (ITSE) was utilized as an error criterion for the evaluation of the fitness function. The voltage, frequency, and tie-line power responses of GBO-PID were evaluated and compared with integral–proportional derivative (GBO-I-PD), tilt integral derivative (GBO-TID), and integral–proportional (GBO-I-P) controllers with 5% step load perturbation (SLP) provided in each of the four areas. Comprehensive comparisons between GBO-PID and other control methodologies revealed that the proposed GBO-PID controller provides superior voltage, frequency, and tie-line power responses in each area. The reliability and efficacy of GBO-PID methodology were further validated with variations in the turbine time constant and speed regulation over a range of  ± 25%. It is evident from the outcomes of the sensitivity analysis that the proposed GBO-PID control methodology is very reliable and can successfully stabilize the deviations in terminal voltage, load frequency, and tie-line power with a shorter settling time in a four-area IPS. [ABSTRACT FROM AUTHOR]

This paper proposes a maiden intelligent controller design that consists of a fuzzy proportional-integral-derivative-double derivative (FPIDD) controller whose parameters are fine-tuned using the Gradient-Based Optimization algorithm (GBO). The proposed FPIDD2 regulator is employed as a secondary regulator for stabilizing the combined voltage and frequency loops in a two-area interconnected power system. The proposed FPIDD2 controller is tested in a two-area hybrid system, with each area comprising a mix of traditional (thermal, gas, and hydraulic power plants) and renewable generation units (wind and solar power). Additionally, the proposed controller takes into account system nonlinearities (such as generation rate limitations and governor deadband), system uncertainties, and load/renewables changes. The dynamic responses of the system demonstrate that FPIDD2 has superior ability to attenuate the deviations in voltage and frequency in both areas of the system. In the investigated hybrid system, the suggested FPIDD2 is compared to a GBO-tuned integral derivative tilted (ID-T) controller and FPID controller. As a fitness function for the GBO, the criteria of minimizing the integral time absolute error (ITAE) are applied. The results are presented in the form of MATLAB/SIMULINK time-domain simulations. The simulation outcomes prove that the presented controller has an outstanding performance compared with the other control strategies in the dynamic response of the system in terms of rising and settling times, maximum overshoot, undershoot values and ITAE. The ITAE value of the FPIDD2 regulator tuned by the GBO technique was enhanced by 90.9% with the GBO-based ID-T and 55.4% with GBO-based FPID controllers. [ABSTRACT FROM AUTHOR]

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Load-frequency-control (LFC) is employed for frequency stability and balanced power flow among control-areas. Inverters are becoming critical assets in modern power networks with increasing renewable energy. As these inverter-based resources prevail, the system inertia decreases, leading to potential frequency instability problems. Grid-forming (GFM) inverter development and applications are gaining significant attraction because of their ability to maintain quality power-grid operations. GFM inverter, acting as a voltage-source-converter, adjusts its output frequency by contributing a portion of the load change to reduce the frequency deviations. The virtual synchronous generator (VSG) control mechanism for GFM is implemented in this work. A two-area interconnected power system model emulating an enhanced IEEE 9-Bus system is developed and simulated in MATLAB-Simulink® for analysis. Secondary controllers are applied in each LFC and GFM-loop of the proposed LFC-GFM system with a magnetotactic-bacteria-optimization (MBO) algorithm for simultaneously tuning these parameters. The proposed control strategy's effectiveness is verified by comparing simulation results with the basic LFC system under varying inverter penetration levels. The simulated dynamic responses verify the efficacy of the controlled penetration of the GFM inverter in the proposed LFC-GFM system with enhanced damping characteristics, improving small-signal stability and reducing settling time by 43.46% and frequency deviation by 55.5%. [ABSTRACT FROM AUTHOR]

The original article can be found online at https://doi.org/10.1038/s41598-024-76980-z.Correction to: Scientific Reportshttps://doi.org/10.1038/s41598-024-76980-z, published online 27 October 2024In the original version of this Article, Abdul Rahman Afzal was omitted as a corresponding author. The correct corresponding authors for this Article are Amil Daraz and Abdul Rahman Afzal.The original Article has been corrected.By Amil Daraz; Hasan Alrajhi; Ahmed N. M. Alahmadi; Mohit Bajaj; Abdul Rahman Afzal; Guoqiang Zhang and Kunpeng XuReported by Author; Author; Author; Author; Author; Author; Author [Extracted from the article]

With an emphasis on a three-region system, this paper explores automatic generation control within a conventional framework. Area 2 uses thermal-thermal sources, Area 3 uses gas-thermal sources, and Area 1 uses thermal-biodiesel sources. IPD(1 + I) is a unique cascade controller that combines integral-proportional-derivative (IPD) components with one-plus-integral (1 + I) components. To find the best gains and settings for the IPD(1 + I) controller, a meta -heuristic method called the African Vulture Optimization Algorithm (AVOA) is applied. Reducing the integral squared error (ISE), as determined by the performance index (Pi), is the main goal. The performance of the IPD(1 + I) controller is evaluated by contrasting it with a range of secondary controllers. Hybrid Peak Area-ISE (hPA-ISE), a novel performance metric, is also assessed in addition to the conventional ISE. The incorporation of renewable energy sources, such solar thermal energy and solid oxide fuel cells, significantly improves the system's performance. Interestingly, under normal conditions, the IPD(1 + I) controller's parameter settings continue to work for both sinusoidal and random load situations, obviating the need for additional tuning. [ABSTRACT FROM AUTHOR]

Frequency, tie-line power, and the terminal voltages of synchronized generators must all be kept within prescribed limits to ensure the stability of an interconnected power grid through combined automatic generation control (AGC) and automatic voltage regulator (AVR) loops. Thermal power plants, electric vehicles, and renewable energy sources—including solar and wind, geothermal, and solar thermal power plants—form the two-area integrated power system in present research. A new cascade controller named the cascaded proportional integral derivative (PID) and fractional-order PID (CPID-FOPID) controller is proposed for the first time, whose performance is compared with the PID and FOPID controller. The results show that the proposed cascade controller outperforms PID and FOPID in delivering superior dynamic characteristics, including short settling times and low oscillation amplitudes. A new metaheuristic algorithm named the coot algorithm was applied to optimize the parameters of these controllers. The suggested controller outperforms FOPID in the combined AGC and AVR problem under uncertain conditions (random load disturbance, variable input of solar irradiation, and wind power). Robustness of the controller is tested with significant variation in the turbine time constant of the thermal and geothermal power plant. In this study, authors also investigated the best possible coordination between the superconducting magnetic energy storage (SMES) and gate-controlled series capacitor (GCSC) devices to control both voltage and frequency simultaneously. The effect of communication time to the power system is analyzed in this study. Additionally, the obtained results are satisfactorily validated using OPAL-RT real-time digital simulator. [ABSTRACT FROM AUTHOR]

In this article, a fractional-order proportional-integral-differential (FOPID) controller and its modified structure, called a MFOPID controller, are presented. To guarantee optimal system performance, the gains of the proposed FOPID and MFOPID controllers are well-tuned, employing the Jellyfish Search Optimizer (JSO), a novel and highly effective bioinspired metaheuristic approach. The proposed controllers are assessed in a hybrid system with two domains, where each domain contains a hybrid of conventional (gas, reheat, and hydro) and renewable generation sources (solar and wind). For a more realistic analysis, the presented system model includes practical limitations with nonlinear characteristics, such as governor dead zone/band (GDZ/GDB), boiler dynamics, generation rate limitation/constraint (GRL/GRC), system uncertainties, communication time delay (CTD), and load changes. The suggested methodology outperforms some newly developed heuristic techniques, including fitness-dependent optimizer (FDO), sine-cosine algorithm (SCA), and firefly algorithm (FA), for the interconnected power system (PS) of two regions with multiple generating units. Furthermore, the proposed MFOPID controller is compared with JSO-tuned PID/FOPID and PI controllers to ascertain its superiority. The results signify that the presented control method and its parametric optimization significantly outperforms the other control strategies with respect to minimum undershoot and peak overshoot, settling times, and ITSE in the system's dynamic response. The sensitivity analysis outcomes imply that the proposed JSO-MFOPID control method is very reliable and can effectively stabilize the load frequency and interconnection line in a multi-area network with interconnected PS. [ABSTRACT FROM AUTHOR]

Since modern power systems are susceptible to undesirable frequency oscillations caused by uncertainties in renewable energy sources (RESs) and loads, load frequency control (LFC) has a crucial role to get these systems' frequency stability back. However, existing LFC techniques may not be sufficient to confront the key challenge arising from the low-inertia issue, which is due to the integration of high-penetration RESs. Therefore, to address this issue, this study proposes an optimized intelligent fractional-order integral (iFOI) controller for the LFC of a two-area interconnected modern power system with the implementation of virtual inertia control (VIC). Here, the proposed iFOI controller is optimally designed using an efficient metaheuristic optimization technique, called the gray wolf optimization (GWO) algorithm, which provides minimum values for system frequency deviations and tie-line power deviation. Moreover, the effectiveness of the proposed optimal iFOI controller is confirmed by contrasting its performance with other control techniques utilized in the literature, such as the integral controller and FOI controller, which are also designed in this study, under load/RES fluctuations. Compared to these control techniques from the literature for several scenarios, the simulation results produced by the MATLAB software have demonstrated the efficacy and resilience of the proposed optimal iFOI controller based on the GWO. Additionally, the effectiveness of the proposed controller design in regulating the frequency of interconnected modern power systems with the application of VIC is confirmed. [ABSTRACT FROM AUTHOR]

Reducing the emissions of greenhouse gases has directed energy sectors toward using renewable energy sources (RESs) and decreasing the dependency on conventional energy sources. Recently, developing efficient load frequency control (LFC) schemes has become essential to face the reduced inertia due to RESs installations. This paper presents a modified tilt fractional order (FO) integral–tilt FO derivative with a fractional filter (TFOI-TFODFF or namely TI λ -TD μ FF) LFC method. Although the proposed controller uses the same elements of standard controllers, it adopts FO control capabilities and flexibilities, including the tilt, FO integral, FO derivative, and FO filter. Thence, a new control structure is obtained, merging the advantages of both controllers. Moreover, the proposed TFOI-TFODFF controller employs two control loops to be able to mitigate low-frequency as well as high-frequency disturbances in power grids. Additionally, a new modified marine predator algorithm (MMPA) is proposed for optimally tuning the parameters of the proposed TFOI-TFODFF LFC method. The performance of the MMPA is enhanced in terms of initialization and exploitation phases using the chaotic maps and weighting factor. A two-area interconnected power system case study is implemented with wind and photovoltaic RESs and electric vehicles (EVs) contribution. The proposed TFOI-TFODFF LFC is compared with the FOPID, TID, TI-DF, and FOTPID controllers, wherein the proposed TFOI-TFODFF has offered superior performance of the proposed controller. Moreover, the proposed modified MPA is compared with the original MPA and other competitive optimization algorithms, and statistical analyses are carried out through parametric and nonparametric tests. [ABSTRACT FROM AUTHOR]

• Reviewed on AGC challenges with various control approaches in power systems. • A detailed survey presented on AGC with renewable energy sources. • AGC problems with integration of energy storage devices & FACTS have addressed. • Research gaps and directions for future power systems is presented. This paper presents a comprehensive literature review and an up-to-date bibliography on automatic generation control (AGC)/load frequency control (LFC) of interconnected power systems integrated with conventional, renewable and sustainable energy sources. The objective of AGC is to quickly stabilize the deviations in frequency and tie-line power following load fluctuations. Various state-of-the-art AGC strategies have not been reviewed so far, hence, an appropriate review on recent AGC mechanism is indispensable. Salient points discussed and highlighted in this survey include different power system models with/without renewable sources, and integration of sophisticated concepts such as microgrids (MGs), smart grids (SGs), distributed generations (DGs), high voltage direct current (HVDC) links, and power system after liberalization. Furthermore, various examined control approaches like traditional controllers, intelligent methods, adaptive, robust, optimal, variable, soft computing, centralized and decentralized methods with their advantages and disadvantages have been pondered and compared. Further, AGC challenges with incorporation of flexible AC transmission systems (FACTS), energy storage devices and high penetration of renewable sources for modern and future power systems have been addressed. This review concludes the new control schemes namely, electrical vehicles (EVs), fractional-order (FO) based controllers, fuzzy aided controllers, and cascaded controllers with case studies. Research gaps and directions for future developments AGC of power systems are also discussed. [ABSTRACT FROM AUTHOR]

The effective and reliable operation of an interconnected power system (PS) is a major concern, because of the large amount of power contribution from the intermittent renewable energy sources to the power grid. Energy storage (ES) devices are employed to enhance the reliability of the PS operation. Electric vehicles (EVs) are a novel type of distributed ES device that may be utilized to compensate for power imbalances. This paper discusses the participation of EVs for combined frequency and voltage control under conventional PS along with a thermal, hydro, realistic dish‐Stirling solar thermal system (RDSTS). Appropriate physical constraints such as governor dead band and generation rate constraints are equipped with thermal and hydro plants, and communication delay between the generating unit and load dispatch center is considered. An aggregate EVs model, RDSTS, and a new cascade controller named fractional‐order proportional‐derivative with filter coefficient cascaded with tilt‐integral‐derivative (CFOPDN‐TID) controller are provided in all areas for various studies. An artificial flora algorithm is employed to determine the optimal value of the various controller parameters under several scenarios. The system dynamics of the CFOPDN‐TID controller outperform the proportional‐integral‐derivative (PID) and TID controllers under various conditions. The incorporation of EVs improves the system performance in terms of less settling time, and peak deviation, and reduce oscillations. The system performance degrades with increases in the communication time delay of the EVs. The integration of RDSTS into the system provides better dynamics than the dish‐Stirling solar thermal system. Numerous studies have been conducted to validate the robustness of the proposed CFOPDN‐TID controller. [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]

Electricity has become one of the most essential components of establishing a quality standard of living in any country. Consequently, considerable work has been focused on designing a sophisticated load frequency control (LFC) system. However, in light of limited resources and real-world challenges, computationally based control algorithms that are more effective and less expensive remain critically needed. Thus, this paper employs a modified honey badger algorithm (HBA) in conjunction with the concepts of Lévy flight and inertia weight to optimize the parameters of a new cascaded two-degree-of-freedom fractional-PID structure coupled with a proportional derivative (2DOF + FOPIDN)-PD controller to solve LFC problems in an interconnected power system (IPS) comprising conventional and renewable energy sources (RES). The proposed control technique is applied to a two-area IPS under diverse load conditions and in the presence of nonlinear elements and electronic devices. The proposed method is evaluated with respect to a range of performance metrics, such as settling time, undershoots, and error criteria values. The collective performance of the established control scheme indicated that the suggested control approach provides excellent reliability under various load condition scenarios, sensitivity tests, and perturbations, proving the system's efficacy and dependability. [ABSTRACT FROM AUTHOR]

By coordinating the operation of regionally interconnected virtual power plants (VPPs), the growing penetration problem of renewable energy sources (RESs) into the power system can be addressed. This study presents an interactive trading cooperation model of regionally interconnected VPPs using bilateral contracts. The proposed model maximizes overall electricity market social welfare (SW) (i.e., maximization of consumer benefits while minimizing energy costs). The focus of the proposed approach is to design and develop a parallel energy exchange cooperation model of interconnected VPPs, ensuring the operational efficiency and reliability of interconnected power systems over the planning horizon. Given that adjacent VPPs may have differences in their energy generation and usage patterns, a scenario tree method is used to model the uncertainties associated with solar irradiation and load demand. A case study of two interconnected VPPs is used, the operational scenario is designed, and the corresponding computational model is developed. The results highlight that the proposed approach gives VPPs the option to utilize their internal network's maximum capacity. As a result, there will be less reliance on the main grid for interconnected VPPs, and an improvement in key performance indicators, including the cost of the VPPs systems and renewable power variations. [ABSTRACT FROM AUTHOR]

Modern structures of electrical power systems are expected to have more domination of renewable energy sources. However, renewable energy-based generation systems suffer from their lack of or reduced rotating masses, which is the main source of power system inertia. Therefore, the frequency of modern power systems represents an important indicator of their proper and safe operation. In addition, the uncertainties and randomness of the renewable energy sources and the load variations can result in frequency undulation problems. In this context, this paper presents an improved cascaded fractional order-based frequency regulation controller for a two-area interconnected power system. The proposed controller uses the cascade structure of the tilt integral derivative (TID) with the fractional order proportional integral derivative with a filter (FOPIDN or PI λ D μ N) controller (namely the cascaded TID-FOPIDN or TID-PI λ D μ N controller). Moreover, an optimized TID control method is presented for the electric vehicles (EVs) to maximize their benefits and contribution to the frequency regulation of power systems. The recent widely employed marine predators optimization algorithm (MPA) is utilized to design the new proposed controllers. The proposed controller and design method are tested and validated at various load and renewable source variations, as is their robustness against parameter uncertainties of power systems. Performance comparisons of the proposed controller with featured frequency regulation controllers in the literature are provided to verify the superiority of the new proposed controller. The obtained results confirm the stable operation and the frequency regulation performance of the new proposed controller with optimized controller parameters and without the need for complex design methods. [ABSTRACT FROM AUTHOR]

Security and stability control system (SSCS) in power systems involves collecting information and sending the decision from/to control stations at different layers; the tree structure of the SSCS requires more levels. Failure of a station or channel can cause all the execution stations (EXs) to be out of control. The randomness of the controllable capacity of the EXs increases the difficulty of the reliability evaluation of the SSCS. In this study, the loop designed SSCS and reliability analysis are examined for the interconnected systems. The uncertainty analysis of the controllable capacity based on the evidence theory for the SSCS is proposed. The bidirectional and loop channels are introduced to reduce the layers and stations of the existing SSCS with tree configuration. The reliability evaluation and sensitivity analysis are proposed to quantify the controllability and vulnerable components for the SSCS in different configurations. By aiming at the randomness of the controllable capacity of the EXs, the uncertainty analysis of the controllable capacity of the SSCS based on the evidence theory is proposed to quantify the probability of the SSCS for balancing the active power deficiency of the grid. [ABSTRACT FROM AUTHOR]

The transition towards decarbonized power systems requires accounting for the impacts of the climate variability and climate change on renewable energy sources. With the growing share of wind and solar power in the European power system and their strong weather dependence, balancing the energy demand and supply becomes a great challenge. We characterize energy compound events, defined as periods of simultaneous low renewable production of wind and solar power, and high electricity demand. Using a logistic regression approach, we examine the influence of meteorological and atmospheric drivers on energy compound events. Moreover, we assess the spatial coherence of energy compound events that pose a major challenge within an interconnected power grid, as they can affect multiple countries simultaneously. On average, European countries are exposed to winter energy compound events more than twice per year. The combination of extremely low temperatures and low wind speeds is associated with a higher probability of occurrence of energy compound events. Furthermore, we show that blocked weather regimes have a major influence on energy compound events. In particular, Greenland and European blocking lead to widespread energy compound events that affect multiple countries at the same time. Our results highlight the relevance of weather regimes resulting in synchronous spatial energy compound events, which might pose a greater risk within a potential fully interconnected European grid. [ABSTRACT FROM AUTHOR]

The power system long-term expansion planning is a computer-intensive problem as demands a varied set of studies especially considering the increasing deployment of intermittent renewables. In the case of the Brazilian power sector planning, the responsible institutions mostly use proprietary software. This paper presents the multiyear two-stage academic generation and transmission expansion planning software, called CARTHER, developed by the authors in order to provide the academy an open-source and non-commercial software, with a friendly interface and with several applications for expansion planning of hydrothermal systems with high intermittent renewables penetration. CARTHER is then calibrated for a case study in the Brazilian power sector, considering the most recent governmental goals for renewable energies for the horizons of 2030, 2040, 2050 and 2060. The results demonstrate the functionality and the qualitative capacity of CARTHER optimization under the expansion's criteria of flexibility and reliability in the face of the intermittent renewables penetration. [ABSTRACT FROM AUTHOR]