Compression and Restoration Identification Method of Wide-band Oscillation Data Based on Autoencoder

The dynamic characteristics of power systems have become increasingly complex with the growing application of power electronics equipment. A high level of real-time monitoring is now required to provide a database for system stability and safety control. Therefore, flexible and accurate sensor technology is crucial. In this article, a noncontact current sensing method is proposed using tunnel magnetoresistance (TMR) technology. Based on the introduction of TMR chip characteristics, the sensing law of a TMR chip surrounding a current-carrying wire is revealed. An arrangement of four TMR chips is then proposed to reflect the magnetic field intensity around a current-carrying wire. A TMR chip array-based noncontact current sensing technique is presented for use as a real set-and-use current sensing method. The convenience of the proposed method is superior to traditional current sensors because the wire does not need to be surrounded by a magnetic ring or coil. A method for location detection is presented to avoid iterating for every sample, which significantly reduces the computation burden. Simulations are then carried out to demonstrate the effectiveness of the proposed method. A current sensor prototype based on a printed circuit board (PCB) is developed, and its practicality is proven by experiments. Test results show that the prototype can meet the requirements of phasor measurement unit (PMU) standards, indicating that the proposed current sensing method is practical and can be applied in M-class and P-class PMUs for current sensing.

To guarantee renewable energy resources accommodation of power system, the use of energy storage facilities has become an inevitable trend. Owing to the various operation restrict of different energy storage facilities, it’s difficult to realize the stable operation and the renewable energy accommodation of the power system with only one kind of energy storage facility. To solve this problem, the dynamic characteristics of power system with various types of energy storage devices are studied in this paper. Through the Individual Based Model (IBM) method, the dynamic model of power system under the background of large-scale renewable energy accommodation is established. This model is tested in typical situations, and the precision and computation efficiency of the IBM are proved.

Power system is one of the largest man-made systems, which over the years has become the vital infrastructure for modern life. The foundation of today’s power system is three-phase alternating current (AC), which is adopted as the main stream technology for its advantages in voltage transforming, wide-area networking and long-distance power transmitting. The AC power system is a self-sustained oscillatory system operating at nominal frequency, i.e., 50 or 60 Hz. However, the multi-time-scale dynamics in a power system, mechanical, electrical or their coupled are prone to cause the exchange of energy at wide range of frequencies other than the nominal one, which is collectively known as the oscillation issues in a power system. Such oscillations would lead to power quality degradation, equipment failure, or even worse, system instability. Actually, the development history of power system is also a history of continuous “battle” against the oscillation problems. This article reviews the basic concepts and classification of the classical as well as emerging power system oscillations. The mechanism, origin and research advances of various oscillations are re-visited and discussed, from the earlier and long-standing low frequency oscillation (LFO), and then subsynchronous oscillation/resonance (SSO/SSR) associated with turbo-generators and wind turbine generators, to the latest wide-band oscillations involving the sophisticated dynamics of increasing renewables and power electronics in a power system. LFO incident was reported for the first time in 1964 in American Western Interconnection, where the formation of a larger power system by combining two smaller one, i.e., Northwest and Southwest systems, caused power oscillation at about 0.1 Hz. Later studies showed that the multiple machines with mechanical inertial but electrically connected through networks function like a mass-spring system, leading to LFOs at a frequency ranging from 0.01 to 2.5 Hz, depending on the size of the system. Initially, excitation control was improved by adding the function of power system stabilizer (PSS) to mitigate LFO. Later, advanced control, including linear optimal control, nonlinear control and optimal decentralized coordinated control, were developed to solve the problem. Since 2000, the continuous increase of system size and coverage causes very-low-frequency oscillation issues, to address which, several new technologies, for instance, wide-area monitoring and control, flexible AC transmission system (FACTS) control, has been commissioned in China and around the world. SSR/SSO is induced by the interactions between the multi-mass shaft of a turbo-generator and the series-compensated AC or HVDC transmissions. The frequency of power oscillation is subsynchronous, or less than the nominal frequency but generally above the 2.5 Hz. The first SSR incident was captured at Mohave Power generating Station in 1970. In China, however, SSR/SSO has been a severe stability concern since 2000, the time witnessing the widely usage of series compensation and HVDC to transfer electricity from remote coal-fueled power plants. After more than ten years’ continuous research, we have developed effective tools and countermeasures, for instance, multi-dimensional analysis, optimized control and coordinated protection, to solve practical SSR/SSO problems in China and some other countries. The integration of wind power introduces new interactive dynamics that involve wind turbine converters and AC grids. It is called sub-/super-synchronous control interaction (SSCI), which would result in a different type of oscillation from several Hz to double nominal frequency. Such sub/super-synchronous oscillations associated with wind power has entered people’s vision since 2009 and gained widespread attention after the occurrence of several actual incidents in US and China. To address this new issue, we have developed novel frequency-domain modeling and analysis methods to quantify the risk first, and then control strategies on either generator/converters side or grid side to modify the interaction to stabilize SSCI. These methods and strategies have been put into practice, for instance in Guyuan and Hami systems in China, to verify their effectiveness. At this moment, power system is undergoing profound changes, one of which is the rapid growth of renewables and power electronics in all sections, including generation, transmission and consumption of electricity. Such a change is triggering power system oscillations in a very wide band, i.e., from several Hz to several thousand Hz. The underlying reason is the multi-time-scale dynamic interactions among the huge number of converters and the increasingly complicated power grid. This leads to open challenges that are yet to be solved, including the need of: (1) Wide-spectrum models to represent the multi-time-scale dynamics; (2) advanced analysis methods to quantify the stability of wide-band oscillations; and (3) adaptive and coordinated controls to mitigate the oscillation under varying system conditions. In a nutshell, systematic and in-depth researches are required to establish new theories and methodologies for this emerging issue so as to promote the sustainable growth of renewable energy and the low-carbon development of power system.

The article established a reduced-order state space model for the grid connected system of a PMSG-based wind farm containing SVG. And it was found that SVG in wind farms may cause wideband oscillation. The influence of the number of wind turbine, active power, reactive power of SVG on wideband oscillation was studied. In order to suppress wideband oscillation, a damping controller for wideband oscillation in PMSG-based wind farm with SVG was proposed. Modal analysis and time-domain simulation analysis were conducted on the grid connected power system of a PMSG-based wind farm containing SVG. The effectiveness of the wideband oscillation damping controller was verified.

This paper proposes a new control scheme for variable speed wind turbines with permanent magnet synchronous generators (VSWT-PMSG) based offshore wind farm (WF), which is connected to the main onshore grid through voltage source converter (VSC) based high voltage DC (HVDC) transmission system, to decrease the frequency fluctuations of the onshore grid. A centralized droop controller for VSWT-PMSGs is designed in order that the offshore WF can control the frequency oscillations of the main grid in which a large scale of WF composed of fixed speed wind turbines with squirrel cage induction generators (FSWT-SCIGs) is installed. In the proposed system, control of the frequency oscillations is performed by adopting the deloading operation. The simulation analysis is performed on a model system composed of synchronous generators (SGs), FSWT-SCIGs based WF, and VSWT-PMSGs based offshore WF to show the effectiveness of the proposed coordinated control system.

The political agenda on wind power usage intends its further expansion in a large scale. As most energy sources, wind power can have negative impacts on humans and environment; this expansion can be accompanied by land use conflicts with land uses sensitive to disturbance. During operation, disturbances from noise, shadow, or ice throw can occur. Due to the dimensions of modern wind power systems, wind power farming can pose a threat to birds and bats (collision and avoidance) and may also lead to a change of landscape sceneries, which can cause conflicts with residents, nature conservation, or tourism interests. Therefore, the control of wind power expansions by spatial planning plays a key role for the mitigation of negative impacts as well as for its public acceptance. Spatial planning offers instruments to resolve potential conflicts with affected stakeholders. On a regional level, the determination of priority and exclusion areas for the use of wind power based on functional criteria represents the most essential planning measure. For the protection of affected residents and nearby housing areas, safety distance regulations are normally applied. Since most distance regulations are defined as fixed distance values, the question arises: if a static approach sufficiently considers the technical state and the further development of wind power systems with increasing plant heights as well as cumulating effects of large wind farms, i.e. cumulated noise effects that rise with the number of spin wheels. To take these factors better into account, the determination of safety distance could be dynamically bound to power plant height and wind farm size. This article introduces a dynamic approach for dimensioning safety distances, which consists of a formula to calculate distances in relation to the height of the wind power plants and the number of spin wheels. The formula takes shading, noise, and icefall into account. It is relevant for wind farm planning, as it does not only allow for determining distances from sensible land uses to wind power plants, but also allows for assessing variants of wind farms in terms of height and number of the spin wheels in a given area.

This paper proposes a design of robust power system stabilizer (RPSS) based on inverse additive perturbation optimization in an interconnected power system with wind farms. In the design, system uncertainties are represented by the inverse additive model. The robust stability condition is used to form the optimization problem of PSS parameters. The structure of PSS is a conventional second-order lead-lag controller. The genetic algorithm is applied to solve the problem and achieve the PSS parameters. Simulation studies in the two-area four-machine system with wind farms confirm that the damping effect and robustness of the proposed PSS are superior to those of the compared PSS.

Wind turbines are increasingly connected to the bulk power grid through electronic devices. Compared with the dynamic characteristics of traditional power system, transient characteristics are dramatically changed. Recognizing the transient characteristics of large-scale wind power connected to the bulk power grid and proposing practical and feasible transient control strategies for wind turbines are important to the safe and stable operation of current power grid. This paper focuses on the interactive characteristics of double-fed induction generator (DFIG) coupled to the power grid of receiving-end. A DFIG-based wind farm can be reduced to a single DFIG wind turbine by simplifying it, transient dynamics of the wind turbine, such as output fault current characteristics, under different fault levels of power grid are analyzed. Moreover, according to the fault ride through (FRT) standard of wind farms, FRT control strategies of DFIG wind turbines under different fault levels of power grid are presented to form a coordinated fault ride-through control scheme. Finally, a case study was conducted with MATLAB/Simulink. The simulation results verified the effectiveness and feasibility of the interactive characteristics analysis and the proposed FRT control scheme of DIFG-based wind farms connected to the receiving power grid.

Recent developments in power systems to build a smart grid depend critically on communication networks which provide unprecedented advantages for comprehensive system visibility, monitoring, protection, and control. However, it increases the system complexity and vulnerability to cyberattacks that could jeopardize the seamless system operation. The attack must be detected effectively, and then proper measures to mitigate the effect quickly to restore normality. This work implements a reduced-order <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> filter to simultaneously estimate the state variable and unknown inputs such as noise or attack signals in the automatic generation control (AGC) system. Further, the knowledge of the disturbances is utilized to mitigate the attack by appropriately compensating the sensor readings, such that the control decisions are based on the correct states, not the corrupted signals generated in the attack scenario. The stability criterion is provided based on Lyapunov functions to check the estimation error in the presence of the exogenous disturbance. Further, the proposed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> estimator performance is evaluated by comparing it with the Kalman filter to verify its effectiveness. The estimator’s performance is validated by developing a cosimulation platform using the server–client architecture of data exchange. Further, the performance is validated in a real-time digital simulator (RTDS) platform used as the power system interacting with an estimator deployed on Raspberry Pi board sensing the attacks.

Accurate short-term forecasting of wind farm power generation is of great significance to economic development and stable operation of power system. In order to improve the accuracy of wind power prediction, this paper presents a short-term wind power prediction method based on empirical mode decomposition and deep learning. We firstly decompose historical data into two-dimensional tensors by using empirical mode decomposition, and then extract the local features of data by using convolutional neural network. The features are transmitted to the bidirectional long short-term memory for prediction. The measured wind power data form wind farm in Xinjiang are used for verification. We use root mean square error and mean absolute error as evaluation indexes to test the algorithm. Results of the experiment show that the reconstructed two-dimensional tensor is beneficial to the ability of convolutional neural network to extract local features, and the prediction accuracy of our method is higher than that of other traditional prediction algorithms.

Modeling and Verification of Dependable Electronic Power System Architecture

The electronic power system can be viewed as a system composed of a set of concurrently interacting subsystems to generate, transmit, and distribute electric power. The complex interaction among sub-systems makes the design of electronic power system complicated. Furthermore, in order to guarantee the safe generation and distribution of electronic power, the fault tolerant mechanisms are incorporated in the system design to satisfy high reliability requirements. As a result, the incorporation makes the design of such system more complicated. We propose a dependable electronic power system architecture, which can provide a generic framework to guide the development of electronic power system to ease the development complexity. In order to provide common idioms and patterns to the system *designers, we formally model the electronic power system architecture by using the PVS formal language. Based on the PVS model of this system architecture, we formally verify the fault tolerant properties of the system architecture by using the PVS theorem prover, which can guarantee that the system architecture can satisfy high reliability requirements. KeywordsSystem Architecture; PVS System; Fault Tolerance; Formal Modeling; Formal Verification.

This paper outlines an approach to perform small-signal stability analysis of a power network with conventional synchronous generators and a wind farm composed of Type-3 wind turbines as the number of turbines in the farm is varied. An enabling ingredient to perform this analysis is a dynamic reduced-order aggregate model for a wind farm that preserves the model order and structure of individual wind turbines. This facilitates stability analysis since the number of wind turbines can be varied with ease and small-signal stability of the mixed machine and inverter-interfaced turbines can be examined systematically. Although there is a vast body of literature on small-signal stability of wind farms, penetration level of wind farms is significantly less studied in this context; this paper introduces a systematic approach for such an analysis. Case studies for a modified Kundur two-area system with an integrated wind farm indicate that as the number of wind turbines is increased to a point that the penetration level is approximately 25%, there is a loss of small-signal stability. We validate this with time-domain simulations for the nonlinear system dynamics and also propose a redesign strategy grounded in a system-theoretic analysis of the dynamical models.

In recent years, sub-synchronous oscillation incidents have been reported to happen globally, which seriously threatens the safe and stable operation of the power system. It is difficult to locate the oscillation source in practice using the parameterized model of open-loop modal resonance. Therefore, this paper aims at the problem of oscillation instability caused by the interaction between the multiple voltage source converters in the wind farm grid-connected system, proposes a method for locating the oscillation source of a wind farm using measurement data based on the transfer learning algorithm of transfer component analysis. At the same time, in order to solve the problem of the lack of oscillation data and the inability to label in the real system, a simplified simulation system was proposed to generate large batches of labeled training samples. Then, the common features of the samples from simulation system and the real system were learned through the transfer component analysis algorithm. Afterward, a classifier was trained to classify samples with common features. Finally, two grid-connected wind farms with VSC access are used to verify that the proposed method has good locating performance. This has important reference value for the practical application of power grid dispatching and operation using measurement to identify oscillation sources.

This paper presents a review study on the data communication over power-lines, commonly referred to as power-line carrier, power-line communication (PLC), mains communications, or power-line digital subscriber line (PDSL). This study examines the technical and application advantages and challenges associated with adopting PLC as a preferred alternative technology for wideband or broadband data communication. The broader coverage area of the PLC network gives it a distinct advantage over other communication network technologies. Additionally, implementing a communication system using the existing power-line network is more cost-effective and less time-consuming compared to constructing a new network from scratch. However, the primary challenge lies in the fact that the power-line network is primarily designed for the distribution of electrical power within the frequency range of 50-60 Hz including the harmonics. This poses various obstacles such as electrical noise from appliances, signal distortions caused by the unregulated nature of the wiring, transformer bypassing, interference from high-frequency modulation, and variations in characteristic impedances, among others. Despite these challenges, the emergence of robust modulation techniques like Orthogonal Frequency Division Multiplexing (OFDM) and Direct-Sequence Spread Spectrum (DSSS), along with the development of Application-Specific Integrated Circuit (ASIC) density with improved processing speeds, as well as advancements in signal processing and error control coding techniques, have made the PLC network the most promising telecommunications access network.