Frequency Oscillations In Power Systems Research Articles

A coordinated modelling and control of modified pumped storage governor with unified power flow controller to damp low frequency oscillations in power system for stochastic renewable penetrations

A modern power system network is more susceptible to oscillatory instability problem due to power oscillations caused by uncertain penetration of renewable sources. Also, pumped storage hydro power generation (PSHPG) is going to take important role for energy storage and management with varying renewable penetrations, but their governors need to be utilized efficiently for power oscillation damping. In this work a coordinated modified pumped storage governor with fractional parallel unified power flow controller (FPUPFC) has been modelled and controlled to damp angular frequency variations in power system. The prime objective of this work is to enhance efficacy of pumped storage hydro turbine governors integrated into an expert system with UPFC to take part in electromechanical oscillation damping. Here the governor is modified by fractional order PID action with additional phase compensation and in FPUPFC both series and shunt converters are controlled simultaneously by parallel fractional lead-lag based control action. The power system considered here consists of hydro generators of 100 MVA with 90.94 MW rated turbine output power with different operating conditions for two area 4 generators and 39 bus 10 generators multimachine renewable integrated system. It has been observed that efficacy of pumped storage hydro turbine governor action has been much improved when coordinated with FPUFC control action. A new hybridized modified differential evolution with fractional particle swarm optimization (MDEFPSO) is proposed to tune the parameters of proposed controller, with a multi-objective function considering variation in speed and real power deviations, settling time, overshoot and undershoot of system response.

Large-Scale BESS for Damping Frequency Oscillations of Power Systems with High Wind Power Penetration

With the high penetration of renewable energy into power grids, frequency stability and oscillation have become big concerns due to the reduced system inertia. The application of the Battery Energy Storage System (BESS) is considered one of the options to deal with frequency stability and oscillation. This paper presents a strategy to size, locate, and operate the BESS within the power grid and, therefore, investigate how sizing capacity is related to renewable energy penetration levels. This paper proposes an identification method to determine the best location of the BESS using the Prony method based on system oscillation analysis, which is easy to implement based on measurements while actual physical system models are not required. The proposed methods for BESS size and location are applied using MATLAB/Simulink simulation software (version: R2023a) on the Kundur 2-area 11-bus test system with different renewable energy penetration levels, and the effectiveness of the applied method in enhancing frequency stability is illustrated in the study cases. The case studies showed a significant improvement in steady-state frequency deviation, frequency nadir, and Rate of Change of Frequency (ROCOF) after implementing BESS at the selected bus. The integration of BESS can help to avoid Under-frequency Load Shedding (UFLS) by proper selections of size, location, and operating strategy of the BESS within the power grid.

Damping Undammed Low Frequency Oscillations in Power Systems: An ANN-Based Approach Using Pre-Disturbance Data

The paper examines undammed low frequency oscillations (LFOs) that can lead to system collapse, citing the Jordan power network incident on May 21, 2021. Traditional model-based methods for studying LFOs' small-signal stability have limitations. To address this, an online damping controller based on an artificial neural network (ANN) is proposed. Unlike existing ANN-based methods relying on offline controllers, this novel approach utilizes pre-disturbance data from phasor measurement units (PMUs) to dampen oscillations effectively. The paper addresses challenges of partially observable systems in online eigenvalue prediction using ANN. MATLAB is used to implement a feedforward ANN system trained on PMU data. The study involves a three-area test system with various operational scenarios, training the ANN across 406 scenarios to predict eigenvalues and damp LFOs.

Study on a comprehensive indicator and online classification of early warning of low frequency oscillation in power system

With the development of smart grid technology in China, the study of low frequency oscillation early warning has become an important element of power system stability research. Aiming at the problems of single warning indicator with poor accuracy and lack of online warning system in the early warning strategy of low frequency oscillation in power system, a comprehensive low frequency oscillation early warning algorithm based on the evaluation method of kernel matrix hierarchical analysis of fuzzy comprehensive is proposed. Firstly, this method screens out the original data collected by Phasor Measurement Unit (PMU), and extracts the key data volume to form multiple early warning indicators, and generates the trapezoidal fuzzy number judgment matrix. Secondly, by calculating the kernel matrix and consistency test, it is determined whether or not the generated fuzzy matrix is reasonable and calculate the relative weights of the evaluation indicators. The affiliation function is constructed for each early warning indicator. A comprehensive indicator is calculated for multiple indicators, and the reasons of low frequency oscillation in power system are classified by the Random Forest (RF) algorithm. Then, the low-frequency oscillation system is constructed, and the algorithm convergence is proved by the Lyapunov indirect method. The algorithm can automatically determine whether low frequency oscillation occurs or not and classify different types of low frequency oscillations online. Finally, the correctness and validity of this paper’s method is verified by a New England 10-machine 39-node system. Compared with the traditional Analytic Hierarchy Process (AHP) method, the proposed method in this paper greatly improves the accuracy of early warning and meets the need of online warning.

Study on stability margin of ultra-low frequency oscillation in hydropower system

In recent years, the ultra-low frequency oscillation of power system caused by hydropower units has occurred frequently. It is very important to study the ultra-low frequency oscillation characteristics of hydropower stations for the stable operation of power system. It is worth further research on how to determine the system stability margin in engineering practice. Based on the established model of single machine system with load, the analysis of the characteristic equation of closed-loop transfer function of single machine system shows that the ultra-low frequency oscillation will occur when the ratio of proportional parameter to integral parameter is too small. Based on the single machine with load system model and the equivalent single machine with load model of multi machine system, the ultra-low frequency oscillation mode of the system is analyzed by eigenvalue analysis method. According to the requirements of the damping ratio index, the security domain of the system ultra-low frequency oscillation is constructed, and the risk and stability margin of the system ultra-low frequency oscillation are evaluated by the characteristic values of the system ultra-low frequency oscillation mode.

Enhanced Visualization and Characterization of Low Frequency Oscillations in Power System

Real-time monitoring ofoscillation events provides enhanced wide-area situational awareness to the system operator. This article focuses on visualizing low frequency oscillatory modes, their detection, and classification following an event. The significant oscillatory modes present in the signal are extracted through a novel energy preserving, nonredundant “frequency partition based mode extraction (FPBME)” algorithm. These modes are analytically deduced and classified as governor mode, interarea mode, and local mode through a novel “energy based mode detection and classification (EBMDC)” algorithm. This article proposed method introduces the concept of “visualization” that is highly operator-friendly through the time domain plots of extracted modes. Time-domain plots of mode’s instantaneous frequency and instantaneous energy, which are considered fundamental characterization of low-frequency oscillations, are also portrayed through the developed method. The proposed method is validated through various scenarios of Kundur’s two-area system and IEEE-39 bus system. A practical test case on the ISO-NE system is also verified through the suggested scheme. Comparison of the proposed method in the context of visualization with other methods such as the Hilbert–Huang technique and continuous wavelet transform is also discussed in this article. The comparative assessment demonstrates the superior performance of the proposed method.

Large-Scale Solar PV Converter based Robust Wide-Area Damping Controller for Critical Low Frequency Oscillations in Power Systems

Integration of large-scale renewable energy sources in legacy power system has negative impact on inertia and low-frequency oscillations (LFOs). Critical LFO modes are the primary concern in system stability as they limit the power transfer capability in inter-region tie-lines. Therefore, to provide adequate damping to critical LFO modes, a robust wide-area damping controller (WADC) design is required. In this paper, time delayed feedback control (TDFC) based WADC design is carried out with large-scale solar photovoltaic (SPV). In the design process, geometric technique is used to determine the appropriate wide-area signals. Time delays and noises in feedback signals as well as different operating scenarios have severe implications on the damping performance of WADC. Hence, considering these uncertainties, the proposed WADC parameters are tuned by modified particle swarm optimization (PSO) algorithm. The performance of proposed WADC is demonstrated on SPV-integrated IEEE 4-machine 11-bus and 16-machine 68-bus systems. Critical modes of the system are damped by more than 10 % damping ratio in both cases. Furthermore, nonlinear dynamic simulations demonstrate that the proposed WADC provides robust performance over wide operating scenarios. Finally, practical efficacy of the proposed method is established by experimental validation through real-time simulation using OPAL-RT.

A three-stage random forest integrating fuzzy matrix method in low frequency oscillation classification of power system

In view of the problems that the early warning process of low frequency oscillation in power system is vulnerable to the influence of complex grid environment. The classification speed is slow due to the large amount of processing data in the classification process. A three-stage random forest based on a fuzzy matrix method is proposed in this paper to improve the accuracy and the classification speed of low frequency oscillation early warning in power system. Firstly, the fuzzy matrix comprehensive evaluation is carried out by PMU data, and the evaluation score S will be obtained to determine whether low-frequency oscillation occurs and makes a quick warning. Then, the data is processed by Synchronous Wavelet Transform (SWT), and the damping ratio and attenuation factor of the data are obtained. Furthermore, Random Forest 2(RF 2) and RF 3 are used to judge the type of low frequency oscillation. Finally, simulation results show that the comprehensive fuzzy matrix improves the accuracy of low-frequency oscillation early warning, and the three-stage classification method reduces the amount of data processing and improves the classification speed and stability.

Optimal fractional steam governor damping controller with variable solar penetrations

When the gains of steam turbine governor are properly tuned with modification in control parameters, it can impart effective damping torque to low frequency oscillations in power system. Here a fractional steam governor control action is proposed to provide damping action whose parameters are tuned by Sail Fish Algorithm (SFA). The system oscillations are generated by variable Solar Photo Voltaic (SPV) integrations. The additional steam governor damper employs fractional lead-lag based control action. The low frequency model of steam generator with SPV penetration has been examined with step and random solar power generation for justifying proposed steam governors damping control action. The system eigen values have been analyzed for different solar penetrations.

Investigating the Impact of Wind Power Integration on Damping Characteristics of Low Frequency Oscillations in Power Systems

This paper investigates the impact of doubly-fed induction generator (DFIG) wind farms on system stability in multi-generator power systems with low-frequency oscillations (LFOs). To this end, this paper establishes the interconnection model of the equivalent generators and derives the system state equation. On this basis, an updated system state equation of the new power system with integrated wind power is further derived. Then, according to the updated system state equation, the impact factors that cause changes in the system damping characteristics are presented. The IEEE two-area four-machine power system is used as a simulation model in which the LFOs occur. The simulation results demonstrate that the connection of wind power to the power feeding area (PFA) increases the damping ratio of the dominant mode of inter-area oscillation from −0.0263 to −0.0107, which obviously improves the system stability. Furthermore, the wind power integration into PFA, as the connection distance of the wind power increases, gradually decreases the damping ratio of the dominant mode of the inter-area oscillation to −0.0236, approaching that of no wind power in the system. Meanwhile, with the increase in the wind power output capacity, the damping ratio of the dominant mode of the intra-area and inter-area oscillation increases, and the maximum damping ratios reach 0.1337 and 0.0233, respectively.

Effective damping of local low frequency oscillations in power systems integrated with bulk PV generation

High penetration of renewable sources into conventional power systems results in reduction of system inertia and noticeable low-frequency oscillations (LFOs) in the rotor speed of synchronous generators. In this paper, we propose effective damping of LFOs by incorporating a supplementary damping controller with a photovoltaic (PV) generating station, where the parameters of this controller are coordinated optimally with those of a power system stabilizer (PSS). The proposed method is applied to damp local electromechanical modes by studying a system comprising a synchronous generator and a PV station connected to an infinite bus. The PV station is modeled following the instructions of the Western Electricity Coordinating Council. The problem is modeled as an optimization problem, where the damping ratio of the electromechanical modes is designed as the objective function. Constraints including upper and lower limits of decision parameters and damping ratio of other modes are considered by imposing penalties on the objective function. Different optimization algorithms are used to pursue the optimal design, such as political, improved gray wolves and equilibrium optimizers. The results validate the effectiveness of the proposed controller with PSS in damping local modes of oscillations.

Research on Governor Parameter Optimization to Suppress Ultra-Low Frequency Oscillation of Power System Caused by Hydropower Unit

In the actual power system with hydropower, long-time and ultra-low frequency oscillation events occur many times. It is found that the unreasonable setting of governor parameters is an important reason for the oscillation. Firstly, the single machine on load system model is used to analyse the relationship between the PID parameters of the governor and the system stability, then the relationship between oscillation mode and PID parameters of governor is analyzed by eigenvalue analysis method, and the negative damping provided by speed regulation system is analyzed by damping torque method, and then the particle swarm optimization algorithm is used to optimize the PID parameters. Through the analysis of the step response of the single machine system before and after the optimization and the damping torque coefficient provided by the speed regulation system, it shows the effectiveness of the optimization algorithm. Finally, in the simulation platform MATLAB/SIMULINK, a single machine load system model which is closer to the actual power grid is built. The governor parameters of the generator are simulated and verified, and the PID parameters are adjusted by using the parameters obtained by the optimization algorithm. The results show that the optimized parameters have a good suppression for the ultra-low frequency oscillation.

Analysis of Technical Performance of PSS2 Based on An Active Power Oscillation Accident of generator

Low frequency oscillation in power system has become the main factor limited the development of power grid in China. Taking the generator power oscillation accident caused by PSS abnormal operation in a gas power plant of China as an example, the accident process is introduced in detail, and the causes of the accident are preliminarily discussed through the analysis of related data. The generator model is established with RTDS platform, then the influences of the rotational inertia, and speed acquisition methods of the unit and setting of the swing reactance on generator PSS(Power System Stabilizer) suppressing power oscillation effect are simulated and analyzed. According to the research results, the accident causes are further analyzed, and relevant suggestions are given for how to avoid such accidents.

A Novel ESPRIT Algorithm for Analysis of Low Frequency Oscillations in Power System

With rapidly increasing load and randomly varying load scenario in a densely connected power system may lead to low-frequency oscillations which can further make a power system unstable. To keep the power system in stable operating limits identifying such dominant low-frequency oscillations is essential. Numerous signal processing techniques are used to detect low-frequency oscillations in a power system. Different techniques have their advantages and disadvantages. Estimation of signal parameters via rotational invariance technique (ESPRIT) is a signal processing technique by which low-frequency oscillations can be identified even under noisy conditions . In this paper, a novel ESPRIT algorithm for identifying low-frequency oscillations is proposed. This methodology is based on the ESPRIT algorithm, whose key concept is that real modes existing in oscillations emerge consistently regardless of the algorithm's order. The performance of this algorithm is verified through a set of synthetic signals generated in MATLAB with different noise levels and varying PMU rates and compared with traditional Prony algorithm. The performance of the proposed algorithm is also verified on real-time test data obtained from the Western Electricity Coordinating Council (WECC). This technique performs fairly well in finding low-frequency oscillation characteristics in the power grid.

Extended Geometric Feature Extraction Process for Detecting Multiple Frequency Oscillations in KEPCO System

In this study, a new algorithm dealing with time-varying modes for determining and tracing multiple frequency oscillations in power systems is proposed. Multiple modes or resonance of forced and natural oscillations can have severe effects on a power system. Therefore, it is crucial to recognize the dominant natural and forced oscillations because the oscillation mode possesses time-varying features that depend on the system operating conditions or changes in the parameters. The salient features of the proposed algorithm include the use of a time-series-based approach to recognize undesired modes (including multiple oscillations over a wide frequency range), tracing time-varying modes as the power system operating condition changes, and effectively determining and applying the oscillation features before implementing the corresponding control measures in the power system. In this study, multiple frequency oscillation scenarios for the test system and practical measurement data for a recent incident that occurred in Korea Electric Power Corporation (KEPCO) system are discussed. Therefore, the proposed algorithm can be practically applied in wide-area monitoring systems, not only for a single forced oscillation or local mode detection but also for system-wide inter-area mode recognition.

The Impact of Primary Frequency Control of WTs on Ultra-Low Frequency Oscillation

Since entering the 21st century, as wind power develops rapidly, wind power plays an increasingly important role in the safe and stable operation of power systems. Since the wind turbines under traditional control don’t provide frequency support, the frequency dynamics of the power grids after load disturbance will be deteriorated. Thus, wind farms are required to equip primary frequency control in many countries. Most existing researches on primary frequency control of wind turbines focus on control strategies and the impact on system frequency, but few studies pay attention to the impact of primary frequency control of wind power on ultra-low frequency oscillation. This paper first proposes an analysis framework for ultra-low frequency oscillations in power systems with wind power. On this basis, a motion equation model of wind turbines is established. Finally, an extended three-machine nine-node system is used as an example to analyze the impact mechanism of primary frequency control on ultra-low frequency oscillation. The impact mechanism provides reference for the design of primary frequency of wind turbines in some regional power grids with ultra-low frequency oscillation.

Configuration method of PSS lead-lag compensator parameters

Power System Stabilizer (PSS) is an important measure to increase damping and suppress low frequency oscillations of power system. During PSS test, the time constant of lead-lag compensator need to be configured, considering the inefficiency and optimization problem when configuring parameters empirically, this paper proposes automatic configuration method of PSS parameters based on Matlab, by setting the expected phase value at each frequency and constructing the objective function with the sum of phase differences square, the automatic calculation of PSS parameters under specific phase requirements at each frequency can be realized, the detailed steps of this method are given, and the method is verified during the PSS test of an 300Mw thermal-power generating unit finally.

Frequency regulation analysis of modern power systems using start-stop peak shaving and deep peak shaving under different wind power penetrations

Frequency regulation has attracted considerable attentions with the integration of large-scale renewable energy into power systems. The de-commitment of conventional units reduces the system inertia, thus causes the poor frequency performance under high wind power penetration. Start-stop of conventional units is always set in power system simulations under high wind power penetration by default. In this work, power systems with deep peak shaving are considered in frequency regulation analysis for supplement. The system parameters of modern power systems in LFC are claimed and some assumptions are made first. The variety of regulating capability of conventional units and models of frequency sensitive wind energy conversion systems (WECS) are considered under different wind power penetrations. The simulation models are then derived according to the physical meaning of these two operation modes under different wind power penetrations. The modeling process is also improved by maintaining controllers optimal in each scenario. Load disturbances and stochastic wind speed are then employed as disturbance sources in the simulation tests. Results show that frequency oscillations of power systems with deep peak shaving would increase along with the wind power penetrations. However, compared with start-stop peak shaving, deep peak shaving can strongly keep systems away from large frequency deviations. Moreover, the regulation effects between the two methods become evident with increasing wind power penetration. The results would help system managers in daily operation.

A Novel Wide-Area Control Strategy for Damping of Critical Frequency Oscillations via Modulation of Active Power Injections

This article proposes a novel wide-area control strategy for modulating the active power injections to damp the critical frequency oscillations in power systems, this includes the inter-area oscillations and the transient frequency swing. The proposed method pursues an efficient utilization of the limited power reserve of existing distributed energy resources (DERs) to mitigate these oscillations. This is accomplished by decoupling the damping control actions at different sites using the oscillation signals of the concerned mode as the power commands. A theoretical basis for this decoupled modulating control is provided. Technically, the desired sole modal oscillation signals are filtered out by linearly combining the system-wide frequencies, which is determined by the linear quadratic regulator based sparsity-promoting (LQRSP) technique. With the proposed strategy, the modulation of each active power injection can be effectively engineered considering the response limit and steady-state output capability of the supporting device. The method is validated based on a two-area test system and is further demonstrated based on the New England 39-bus test system.

A Clustering-Based Approach for Estimation of Low Frequency Oscillations in Power Systems

This paper presents a clustering technique to rank the dominant modes of low frequency oscillations in power systems under model order uncertainty of the signal. The rotational invariance property of the signal subspace is utilized to obtain the modes of oscillations. Rotational invariance of the signal under multiple shifts is considered to obtain the preliminary estimates of the modes. Subsequently, the modes are clustered to obtain the dominant modes that belong to the signal subspace. A signal subspace participation index (SSPI) is used to rank the modes according to their dominance in signal subspace. Thereafter, the convex combination of the preliminary modes, estimated from the multiple shifts of the signal subspace, is used to obtain the final mode estimates. The simulation results are presented for signal generated using the modes obtained from a two-area system. Additionally, the methodology is also tested on field data obtained from the PMU installed at a generating station in India.