System Stability Issues Research Articles

СТІЙКІСТЬ РОБОЧИХ РЕЖИМІВ АВТОНОМНИХ АСИНХРОННИХ ГЕНЕРАТОРІВ ІЗ САМОЗБУДЖЕННЯМ

The paper presents the results of investigation the stability conditions of self-excited induction generators. A mathematical model of the generating system with an analytical description of the dependence of the magnetization inductance on the current is used. It allows to avoid the iterative procedure and to scale the dependence to determine the magnetization inductance for induction machines of different types and power. The influence of the load inductance on the stability of the generating system at different rotational speeds is investigated. It is shown that an increase in the inductance value increases the system stability margins in the self-excitation zone. Also this article deals with the issues of system stability within the self-excitation zone of an induction generator at different rotational speeds depending on the value of the capacitance of self-excitation capacitors. It is depicted that at low rotational speeds there may not exist a stable operation mode in the self-excitation zone regardless of the value of the capacitance in the motor stator circuit. This method of determination the stability of the operation modes of the generation system will be useful both for the design of new systems and for the modification and adjustment of existing ones. References 9, figures 4.

A grid-forming approach utilizing DC bus dynamics for low inertia power systems with HVDC applications

While power electronic converters, such as voltage source converters (VSCs), are crucial for the operation of converter-dominated renewables and their integration with the electricity grid, their reliance on VSCs can pose a challenge. The limited inertia of these sources can lead to a deterioration of the rate of change of frequency, potentially causing power system stability issues. A grid-forming approach utilizing dc-link dynamics is one of the attractive alternatives to achieve grid synchronization and support grid frequency. Existing grid-forming control schemes, which assume a constant or virtually constant dc source, rely on a fixed physical dc-link capacitor. Nonetheless, the inertia support from such a capacitor is brief, owing to its limited energy storage capability. Consequently, enhancing inertia becomes imperative; otherwise, it may result in an increased rate of change of voltage on the dc side, potentially leading to issues with protection, undesirable interactions, and system instability. This paper proposes a new grid-forming control strategy that considers a virtual capacitor to achieve grid synchronization while simultaneously providing the network with inertia response services during power imbalances. Moreover, including a virtual resistor in the controller effectively attenuates power and dc voltage oscillations. Simulations using Simulink and small signal stability analysis are conducted to validate the efficacy of the proposed controller.

Research on Maximum Power Control of Direct-Drive Wave Power Generation Device Based on BP Neural Network PID Method

Ocean wave energy is a new type of clean energy. To improve the power generation and wave energy conversion efficiency of the direct-drive wave power generation system, by addressing the issue of large output errors and poor system stability commonly associated with the currently used PID (proportional, integral, and derivative) control methods, this paper proposes a maximum power control method based on BP (back propagation) neural network PID control. Combined with Kalman filtering, this method not only achieves maximum power tracking but also reduces output ripple and tracking error, thereby enhancing the system’s control quality. This study uses a permanent magnet linear generator as the power generation device, establishes a system dynamics model, and predicts the main frequency of irregular waves through the Fast Fourier Transform method. It designs a desired current tracking curve that meets the maximum power strategy. On this basis, a comparative analysis of the control accuracy and stability of three control methods is conducted. The simulation results show that the BP neural network PID control method improves power generation and exhibits better accuracy and stability.

Parameter Optimization of Energy Storage Virtual Synchronous Machine Based on Particle Swarm Optimization Algorithm

Energy transformation is a severe challenge and major demand faced by China’s sustainable development, and new energy development has become a key driving force for energy transformation. The issue of system stability is brought to light by the steadily rising share of renewable energy sources like wind and solar, which in turn places greater demands on the inertia support capacity of power plants. In order to replicate the dynamic equations of a conventional synchronous machine and add inertia and damping to the system, a new technology known as virtual synchronous machine (VSM) control has arisen. Therefore, improving the system’s absorption capacity of new energy generation and ensuring its safe and stable operation are both greatly aided by the study of energy storage VSM control technology’s grid stability and parameter design methods. Although VSM control adds inertia to a system, which is good for stability, it also complicates the system’s ability to withstand tiny disturbances. This paper investigates the small disturbance stability of VSM-controlled power generating and storage systems. The stability analysis method of storage VSM when subjected to random power sources is investigated further, and a method for optimising the system’s parameters is proposed. VSM with optimised parameters can provide sufficient inertia and damping under complex operating conditions, as shown by simulation results in real-world systems. Finally, the proposed method’s efficacy was assessed with the help of an enhanced binary particle swarm optimisation (EBPSO) algorithm, and the outcomes confirmed its superiority.

Transient Stability Impact of Short Circuit Fault System Based on SVC And PSS Applications

Researchers are currently focusing on two solutions, namely Static VAR compensator (SVC) and power system stabilizer (PSS), to address different power system stability issues in large area interconnected power grids. To enhance transient stability, researchers have suggested a combined approach involving SVC and PSS. In this method, SVC and PSS coordinate and cooperate with each other to provide better stability assurance. To verify the feasibility of this method, simulation experiments were conducted using MATLAB. Simulated the situation of single-phase ground fault, two-phase ground fault, and three-phase ground fault in the power system, and tested the effectiveness of SVC and PSS respectively. The simulation results show that the combined use of SVC and PSS can significantly improve the transient stability of power systems and effectively reduce the impact of faults on the system. In summary, the combined use of SVC and PSS can effectively solve various power system stability issues that may arise in large-scale interconnected power grids. By conducting simulation experiments in MATLAB, researchers have verified the feasibility of this method under different fault conditions, providing strong support for practical applications.

Modeling and Nonlinear Characteristics Analysis of Fluorescent Lamp Driven by a Full-Bridge Inverter

Addressing the issue of system stability is a crucial step towards the successful integration of memristive devices in power electronics applications. This paper focuses on fluorescent lamps possessing memristive characteristics and investigates the instability phenomena and mechanisms within a full-bridge inverter with a fluorescent lamp load. Based on the memristive characteristics of fluorescent lamps, this paper establishes the averaged model of the system, whose coefficient matrix is nonlinear, periodic, and time-varying. This study identifies the occurrence of low-frequency oscillations within the system and elucidates the fundamental mechanism underlying the emergence of low-frequency oscillations. Furthermore, this paper establishes the stability boundaries of the system across different parameter planes. The research findings indicate that the low-frequency oscillations within the system are attributed to the occurrence of Hopf bifurcations in a frequency range higher than line frequency but significantly lower than switching frequency. Lastly, the PSpice circuit of the system is designed, and simulation results are provided for validation. This study can offer guidance on parameters and control strategies for ensuring the stable operation of a full-bridge inverter with fluorescent lamps. Moreover, it can facilitate the comprehension of instability mechanisms in systems incorporating memristive devices, thereby offering a foundation for the expansion of memristor applications.

Voltage-Oriented Control-Based Three-Phase, Three-Leg Bidirectional AC–DC Converter with Improved Power Quality for Microgrids

Renewable energy sources (RESs) and energy storage schemes (ESSs) integrated into a microgrid (MG) system have been widely used in power generation and distribution to provide a constant supply of electricity. The power electronics converters, particularly the bidirectional power converters (BPCs), are promising interfaces for MG infrastructure because they control the power management of the whole MG system. The controller of BPCs can be designed using several different control strategies. However, all the existing controllers have system stability, dynamics, and power quality issues. Therefore, this study demonstrates the development of an LCL-filtered grid-connected bidirectional AC–DC converter’s (BADC) control strategy based on voltage-oriented control (VOC) to overcome these issues. The proposed VOC-based inner current control loop (ICCL) is implemented in synchronous dq-coordinate with the help of proportional-integral (PI) controllers. An observer-based active damping (AD) is also developed in order to estimate the filter capacitor current from the capacitor voltage instead of directly measuring it. This developed AD system helps to damp the resonance effect of the LCL filter, improves system stability, and also eliminates the practical challenges of measuring capacitor current. The proposed controller with AD is able to realize bidirectional power transfer (BPT) with reduced power losses due to the elimination of passive damping and improved power quality, system dynamics, and stability. The mathematical modeling of the suggested system was developed, and the structure of the system model was established in the MATLAB/Simulink environment. The performance of the proposed system was validated with real-time software-in-the-loop (RT-SIL) simulation using the OPAL-RT simulator for a 16 kVA converter system. The real-time (RT) simulation results show that the BADC with the proposed control scheme can provide better dynamic performance and operate with tolerable total harmonic distortion (THD) of 2.62% and 2.71% for inverter and rectifier modes of operation, respectively.

An Enhanced Tuna Swarm Algorithm for Optimizing FACTS and Wind Turbine Allocation in Power Systems

The significance of FACTS devices has been increasing as they have the ability to donate compensation for power systems, making a significant impact on power system stability and power transfer issues. However, to optimize the performance of these devices, it is important to carefully select their sizes and locations. This article aims to determine the optimal size and location of several FACTS devices to achieve two objectives: minimizing fuel costs and minimizing power losses. These objectives are solved one by one, then combined into a multi-objective function to minimize gross cost. An Enhanced Tuna Swarm Optimization is proposed to improve the performance of the original version of Tuna Swarm Optimization. The traditional Tuna swarm optimization is improved relying on “high and low-velocity ratios” included in the Marine Predator Algorithm. The main advantage of this approach is to avoid the risk of the optimal value being trapped in local minima. The IEEE 30-bus standard system is used as a case study, with SVC, TCSC, and TCPS installed as FACTS devices, and two wind turbines as renewable resources penetration. Different optimization algorithms are used, and a comparison is made to prove the superiority of the proposed algorithm compared to the other tested algorithms.

A Generalized Harmonic Compensation Control Strategy for Mitigating Subsynchronous Oscillation in Synchronverter Based Wind Farm Connected to Series Compensated Transmission Line

With the increasing application of synchronverter technology in renewable energy power generation, power system stability issue becomes more complicated. Due to the impedance interaction between the synchronverter based wind farm and the series compensated transmission line, the synchronverter based wind farm is prone to cause sub-synchronous oscillation (SSO). To suppress this SSO, a generalized harmonic compensation control strategy of active power filter (APF) with supercapacitor is proposed, which counteracts SSO by injecting the generalized harmonic current including reactive and oscillation current. Since the generalized harmonic current can be calculated by subtracting the sinusoidal active current from the sampling current, a first-order inertial controller of the voltage loop for APF is proposed to accurately obtain the active current. In addition, the supercapacitor of APF is used to reduce the dc-side voltage fluctuation caused by SSO. As this paper does not need to directly extract the SSO component, the proposed method does not need to know the system oscillation frequency in advance, which can be used as a defensive control method of SSO. Finally, experimental results verify the effectiveness of the proposed strategy.

High-order Adams Network (HIAN) for image dehazing

Convolutional Neural Networks (CNN) are widely used in image dehazing. However, existing network frameworks are built based on manual design from practical experience, lacking interpretable result or theoretical guidelines. Recently, residual networks are regarded as the explicit Euler forward approximation of the ODE (Ordinary Differential Equation), and several ODE-inspired networks are proposed based on the low-order explicit Euler schemes. However, on the issues of system stability and training convergence, high-order Implicit Adams Predictor–Corrector (IAPC) methods have proven to be better than low-order explicit Euler methods. Hence, we extend the IAPC method to the High-order Implicit Adams Network (HIAN). To do so, we design a series of Implicit Adams Predictor–Corrector Blocks (IABs) based on the high-order IAPC methods, all of which give better stability and accuracy than the ones designed using the low-order Euler methods. Given that, we further propose the Implicit Adams Predictor–Corrector Module (IAM) by combining the Non-local Sparse Attention (NSA) and Attention Feature Fusion (AFF) with stacked IABs where the NSA explores the mutual-correlation among intermediate features with low computation cost via a sparse constraint, while the AFF fuses intermediate features by reweighting the features from stacked IABs adaptively. Moreover, because manual network design with IABs limits dehazing performance, the Neural Architecture Search (NAS) is used to find an optimal architecture automatically. This resulting design not only is interpretable for image dehazing but also provides a reliable guideline on future network designs. The experiments demonstrate that the proposed method outperforms most existing methods on both synthetic and real images.

Fuzzy-based prediction of solar PV and wind power generation for microgrid modeling using particle swarm optimization

Regardless of their nature of stochasticity and uncertain nature, wind and solar resources are the most abundant energy resources used in the development of microgrid systems. In microgrid systems and distribution networks, the uncertain nature of both solar and wind resources results in power quality and system stability issues. The randomization behavior of solar and wind energy resources is controlled through the precise development of a power prediction model. Fuzzy-based solar PV and wind prediction models may more efficiently manage this randomness and uncertain character. However, this method has several drawbacks, it has limited performance when the volumes of wind and solar resources historical data are huge in size and it has also many membership functions of the fuzzy input and output variables as well as multiple fuzzy rules available. The hybrid Fuzzy-PSO intelligent prediction approach improves the fuzzy system's limitations and hence increases the prediction model's performance. The Fuzzy-PSO hybrid forecast model is developed using MATLAB programming of the particle swarm optimization (PSO) algorithm with the help of the global optimization toolbox. In this paper, an error correction factor (ECF) is considered a new fuzzy input variable. It depends on the validation and forecasted data values of both wind and solar prediction models to improve the accuracy of the prediction model. The impact of ECF is observed in fuzzy, Fuzzy-PSO, and Fuzzy-GA wind and solar PV power forecasting models. The hybrid Fuzzy-PSO prediction model of wind and solar power generation has a high degree of accuracy compared to the Fuzzy and Fuzzy-GA forecasting models.The rest of this paper is organized as: Section II is about the analysis of solar and wind resources row data. The Fuzzy-PSO prediction model problem formulation is covered in Section III. Section IV, is about the results and discussion of the study. Section V contains the conclusion. The references and abbreviations are presented at the end of the paper.

Finite-time fault-tolerant consensus for leader-following multi-agent systems with semi-Markov switching topologies

This paper investigates the finite-time leader-following consensus problem for multi-agent systems with switching topologies. First of all, consider the characteristic of failures, a failure distribution model which is more in line with the actual situation is established, and a semi-Markov chain is used to describe the topology switching of the multi-agent system, in which the transfer rate is time-varying. Secondly, based on the past state information, a topology-dependent consensus protocol is established, then the fault-tolerant consensus problem of leader-following multi-agent is transformed into the issue of system stability, according to the mode-dependent Lyapunov function and the finite time stochastic theorem, the sufficient conditions for the stability of the closed-loop system and the constraints of average residence time are obtained. In addition, an initial-state based H ∞ performance index is proposed to reduce the influence of zero initial conditions on the system. Finally, a numerical example is provided to show the effectiveness of the proposed method.

Uses of Superconducting Magnetic Energy Storage Systems in Microgrids under Unbalanced Inductive Loads and Partial Shading Conditions

Superconducting magnetic energy storage (SMES) systems are characterized by their high-power density; they are integrated into high-energy density storage systems, such as batteries, to produce hybrid energy storage systems (HESSs), resulting in the increased performance of renewable energy sources (RESs). Incorporating RESs and HESS into a DC bus to obtain a DC microgrid concept is considered a more attractive option for solving system reliability and stability issues. In this paper, we focus on employing SMES systems based on their characteristics of a fast response and high efficiency, which contribute to increased battery lifespan, and reducing the mismatch between the energy supplied by the renewable energy source and the load demand by compensating for the effects of partial shading on the PV system on the DC bus side and the imbalance in loads on the other side of the AC bus. The incremental conductance algorithm (INC) is used for maximum power point tracking (MPPT) in the PV system. Fuzzy logic control (FLC) is proposed for the generation of control signals for the DC–DC chopper used to charge/discharge the SMES coil. Simulations using MATLAB/Simulink were then carried out to assess the proposed models of the (standalone and grid) connection systems.

Analysis of IEEE 33, 34 and 69 Bus Systems using Gauss Seidel

Abstract: Optimum power flow studies to minimize either the power distribution losses or the cost of power drawn from the substation, without affecting on the voltage regulation. This paper discusses the concept of Gauss Seidel method to be used with load flow analysis control for stability of large power systems. Voltage Stability has become an important issue of power system stability. This paper work concentrates on simple and efficient load flow analysis of radial distribution system for finding voltage magnitudes and also the voltage profile. This load flow study of radial distribution system network is of prime importance for effective planning of load transfers. Power companies are interested in finding the most efficient configuration for minimization of real power losses and load balancing among distribution feeders to save energy and enhance the overall performance of the distribution system. This test has been performed on the 33, 34 and 69 bus systems with the use of MATLAB software

Voltage Stability Improvement In Multi-bus System Using Static Synchronous Series Compensator

Abstract: Network stability has become a major worry as the power system has become increasingly complicated as a result of open access electricity market activities and increased demand. Voltage unbalance and collapse have become a global issue for a variety of reasons. FACTS devices are used to manage system stability issues. Use of a static synchronous series compensator (SSSC) to enhance the voltage stability of a power system is investigated in this paper. IEEE 9 bus networks are modelled using MATLAB Simulink software to investigate voltage management and reactive power compensation. For a multibus system, the effectiveness of SSSC on voltage stability is examined. Using a static synchronous series compensator enhances voltage stability. Keywords: SSSC, Faults, voltage improvement

Load-Frequency Control of Three-Area Interconnected Power Systems with Renewable Energy Sources Using Novel PSO~PID-Like Fuzzy Logic Controllers

Modern era power systems may include not only traditional primary energy sources like hydro or thermal energy, but also a variety of Renewable Energy (RE) sources such as solar and/or wind power. This leads to the complexity of the electrical networks related to their design and construction as well as system stability and control issues. Considered to be one of the most crucial control issues, Load Frequency Control (LFC), must be continuously improved in order to ensure the control goals. For an interconnected power system, the control purposes are to maintain the net frequency at nominal value, e.g. 50 or 60Hz as well as to ensure that tie-line power flows are stable at scheduled values. This work proposes a novel LFC strategy applying Particle Swarm Optimization (PSO) ~ PID – like fuzzy logic–based controllers. PSO is one of the most effective optimization techniques. It is used to optimally determine four scaling factors for each LFC proposed in this study. A three-area power network consisting of a hydraulic station, a non-reheat plant, and a reheat unit along with RE sources such as wind and solar power are taken into consideration. The control performance of the proposed control strategy is compared to those of existing controllers, i.e. Genetic Algorithm (GA), Bacteria Foraging Optimization Algorithm (BFOA), Fractional Order-PID (FPID), and fuzzy logic-based PI controllers for the same interconnected power grid model with various case studies of load changes along with nonlinearities and different RE source conditions. Simulation results implemented in MATLAB/Simulink demonstrate the feasibility and applicability of the proposed control strategy.

Reduction of Starting Current in Large Induction Motors

Large induction motors can have a high inrush and run-up current during starting, often up to ten times the rated current. In weak supplies, this could be a problem, causing system stability issues and the voltage to dip below acceptable levels. In islanded systems, the capacity could be pulled below its maximum. There are several different starting methods possible, but they are often only suitable for smaller machines. One method not investigated is the use of parallel capacitor compensation during the starting because large induction motors are very inductive during the starting sequence, so that supplying reactive power may be more effective than supplying energy. This paper first investigates several different induction motors with increasing size and assesses their compensation requirements in terms of the reactive power requirement during starting. It is shown that they do generally become more inductive as they increase in size. It is illustrated, using simulations, that using parallel capacitors during starting can significantly reduce the starting current. The concept is tested using a small experimental motor. Series inductors are added to the motor to make it more inductive and look more like a larger machine. The experimental results confirm that the method works. It is also found that the parallel capacitors require series filters to prevent harmonic current, and these can be realized using inductors in series with the compensation capacitors. Point-on switching using solid-state relays was tested, and these can reduce the transient switch-on current over the first voltage cycle.

Enhancement of the System Stability of DB-Controlled VSC Links Parallel Operated with a Weak Multi-Machine AC Power System

To allow the large-scale integration of renewable energy sources into the grid, VSC-HVDC is commonly utilized. However, with greater integration, several power system stability issues arise. In this study, we examined the small-signal rotor angle stability of a model of the Australian power system with embedded VSC-based HVDC links. A simplified model of the Australian power network was used to connect the potential geothermal resources in the region of Innamincka using a 1100 km HVDC link. We observed that the introduction of the new source of geothermal power generation had an adverse impact on the damping performance of the system. Therefore, two forms of stabilization are examined here: (i) generator power system stabilizers (PSS) fitted to the synchronous machines, which are used to convert geothermal energy to electrical power; and (ii) power oscillation damping controllers (PODs) fitted to the VSC-HVDC link. In the case of the PODs, two types of stabilizing input signals are considered: (i) local signals such as power flow in adjacent AC lines, and (ii) wide-area signals such as bus voltage angles at key nodes in the various regions of the system. It was concluded that the small-signal rotor angle stability of the interconnected AC/DC system can be greatly enhanced by employing the designed damping controllers.

State of the Art of the Techniques for Grid Forming Inverters to Solve the Challenges of Renewable Rich Power Grids

To mitigate the fast-growing demand of electrical energy, the use of renewable energy resources, e.g., solar and wind, can offer an environmentally friendly and sustainable solution. Due to their intermittent nature, the grid connected operation of renewable energy resources provides a better performance compared to the standalone operation. However, the massive penetration of power electronic inverter/converter-interfaced renewable resources in power systems introduces new issues, such as voltage and frequency instabilities, because of their inherent low inertia properties. As a consequence, these issues may lead to serious problems, such as system blackouts. Therefore, there is an immediate demand to solve these new issues and ensure the normal performance of the power system with the large penetration of renewable energy resources. To achieve this, grid connected inverters/converters are designed to address these problems and behave as synchronous generators, which is possible with grid forming (GFM) inverters/converters concepts. This paper reviews the recent advancement of GFM converters for solving emerging issues related to the renewable rich power grids. It also provides a comprehensive review on frequency deviations and power system stability issues in low-inertia systems and recent advancements in control methods for harmonic mitigation. It is expected that this paper will help the research community to enhance the technology further to solve the challenges in renewable rich power grids.

Exploration of new analytical correlations as an alternative to the Kramers-Kronig transforms for the assessment of impedance spectroscopy data

• Alternative method to detect errors in EIS spectra. • Overcome of some practical issues for assessment of simple spectra. • Elucidation of analytical correlations between magnitude and phase. New analytical correlations between impedance magnitude and phase are developed and presented. These correlations are used for the assessment of impedance spectroscopy data. As correlations are obtained, they can be calculated point to point at each frequency of the spectra with no need to establish explicit premises related to stability, linearity or finite limits for their derivation. Their use is simpler than that based on the direct evaluation of the Kramers-Kroning transforms or alternative methods. An example of their derivation from basic equations involving complex numbers is described. They were obtained by looking for an explanation of the empirical fact that the slope of the Bode-Magnitude diagram vs frequency resembles the shape of the corresponding Bode-Phase diagram. Unlike the Kramers-Kronig transform, these new correlations can also be directly applied to test spectra with highly predominant capacitive or inductive responses or even incomplete loops. Their analytical expressions are exact for simple ideal elements and circuits, including the Warburg diffusion element. These correlations were tested with simulated spectra altered with known random error distributions, and they were able to detect the random distribution and the error level for simple spectra when the errors were > 0.5%. For more sophisticated spectra, the minimum error that can be detected without interference of the deviations due to the proper algorithm are around 2.5%. No exact correlation was found for a constant phase element (CPE), but a close empirical approximation was obtained for a single CPE. It is necessary to improve this approximation when a CPE is combined with some other elements because of detected deviations. In addition, it was found that in a first approach the algorithm does not detect non-linear behavior on a simple experimental circuit, but the test gave insights of how to detect it. On the contrary, it is well suited for detection of system stability issues. Examples of their application to actual experimental spectra, high capacitive or with several loops, are presented and the limitations discussed. More work and exhaustive tests are necessary to improve the method and stablish its real limitations, but its use for assessment of simple spectra at certain error level can already be done. Given that the derivation of the new correlations is only based on its complex number nature, this study concludes that the magnitude and phase of any complex number or 2D vector are not independent, and it is expected that similar correlations can be applied to any frequency-dependent complex variable, vector or transfer function, such as those used in optics or rheology.