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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 renewable energy sources, how we can improve the stability of the new energy power system has become an urgent issue pursued by scholars. In this paper, a joint scheduling method for pumped storage units (PSUs) and renewable energy sources (RESs) considering frequency deviation and voltage stiffness constraints is proposed. First, the analytical expression of the frequency deviation constraint is derived based on the primary frequency regulation model. Then, the voltage stiffness constraint is constructed to describe the system's capability of maintaining the voltage magnitude. Finally, to minimize the renewable energy abandonment caused by stability requirements, the joint scheduling model for PSUs and RESs is established. The application of the method ensures that the frequency deviation of the modified IEEE 39 bus system is less than 0.5 Hz, while the voltage stiffness remains above 0.9. [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]

This paper aims to investigate the dynamic stability of a multi-area power system. A three-degree-of-freedom-based fractional order proportional integral derivative-proportional resonant (FOPID-PR) controller is designed and implemented in the multi-area power system to stabilize the frequency and the fluctuations of power after the disturbance occurs. For improving the system dynamics, the parameters of the three degrees of the FOPID-PR controller are optimized using an artificial humming bird (AHB) optimization. AHB optimization is used in the controllers to fine-tune the gain. It will identify any minor adjustments in the FOPID-PR controller's value. The proposed methods are implemented in the five-area power system. Five areas, diesel generator, aqua electrolyzer, fuel cell (FC), wind turbine, hydro, and bio-mass-based power generator, are given with their dynamic responses by conceding frequency deviations in each area. The results are obtained under random, stochastic, and step loads, including the frequency and tie-line characteristics. The proposed method results in reduced ITAE of 61.04%, 70.76%, 81.9% and 86.42% for SSA, DE, GWO and PSO, respectively. [ABSTRACT FROM AUTHOR]

This study focuses on the automatic generation control (AGC) system, which is crucial for maintaining balance between power generation and demand in power systems. The implementation of the AGC system needs to be more precise due to the increasing uncertainty surrounding renewable energy sources (RESs) and changes in demand. The objective of this study is to investigate the AGC functions in a two-area hybrid power system that combines a PV system with a reheat thermal system. To improve system performance, we utilize a proportional-integral (PI) controller. We utilized a recently developed optimization method, RIME, for tuning controller parameters. This technique has not been studied before in AGC processes. Furthermore, the optimization procedure utilizes a modified version of the integral of time-multiplied absolute error (ITAE) objective function. The study compares the performance of the RIME-tuned PI controller under various scenarios, including changes in thermal system load, load variations in both areas, and robustness considerations, with well-known techniques in the literature, such as the black widow optimization algorithm (BWOA), the salp swarm algorithm (SSA), the shuffled frog leaping algorithm (SFLA), the firefly algorithm (FA) and the genetic algorithm (GA). Our comparative study demonstrates that the proposed controller outperforms state-of-the-art approaches in terms of overshoot values and damping durations for both system frequency and tie-line power changes. The study provides valuable information on the effectiveness of the RIME-tuned PI controller in controlling AGC processes in complex hybrid power systems.

The increase of new energy permeability increases the complexity of power system frequency control. Frequency regulation assisted by energy storage can alleviate this problem to some extent. However, due to the security and economic constraints of energy storage operation, frequency regulation measures need to be more targeted. In this paper, a primary frequency regulation method of power grid assisted by energy storage based on frequency response characteristics is proposed. Firstly, based on the model of frequency regulation assisted by energy storage, the frequency modulation integrated control method of auxiliary energy storage with inertia and droop is selected. Through the correlation analysis of rate of change of frequency and frequency deviation to frequency modulation requirements, frequency regulation demand zoning rules based on frequency response characteristics are designed. Then, according to the partition judgment corresponding to different frequency modulation requirements, the energy storage active power output mode is dynamically adjusted to respond to the uncertainty of frequency modulation requirements. On this basis, aiming at the contradictory relationship between frequency modulation demand and energy storage output demand, energy storage output strength and its cycle life, the multi-objective optimization problem is designed and solved to balance. Finally, the simulation results verify that the proposed method can effectively reduce the depth of charge and discharge of energy storage on the basis of ensuring the frequency modulation effect of power grid.

The mismatch between generated power and load demand often leads to undesirable fluctuations in the frequency and tie-line power change of a power system. To mitigate this problem, the implementation of a control process known as load frequency control (LFC) becomes essential. The objective of this study is to optimize the parameters of the LFC controller for a two-area power system consisting of a reheat thermal generator and a photovoltaic power plant. A proportional–integral (PI) controller is employed to damp the oscillations that occur in the frequency and tie-line power change. A newly developed meta-heuristic optimization technique called gorilla troops optimization (GTO) is used for the first time to optimally tune the parameters of the PI controller and improve its performance. The performance of the GTO optimization technique is analyzed under varying load demands, parameter variations, and nonlinearities. Comparative evaluations with different optimization algorithms are performed. The obtained results demonstrate that the proposed GTO-PI controller outperforms the other optimization techniques in terms of reducing the overshoot values in the system frequency and tie-line power change, as well as achieving faster settling times for these oscillations. This research highlights the effectiveness of the GTO-PI controller in LFC, providing improved performance over alternative algorithms. The results underscore the significance of utilizing meta-heuristic optimization techniques for optimal parameter tuning in power system control applications. [ABSTRACT FROM AUTHOR]

The aim of this paper is to propose an enhancement to the primary frequency control (PFC) of the San Cristobal Island hybrid wind–diesel power system (WDPS). Naturally, variable speed wind turbines (VSWT) provide negligible inertia. Therefore, various control strategies, i.e., modified synthetic inertial control, droop control and traditional inertial control, if introduced into VSWT, enable them to release hidden inertia. Based on these strategies, a WDPS has been simulated under seven different control strategies, to evaluate the power system performance for frequency regulation (FR). Furthermore, the student psychology-based algorithm (SBPA) methodology is used to optimize the WDPS control. The results show that modified synthetic inertial control is the most suitable approach to provide FR. However, further exhaustive research validates that droop control is a better alternative than modified synthetic inertial control due to the negligible system performance differences. In addition, droop control does not require a frequency derivative function in the control system. Therefore, the hybrid system is more robust. Moreover, it reduces the steady state error, which makes the power system more stable. In addition, a pitch compensation control is introduced in blade pitch angle control (BPAC) to enhance the pitch angle smoothness and to help the power system to return to normal after perturbations. Moreover, to justify the performance of hybrid WDPS, it is tested under certain real-world contingency events, i.e., loss of a wind generator, increased wind speed, fluctuating wind speed, and simultaneously fluctuating load demand and wind speed. The simulation results validate the proposed WDPS control strategy performance. [ABSTRACT FROM AUTHOR]

A virtual synchronous generator (VSG) strategy can introduce the rotational inertia and damping characteristics of the synchronous generator to the static inverter, e.g., PV, wind generation, and ESS, which are used to enhance the system frequency support characteristics of the micro-grid. However, under various operations of the VSG, the inertia and damping support capabilities are different, and the conventional VSG strategy with a fixed control coefficient sacrifices a certain degree of dynamic regulation performance with less robustness. This research proposes an improved VSG strategy with adaptive inertia and damping coefficients to increase the flexibility of VSG. To this end, a mathematical model is first established to analyze the impact of various parameters on the characteristics of VSG, and then the root trajectory is used to explore the impacts of various rotational inertia and damping coefficients on the stability ofthe VSG system. Second, an improved control strategy with adaptive inertia and damping coefficients is proposed based on the characteristics of the second- order system and the system frequency deviations. Finally, a simulation system with the VSG is constructed based on MATLAB/Simulink. The effectiveness of the proposed control strategy is verified by comparing the simulation results to the conventional control strategy with the fixed control coefficients under over- frequency and under-frequency disturbances. [ABSTRACT FROM AUTHOR]

Installing wind farms in isolated power systems can cause issues regarding frequency control. These issues are due to the variable nature of wind and the characteristics of the grid itself. This research analyzed how frequency deviation is affected by distributing multiple wind farms and how to reduce those deviations by leaving active power reserves in the wind farms. Monte Carlo simulations were used, considering various scenarios where wind penetration was gradually increased while leaving fixed and variable power reserves, using fuzzy control for the latter. The results obtained demonstrate that as wind penetration increases, frequency deviations also increase until they violate the Cuban grid code. These deviations were reduced by implementing reserves in the wind farms, with the best results achieved when using variable reserves. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Engineering Technology is the property of Editorial Department of Electric Power Engineering Technology 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.)

Power system stability relies heavily on load frequency control (LFC) because it ensures that the power generated in a grid matches the load demand. The conventional LFC methods are no longer adequate with the rising use of renewable energy sources like wind and solar power. These resources are intermittent, and their power output varies depending on weather conditions. As a result, incorporating renewable energy resources (RERs) into the LFC system necessitates a different approach. One method is to use advanced control algorithms that can respond quickly to changes in power output. Hence, this article proposes an autoencoder‐based jellyfish optimization developed in this framework to reduce the power outage and control voltage and frequency fluctuations. The LFC system can be optimized by combining autoencoder and jellyfish optimization techniques to effectively handle the variability and unpredictability of RERs while maintaining the power system's stability and reliability. This approach may also result in more efficient and cost‐effective power system operation by reducing the need for conventional power generation and minimizing the impact of RERs on the system. [ABSTRACT FROM AUTHOR]

Because the majority of wind turbines operate in maximum output power tracking mode, power system frequency cannot be supported. However, if the penetration rate of wind power increases, the system inertia related to frequency modulation may decrease. In addition, frequency stability will be severely affected in the event of significant disturbances to the system load. Due to the high penetration of wind power in isolated power systems, this study suggests a coordinated frequency management approach for emergency frequency regulation. In order to prevent the phenomenon of load frequency control in doubly fed induction generators (DFIGs), a unique efficient control scheme is developed. The Cascaded Fractional Model Predictive Controller coupled with Fractional-Order PID controller (CFMPC-FOPID) is developed to provide the DFIG system with an efficient reaction to changes in load and system parameters. The proposed controller must have a robust tendency to respond quickly in terms of minimum settling time, undershoot, and overshoot. Nonlinear feedback controllers are designed using frequency deviations and power imbalances to achieve the reserve power distribution between generators and DFIGs in a variety of wind speed conditions. It makes upgrading quick and easy. In Matlab/Simulink, a simulation model is built to test the viability of the suggested approach.

The adjacent interharmonic pairs or single adjacent interhamonic symmetrical to the fundamental/harmonic component can be caused by the large-scale grid connection of renewable energy. It is usually necessary to confirm the type of adjacent interharmonics to build an accurate calculation model when estimating the frequency components in electric signal. However, the spectrum leakage interferences caused by the grid frequency deviation makes that requirement hard to achieve. Towards the problem, an effective criterion to confirm the type of the adjacent interharmonics and an accurate estimation method of the harmonics and adjacent interharmonics based on the criterion even there is frequency deviation are proposed. Firstly, the spectrum leakage interferences are suppressed to obtain the adjacent interharmonic spectral lines by analysing the relationship of the frequency deviation and spectral lines. Then, the type criterion of the adjacent interharmonics is proposed by comparing the spectrum difference between each type of adjacent interharmonics. Finally, the spectral line equation for each type of adjacent interharmonics are constructed according to the confirmed type to accurately estimate the harmonics and adjacent interharmonics. Even there is frequency deviation, the type of the adjacent interharmnics can be confirmed accurately and a more precise estimation of the harmonics and adjacent interharmonics can be achieved with the proposed method. The accuracy of the proposed method is verified by the simulation.

Abstract With the rapid increase of wind power penetration, the frequency indicators of power system, encompassing frequency deviation and rate of change of frequency (RoCoF), are prone to exceed the pertinent relay thresholds, thus leading to serious power outages. Wind farms can participate in primary frequency regulation (PFR) to alleviate the above problem. However, wind farms reserve capacity (WFRC) presented by overspeed control and pitch angle control is the important factor for frequency safety especially when large disturbance occurs, and it varies obviously in different conditions. Thus, WFRC should be utilized optimally to avoid insufficient or excessive response of wind farms in PFR. To overcome the challenge, this paper proposes frequency‐trajectory‐oriented control (FTOC) for wind farms based on a two‐fold optimization framework, seeking to obtain the best frequency control performances in PFR through realizing the optimal compromise between frequency results and the consumption of WFRC. First, when the frequency indicators deviate significantly from the normal values, the optimal frequency trajectory is planned periodically according to the local standards and operation conditions, thereby minimizing the total consumption of WFRC on the premise of frequency safety. Second, based on model predictive control and a real‐time power system parameters estimator, the total reference power of wind farms, which helps the frequency track the latest planned trajectory, is optimally distributed among wind generators according to their reserve capacity. In this case, through the optimal frequency trajectory planning and tracking, the new method in this paper not only effectively prevents the frequency results from exceeding the local standards under diverse conditions, but also finds the optimal balance among frequency indicators safety, frequency trajectory smoothness, and the reserve capacity consumption of wind power generators. Finally, the simulation results prove the effectiveness and advancement of FTOC.

The load frequency control of a thermal power producing system, the ant colony optimization (ACO) approach adjusted proportional integral derivative (PID) controller is proposed. This work examines the single area thermal power system with/without generation rate constraint. For emergency situations, a PID controller is developed and used to regulate power system characteristics. This study uses the ACO method with the integral time absolute error objective function optimize controller gain values. In addition, the performance of the suggested approach is evaluated by introducing non-linearity components to the power-generating systems under study. Conventional, particle swarm optimization (PSO), and genetic algorithms (GA) approach tuned controller responses are compared with ACO. Fast settling with minimal peak and undershoots in the producing power supply of the system under emergency loading situations demonstrates the superiority of the proposed controller over competing controllers. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Engineering Technology is the property of Editorial Department of Electric Power Engineering Technology 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.)

A method is proposed for measuring the eccentricity of rotating shafts that connect electric motors to various energy transducers. A functional diagram is developed for a device permitting acoustic measurement of shaft eccentricity. The time for shaft compression and the shaft's torsional angles are determined in the cases of zero and maximum eccentricity. [ABSTRACT FROM AUTHOR]

With the rapid increase of wind power penetration, the frequency indicators of power system, encompassing frequency deviation and rate of change of frequency (RoCoF), are prone to exceed the pertinent relay thresholds, thus leading to serious power outages. Wind farms can participate in primary frequency regulation (PFR) to alleviate the above problem. However, wind farms reserve capacity (WFRC) presented by overspeed control and pitch angle control is the important factor for frequency safety especially when large disturbance occurs, and it varies obviously in different conditions. Thus, WFRC should be utilized optimally to avoid insufficient or excessive response of wind farms in PFR. To overcome the challenge, this paper proposes frequency‐trajectory‐oriented control (FTOC) for wind farms based on a two‐fold optimization framework, seeking to obtain the best frequency control performances in PFR through realizing the optimal compromise between frequency results and the consumption of WFRC. First, when the frequency indicators deviate significantly from the normal values, the optimal frequency trajectory is planned periodically according to the local standards and operation conditions, thereby minimizing the total consumption of WFRC on the premise of frequency safety. Second, based on model predictive control and a real‐time power system parameters estimator, the total reference power of wind farms, which helps the frequency track the latest planned trajectory, is optimally distributed among wind generators according to their reserve capacity. In this case, through the optimal frequency trajectory planning and tracking, the new method in this paper not only effectively prevents the frequency results from exceeding the local standards under diverse conditions, but also finds the optimal balance among frequency indicators safety, frequency trajectory smoothness, and the reserve capacity consumption of wind power generators. Finally, the simulation results prove the effectiveness and advancement of FTOC. [ABSTRACT FROM AUTHOR]

A virtual synchronous generator (VSG) strategy can introduce the rotational inertia and damping characteristics of the synchronous generator to the static inverter, e.g., PV, wind generation, and ESS, which are used to enhance the system frequency support characteristics of the micro-grid. However, under various operations of the VSG, the inertia and damping support capabilities are different, and the conventional VSG strategy with a fixed control coefficient sacrifices a certain degree of dynamic regulation performance with less robustness. This research proposes an improved VSG strategy with adaptive inertia and damping coefficients to increase the flexibility of VSG. To this end, a mathematical model is first established to analyze the impact of various parameters on the characteristics of VSG, and then the root trajectory is used to explore the impacts of various rotational inertia and damping coefficients on the stability of the VSG system. Second, an improved control strategy with adaptive inertia and damping coefficients is proposed based on the characteristics of the second-order system and the system frequency deviations. Finally, a simulation system with the VSG is constructed based on MATLAB/Simulink. The effectiveness of the proposed control strategy is verified by comparing the simulation results to the conventional control strategy with the fixed control coefficients under over-frequency and under-frequency disturbances.

Due to the fluctuation of PV power, it is difficult to keep the active power of the PV grid-connected inverter constant. To address the above problems, this paper proposed a new three-level integrated photovoltaic storage machine consisting of a T-type three-level DC/AC converter, a three-level Boost converter and a three-level bi-directional DC/DC converter and related control strategies. The three-level structure allowed for lower switching losses resulting in higher system efficiency and wider voltage range adaptability. In terms of control, frequency differentiation and deviation control were introduced in the control of the energy storage DC/DC converter to achieve frequency regulation of the transient/static support of the active power of the parallel network. The simulation and experiment show that when the frequency fluctuation range is 50.02~49.97 Hz (meeting the national standard), the new optical storage all-in-one machine proposed in this paper can operate stably and be easily realized.

In current electrical power industry, a great number of power electronic devices produce harmonics. Moreover, the fundamental system frequency of a power line can deviate in the cases of fluctuating and periodically varying loads and transients. This frequency deviation introduces further undesirable frequency components in the spectrum. Correct measurement of harmonics under such system frequency deviations has prominent importance for the protection of power electronics devices. For this goal, this paper proposes a new iterative optimization-based algorithm for the estimation of harmonics in these circumstances. The method is based on time-domain Gauss-Newton optimization of distorted power line signal which attains its parameters directly from the spectrum of the signal by employing local extrema of the corresponding spectrum. In the first phase of the algorithm, the deviated system frequency is estimated. In the second phase, the harmonic components are estimated and fine-tuned correspondingly. Case studies show that the proposed method is robust and precisely estimates deviations in the system’s fundamental frequency and measure the amplitudes of harmonic components very accurately. It requires just a stoppage criterion. The computational assessment of the method also shows its time efficiency in identifying harmonics. Thus, it is a very good candidate for real-time harmonic measurements.

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press 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.)

Regression, data classification and function approximation are among the most common applications that make use of machine learning models. However, due to the vast range of applications for machine learning, comprehensive understanding of how to choose a model based on machine learning, as well as how to choose its structure, training method, and performance analysis criterion, is frequently lacking. This key issue is addressed using a well-known load frequency control (LFC) problem which is instrumental in maintaining balance between power generation and load demand. The study relates to developing and contrasting the performance of the Meta heuristic optimization based approach to the artificial neural network (ANN) based machine learning topology for the LFC control against the optimized ANN controller. The selected performance indices are peak time and settling time of the frequency deviation. It is observed that Linear Neural Network (LNN) outperforms Feedforward Neural Network (FNN) and Recurrent Neural Network (RNN). The performance is enhanced when its parameters are optimized by the metaheuristic algorithms. [ABSTRACT FROM AUTHOR]

This paper proposes a novel Improved Artificial Electric Field Algorithm (IAEF)-based AGC in a multi-area power system to minimize the area control error and to obtain an optimal solution. Here, four area AGC systems equipped with the PID controller are examined for the study processes. Also, an optimal gain value for the PID controller is obtained by employing an IAEFA; thus minimizing the area control error (ACE). In addition to this, nine different test functions are employed to evaluate the performances of the proposed IAEF-based AGC of a multi-area power system and are compared with several optimization approaches such as AEF algorithm, BBO Algorithm, PSO Algorithm as well as DE Algorithm. Also, the performance evaluation based on three different simulation strategies such as simulation based on time domain, Random disturbances of the AGC system as well as System Dynamics for maximum frequency deviation and Percentage Improvement for a four area power system. Here, the maximum frequency deviations for four areas are −0.0132, −0.0145, −0.0122 and −0.0120, respectively. Moreover, the percentage improvements with respect to the IAEF with respect to the PID controllers are 67.32%, 57.21%, 47.26% and 55.47%, respectively. The experimental analysis reveals that the proposed approach provides very less tie-line control error and better optimal tuning of the PID controller when compared with all other approaches. [ABSTRACT FROM AUTHOR]

In a constantly and rapidly changing global environment, one of the main priority tasks for every country is preserving, maintaining, and operating an independent and individually robust and stable energy system. This paper aims at researching electrical power systems' (EPSs) behavior during desynchronization from a synchronous area, its stability in islanded mode, and its synchronization. The analysis of EPS behavior was accomplished utilizing numerical simulations in a widely used programming/simulation package. The sudden tripping of the EPS into an isolated island mode with known generation and load values was simulated, analyzed, and discussed. We investigated the behavior of an isolated EPS in the case of the loss of a certain amount of active power, and determined the maximum power that must be available to ensure the reliable operation of the isolated EPS and the power reserve that must be maintained to prevent the EPS from triggering UFLS. The simulation of the synchronization of an isolated EPS with a synchronous area was accomplished and analyzed. The obtained results were applied to reveal the sequence of actions that will help an EPS to ensure and maintain the stable and reliable operation of electrical installations during desynchronization. [ABSTRACT FROM AUTHOR]

Participation of modern variable-speed wind turbine generators in system frequency support has gained much attention from various transmission system operators to increase renewable technology hosting capacity in their power networks. A supplementary control loop is added to enable the modern variable-speed wind turbine generators to act as traditional alternators and utilize their hidden inertia. However, conventional natural inertia control strategies, such as typical ROCOF-dependent and $\Delta $ f-dependent controllers, have limited effectiveness in diverse power system operating and contingency conditions. In this work, the two variants of typical natural inertia controllers are first discussed. Then, two novel adaptive control structures, adaptive ROCOF-dependent and adaptive $\Delta $ f-dependent, are proposed. The proposed controllers adaptively change their gains based on the $\Delta f$ and ROCOF signals, respectively, while also considering the wind speed at which the sudden load changes occurred. The results illustrate the superiority of the proposed controllers in handling severe operating condition changes. Furthermore, sensitivity analysis for the typical and proposed controllers shows that the proposed controllers are the best controllers that can be used under different wind penetration levels, wind speeds, and sudden load changes in terms of various key performance indicators, especially frequency nadir, maximum ROCOF, and maximum deviation in frequency.

The primary goal of this article is to design and implement a secondary controller with which to control the system frequency in a networked microgrid system. The proposed power system comprises of Renewable energy sources (RESs), energy-storing units (ESUs), and synchronous generator. RESs include photovoltaic (PV) and wind turbine generator (WTG) units. The ESU is composed of a flywheel and a battery. Because renewable energy sources are not constant in nature, their values fluctuate from time to time, causing an effect on system frequency and power flow variation in the tie line. The nonlinear output from the RESs is balanced with the support of ESUs. In order to address this situation, a proportional integral derivative (PID) controller based on the Mayfly algorithm (MA) is proposed and built. Comparing the responses of controllers based on the genetic algorithm (GA), differential evolution (DE), and particle swarm optimization (PSO) technique-optimized to demonstrate the superiority of the MA-tuned controller.. The results of the validation comparisons reveal that the implemented MA-PID controller delivers and is capable of regulating system frequency under various load demand changes and renewable energy sources. A robustness analysis test was also performed in order to determine the effectiveness of the suggested optimization technique (1%, 2%, 5%, and 10%) step load perturbation (SLP) with ±25% and ±50% variation from the nominal governor and reheater time constant). [ABSTRACT FROM AUTHOR]

With the increase of the penetration rate of renewable energy power generation in the power system, the power grid gradually tends to be weak. Under the scenario of nonlinear load connecting to weak power grid, the grid-side voltage will produce unbalance, distortion and frequency deviation due to the influence of large internal impedance, insufficient inertia, three-phase current unbalance and harmonics of weak power grid. The operation of active power filters (APF) under above conditions can lead to significant degradation in harmonic compensation performance. An adaptive proportional integral (PI) + vector PI (VPI) harmonic compensation strategy for a three-phase APF is proposed for use in complex conditions of weak grid. The strategy consists of an adaptive notch filter based synchronous phase-locked loop (ANF-PLL) and an adaptive PI + VPI current control method. In this strategy, a series of adaptive lattice notch filters are introduced to improve the accuracy of grid phase and frequency estimation under the condition of voltage unbalance, distortion and a large range of frequency deviation. Then the phase and frequency information are used in the Park transformation of harmonic detection and current compensation control and the update of PI + VPI current control law parameters. A VPI current tracking controller with adaptive resonant frequency is constructed, which can improve the gain of the resonant frequency point and ensure that the APF can maintain the best compensation performance under the above weak grid conditions. Finally, the simulation and experimental results indicate that the ANF-PLL shows a better phase and frequency estimation performance under complex conditions of weak grid than the conventional and notch filter based methods, and the harmonic compensation strategy presented in this paper achieves a significant performance improvement under complex conditions of weak grid compared with Fixed VPI/SRF-PLL strategy and adaptive VPI/NF-PLL strategy. [ABSTRACT FROM AUTHOR]

The ways of reducing the error of measurement methods of frequency deviation and expanding the measurement ranges of frequency deviation are considered. The possibilities of reducing the error of the electronic counting frequency meter method using digital signal processing algorithms are investigated. Digital signal processing algorithms are implemented in software developed by the authors on a modern spectrum analyzer. The algorithm for digital signal processing with the spectrum analyzer is described. Using a mathematical model embedded in the calculation algorithm of the developed software, the measurement error of frequency deviation is estimated. The possibility of using the electronic counting frequency meter method with the help of digital signal processing algorithms of the spectrum analyzer has been experimentally investigated. We consider the error sources in the classical method of the electronic counting frequency meter and possible ways of their elimination. Comparisons of the proposed implementation of the electronic counting frequency meter method with the classical method, which is implemented in the State Primary Standard of the unit of frequency deviation GET 166-2020, are carried out. The proposed implementation of the method has expanded the measurement range of frequency deviation towards small values in comparison with the classical method of electronic counting frequency meter. Limitations and prospects of application of the investigated method in reference means of measuring frequency deviation based on analog-to-digital converters are considered. [ABSTRACT FROM AUTHOR]

Gas turbines with fast response characteristics make it possible to improve the flexibility of grid regulation. However, there are still some challenges in the connection of gas turbines. On the one hand, the difference of regulation rate between gas turbines and steam turbines causes the system to oscillate strongly. On the other hand, the connection of the gas turbine reduces the inertia of the system, thereby increasing the frequency deviation of the primary frequency response. Based on the above two problems, the additional control strategies are proposed in this paper. The strategies modify the voltage control and power control respectively, thereby improving the primary frequency response of the system. Moreover, a power plant and surrounding power grid in Taicang is chosen as the research object to validate the correctness of the additional control strategies proposed in this paper. The experimental results show that the proposed control strategy can well suppress the frequency oscillation and reduce the frequency deviation.

The paper represents the results of field measurements in the off-grid power system of oil field including diesel power plant, which supplies drilling rig system BU-4500/270 EK-BM. The data has been processed using the instantaneous power theory by Hirofumi Akagi. The active power load diagram of diesel power plant and power system frequency schedule have been obtained for hole drilling technological process of drilling rig. Abrupt load changes during drilling lead to large frequency deviations, which do not allow using gas piston generators in power system of oil field without revision of number and rated power of generators or using electrical energy storage system.

Due to the fluctuation of PV power, it is difficult to keep the active power of the PV grid-connected inverter constant. To address the above problems, this paper proposed a new three-level integrated photovoltaic storage machine consisting of a T-type three-level DC/AC converter, a three-level Boost converter and a three-level bi-directional DC/DC converter and related control strategies. The three-level structure allowed for lower switching losses resulting in higher system efficiency and wider voltage range adaptability. In terms of control, frequency differentiation and deviation control were introduced in the control of the energy storage DC/DC converter to achieve frequency regulation of the transient/static support of the active power of the parallel network. The simulation and experiment show that when the frequency fluctuation range is 50.02～49.97 Hz（meeting the national standard）, the new optical storage all-in-one machine proposed in this paper can operate stably and be easily realized. [ABSTRACT FROM AUTHOR]

To ensure a balance between the power generated and the consumed power in power systems, a control process namely automatic generation control (AGC) must be carried out. This process becomes more challenging due to increasing use of renewable energy sources (RES) such as wind turbines (WT) and photovoltaic (PV) panels. Therefore, AGC needs to be performed more sensitively. In this study, it has been aimed to determine the parameters of the PID controller by using the whale optimization algorithm (WOA) for the AGC in a hybrid power system consisting of photovoltaic (PV) system and thermal generator. The performance of WOA tuned PID controller is tested under load change in area-1 and area-2. Additionally, comparisons have been made with the performances of other optimization techniques such as firefly algorithm (FA), genetic algorithm (GA) and population extremal algorithm (PEO). The results obtained indicated that the WOA tuned PID controller proposed in the study gave better results than the other methods in terms of overshoot values and settling time of system frequency. [ABSTRACT FROM AUTHOR]

The automatic coordination control technology of interconnected medium voltage direct current (MVDC) distribution network based on frequency deviation is studied to improve the influence of frequency deviation on the operation of MVDC distribution network. Firstly, two regional interconnected MVDC distribution networks are built, and connected and operated in parallel with the AC power grid through the medium voltage single-phase AC port, to realize the interconnection of different regions of the distribution network according to the MVDC feeder. Through the mutual power support of each division of the distribution network, the frequency of each division of the distribution network is the same, and the frequency deviation of each division is reduced. According to the zoning frequency characteristics of the interconnected MVDC distribution network, the control strategy of the flexible interconnection device and the control strategy of the photovoltaic power generation system are combined to realize the automatic coordinated control of the frequency deviation of the interconnected MVDC distribution network. The experimental results show that this technology can improve the frequency deviation of the interconnected MVDC distribution network, realize the automatic coordinated control of the distribution network, and the fluctuation range of the tie line power deviation in each region decreases significantly. [ABSTRACT FROM AUTHOR]

Load frequency control is an important factor of supplying quality electricity in an interconnected power system. As a result, an optimally tuned Proportional-Integral-Derivative (PID) controller is proposed in this work to eliminate frequency errors caused by unexpected load changes while maintaining tie-line power exchange. The PID controller is tuned using several optimization techniques such as GA, PSO, SCA, and GWO. A two-area power system with Generation Rate Constraint is studied in the first instance, and a three-area thermal power system with both generation rate constraint and dead band effect is considered in the second case. In both scenarios, a PID controller is employed for each area. When compared to the results of other optimization approaches for the same integrated power system, such as Genetic Algorithm, Particle Swarm Optimization, and Sine Cosine Algorithm, the GWO-based PID controller outperforms them in both scenarios. According to the simulation findings, the GWO technique gives better dynamic responses in terms of overshoot value, settling time, and Integral Time Absolute Error. Finally, to evaluate the robustness of the suggested optimization strategies, sensitivity analysis is done by modifying the system parameters (turbine time constant, governor time constant, and both simultaneously) in the range of 25% from their nominal values. [ABSTRACT FROM AUTHOR]

The goal of this study is to introduce an effective load frequency control scheme with the integration of tidal turbines in a standalone microgrid (μ G) system. As standalone μ G experiences lower inertia and lacks primary frequency control, the use of variable tidal turbines in the de-loaded region may be accepted as one of the feasible solutions for managing frequency regulation issues. In this condition, the de-load region alludes to an area where tidal turbines liberate their accumulated kinetic energy in rotational parts pursuing frequency fluctuations. An effectual cascade fractional order fuzzy PID-integral double derivative (CFOFPID-IDD) controller suggested for efficient utilization of tidal turbines, whose design variables are tuned through a recently appeared Jaya algorithm. An investigation is made between the acquired outcomes of the studied CFOFPID-IDD droop controller with fractional order fuzzy PID droop control to analyze the proposed strategy performance in various load conditions, with different physical constraints like time delay, dead zone, and generation rate constraints. Moreover, the sensitivity test reveals that the Jaya-optimized CFOFPID-IDD controller can undergo ± (10–25) % variation in various coefficients without retuning the design variable values. The simulation outcomes validate the effectiveness and adequacy of the proposed regulator. • A new cascade fractional PID-IDD droop control is presented for frequency control of isolated microgrid system. • Optimization of controller parameters is done by adopting Jaya algorithm. • The pre-eminence of the suggested control strategy is established over other existing control strategies. • Sturdiness of the controller is corroborated via Sturdiness investigation. [ABSTRACT FROM AUTHOR]

Sliding mode control (SMC) has the attractiveness of robustness to the system model uncertainties and disturbance, which has wide applications in power system, power electronics, and vehicle suspension system. However, it also has a drawback of chattering. To decrease the chattering phenomenon, this study develops a novel adaptive high-order sliding mode control (HOSMC), which has the benefit of parameterizable unmodeled dynamics compared with the HOSMC method. The proposed method can be employed for load frequency control with nonlinearities. The simulations are based on two and three areas of the power system with load frequency control. From the simulation results, it is apparent that the frequency deviation and ACE (area control error) converge to zero when using the proposed method. In addition, the simulation results validate the robustness of the proposed method in the case of parameters change. The oscillation and chattering can be attenuated more by the raised adaptive HOSMC compared to the super-twisting (ST) algorithm, which verifies the advantages of the proposed adaptive HOSMC scheme.