41 results on '"XiaoZhe Wang"'
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2. A Data-Driven Sparse Polynomial Chaos Expansion Method to Assess Probabilistic Total Transfer Capability for Power Systems with Renewables
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Xiaoting Wang, Xiaozhe Wang, Xi Lin, and Hao Sheng
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Signal Processing (eess.SP) ,Mathematical optimization ,Computer science ,020209 energy ,Probabilistic logic ,Energy Engineering and Power Technology ,02 engineering and technology ,Variance (accounting) ,Data-driven ,Electric power system ,Transmission (telecommunications) ,Transfer (computing) ,FOS: Electrical engineering, electronic engineering, information engineering ,0202 electrical engineering, electronic engineering, information engineering ,Probability distribution ,Electrical Engineering and Systems Science - Signal Processing ,Electrical and Electronic Engineering ,Random variable - Abstract
The increasing uncertainty level caused by growing renewable energy sources (RES) and aging transmission networks poses a great challenge in the assessment of total transfer capability (TTC) and available transfer capability (ATC). In this paper, a novel data-driven sparse polynomial chaos expansion (DDSPCE) method is proposed for estimating the probabilistic characteristics (e.g., mean, variance, probability distribution) of probabilistic TTC (PTTC). Specifically, the proposed method, requiring no pre-assumed probabilistic distributions of random inputs, exploits data sets directly in estimating the PTTC. Besides, a sparse scheme is integrated to improve the computational efficiency. Numerical studies on the modified IEEE 118-bus system demonstrate that the proposed DDSPCE method can achieve accurate estimation for the probabilistic characteristics of PTTC with a high efficiency. Moreover, numerical results reveal the great significance of incorporating discrete random inputs in PTTC and ATC assessment, which nevertheless was not given sufficient attention., Comment: Accepted by IEEE Transactions on Power Systems for future publication
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- 2022
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3. Markov Game for Securing Wide-Area Damping Control Against False Data Injection Attacks
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Qingyang Li, Xiaozhe Wang, Ilias Zenelis, Li Zhu, Shichao Liu, and Yang Li
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Computer Networks and Communications ,Computer science ,020209 energy ,media_common.quotation_subject ,Control (management) ,0211 other engineering and technologies ,Markov process ,02 engineering and technology ,symbols.namesake ,Mode (computer interface) ,0202 electrical engineering, electronic engineering, information engineering ,Electrical and Electronic Engineering ,Function (engineering) ,media_common ,021103 operations research ,business.industry ,Physical layer ,Minimax ,Telecommunications network ,Computer Science Applications ,Control and Systems Engineering ,symbols ,business ,Markov game ,Information Systems ,Computer network - Abstract
While wide-area communication networks facilitate the exchange of measurements and control signals for wide-area damping controllers, they bring in new threats of cyberattacks. This article formulates the dynamic interaction between an intelligent spoof attacker and the wide-area damping control (WADC) center as a zero-sum two-player Markov game. In this Markov game, the attacker intelligently spoofs the communication links sending wide-area control signals to selected generators while the WADC selectively encrypts transmitted control signals with limited cyberresources. The successful spoof of specific communication links leads to the degradation of the WADC performance and even to system instability indicated by the real part of the targeted interarea oscillation mode. The potential performance degradation in the physical layer is uniquely included in the cost function of this game while the other two parts of the cost function are the cybersecurity investments of both the attacker and the WADC (defender). The minimax Q-learning approach is used to obtain the optimal defense and attack strategies. Simulation results show that the strategies for the attacker and the WADC converge within 3000 iterations by using the minimax Q-learning approach. The proposed Markov game provides a cyberphysical framework to make the optimal defense strategy for the WADC.
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- 2021
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4. WAMS-Based Model-Free Wide-Area Damping Control by Voltage Source Converters
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Ilias Zenelis, Boon-Teck Ooi, Jinpeng Guo, and Xiaozhe Wang
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Computer science ,020209 energy ,Control (management) ,Energy Engineering and Power Technology ,Systems and Control (eess.SY) ,02 engineering and technology ,Model free ,Converters ,Network topology ,Electrical Engineering and Systems Science - Systems and Control ,Wide area ,Control theory ,FOS: Electrical engineering, electronic engineering, information engineering ,0202 electrical engineering, electronic engineering, information engineering ,Voltage source ,Electrical and Electronic Engineering ,Decoupling (electronics) - Abstract
In this paper, a novel model-free wide-area damping control (WADC) method is proposed, which can achieve full decoupling of modes and damp multiple critical inter-area oscillations simultaneously using grid-connected voltage source converters (VSCs). The proposed method is purely measurement based and requires no knowledge of the network topology and the dynamic model parameters. Hence, the designed controller using VSCs can update the control signals online as the system operating condition varies. Numerical studies in the modified IEEE 68-bus system with grid-connected VSCs show that the proposed method can estimate the system dynamic model accurately and can damp inter-area oscillations effectively under different working conditions and network topologies.
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- 2021
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5. Local blackout and global power system wide blackout are caused by non‐linear negative damping
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Jinpeng Guo, Boon-Teck Ooi, and Xiaozhe Wang
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Computer science ,020209 energy ,05 social sciences ,Blackout ,050301 education ,Energy Engineering and Power Technology ,02 engineering and technology ,Phase plane ,Fault (power engineering) ,Electric power system ,Control and Systems Engineering ,Control theory ,Limit (music) ,0202 electrical engineering, electronic engineering, information engineering ,medicine ,Trajectory ,Waveform ,Transient (oscillation) ,Electrical and Electronic Engineering ,medicine.symptom ,0503 education - Abstract
Local blackout occurs when the transient stability limit is exceeded after a transmission line fault. As to global blackout, a recording of the 10 August 1996-WECC blackout shows that it was accompanied negative damping. A turbine-generator swinging against an infinite bus is used to approximate the dynamics leading to the WECC blackout. There is no analytic solution when non-linearity is included. Small-signal linearisation shows that negative damping can occur but cannot produce the waveform recorded in the WECC blackout. Therefore, the graphical phase-plane method, which is easy to use, is resorted to. The study shows that the kernel of non-linearity consists of the gradients which produce limit cycles. Positive or negative damping is produced by shifting the gradients of the limit cycles to the right or left in the direction of the trajectory. The study makes a contribution by showing that phase plane can be used to study the impact of multiple independent controllers. A worked example shows when transient stability limit is exceeded, local blackout occurs. The swing equation of local blackout is applied to the WECC blackout. As proof that negative damping was due to non-linearity, a waveform having the frequency of the recorded WECC blackout is presented.
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- 2020
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6. Harmonic circulation and DC voltage instability mechanism of parallel‐SVG system
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Qirong Jiang, Guoqing Li, Hui Shao, Jikai Chen, Jiangchao Qin, Yiping Cheng, Chu Sun, and Xiaozhe Wang
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Physics ,Renewable Energy, Sustainability and the Environment ,020209 energy ,020208 electrical & electronic engineering ,Scalable Vector Graphics ,Resonance ,Topology (electrical circuits) ,02 engineering and technology ,computer.file_format ,Topology ,Instability ,Transfer function ,0202 electrical engineering, electronic engineering, information engineering ,Harmonic ,Output impedance ,computer ,Pulse-width modulation - Abstract
A parallel static var generator (SVG) system based on cascaded H-bridge topology in wind afflux station is analysed in this study to reveal the mechanism of harmonic current and DC voltage instability due to the phase difference between the PWM carriers. First, the inherent relation of harmonic current and low-frequency disturbance is revealed by carrier-phase-shift pulse-width-modulation (CPS-PWM) theory. Second, to identify the negative impact of low-frequency disturbance, a small-signal circuit model is built to research the electric coupling relation between SVGs and the grid, then pointing out the main factors which affect the harmonic circulation among the two-paralleled SVGs. Third, the output impedance and the transfer function of SVG give an insight into the interaction between SVG and low-frequency resonance characteristics, based on which a virtual resistance method is proposed to shape the resonant peak. Finally, theoretical analysis and system experiment prove that the proposed control strategy can rapidly attenuate low-frequency resonant peaks of the system, avoiding the DC voltage instability in the SVG system when harmonic circulation occurs.
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- 2020
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7. Online Model-Free Estimation of the Dynamic System Model for a Power System With Renewables in Ambient Conditions
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Boon-Teck Ooi, Jinpeng Guo, and Xiaozhe Wang
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Online model ,Mathematical optimization ,General Computer Science ,Computer science ,020209 energy ,ComputerApplications_COMPUTERSINOTHERSYSTEMS ,Topology (electrical circuits) ,02 engineering and technology ,network topology change ,Network topology ,7. Clean energy ,online estimation ,Electric power system ,dynamic system model estimation ,0202 electrical engineering, electronic engineering, information engineering ,General Materials Science ,Estimation ,Distributed RES ,Dynamic system model ,missing measurements ,business.industry ,General Engineering ,Renewable energy ,lcsh:Electrical engineering. Electronics. Nuclear engineering ,business ,lcsh:TK1-9971 - Abstract
In this paper, an online model-free method is proposed to estimate the dynamic model of a power system with distributed renewable energy sources (RES). The proposed method, requiring no knowledge of network topology and model parameters, is computationally efficient and can be implemented online. The impact of missing PMUs is evaluated in detail, which shows that most entries of the dynamic model can still be well estimated in the case of missing PMUs. Simulation studies in the modified IEEE 68-bus system demonstrate that the proposed method can provide accurate estimation of the dynamic model in different operating conditions. The method can help detect topology change even when some PMUs are lost.
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- 2020
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8. A Data-Driven Uncertainty Quantification Method for Stochastic Economic Dispatch
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Rong-Peng Liu, Xiaoting Wang, Yunhe Hou, Francois Bouffard, and Xiaozhe Wang
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Signal Processing (eess.SP) ,Mathematical optimization ,Wind power ,business.industry ,Computer science ,020209 energy ,Cumulative distribution function ,Monte Carlo method ,Economic dispatch ,Energy Engineering and Power Technology ,Probability density function ,02 engineering and technology ,Surrogate model ,FOS: Electrical engineering, electronic engineering, information engineering ,0202 electrical engineering, electronic engineering, information engineering ,Probability distribution ,Electrical and Electronic Engineering ,Uncertainty quantification ,Electrical Engineering and Systems Science - Signal Processing ,business - Abstract
This letter proposes a data-driven sparse polynomial chaos expansion-based surrogate model for the stochastic economic dispatch problem considering uncertainty from wind power. The proposed method can provide accurate estimations for the statistical information (e.g., mean, variance, probability density function, and cumulative distribution function) for the stochastic economic dispatch solution efficiently without requiring the probability distributions of random inputs. Simulation studies on an integrated electricity and gas system (IEEE 118-bus system integrated with a 20-node gas system are presented, demonstrating the efficiency and accuracy of the proposed method compared to the Monte Carlo simulations., Accepted by IEEE Transactions on Power Systems for future publication
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- 2021
9. Targeted False Data Injection Attacks Against AC State Estimation Without Network Parameters
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Marthe Kassouf, Georgia Pierrou, Xiaozhe Wang, and Mingqiu Du
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Data processing ,General Computer Science ,Computer science ,020209 energy ,Real-time computing ,Process (computing) ,020206 networking & telecommunications ,Topology (electrical circuits) ,Systems and Control (eess.SY) ,02 engineering and technology ,Construct (python library) ,Phasor measurement unit ,Electrical Engineering and Systems Science - Systems and Control ,Data modeling ,Electric power system ,FOS: Electrical engineering, electronic engineering, information engineering ,0202 electrical engineering, electronic engineering, information engineering ,State (computer science) - Abstract
State estimation is a data processing algorithm for converting redundant meter measurements and other information into an estimate of the state of a power system. Relying heavily on meter measurements, state estimation has proven to be vulnerable to cyber attacks. In this paper, a novel targeted false data injection attack (FDIA) model against AC state estimation is proposed. Leveraging on the intrinsic load dynamics in ambient conditions and important properties of the Ornstein-Uhlenbeck process, we, from the viewpoint of intruders, design an algorithm to extract power network parameters purely from PMU data, which are further used to construct the FDIA vector. Requiring no network parameters and relying only on limited phasor measurement unit (PMU) data, the proposed FDIA model can target specific states and launch large deviation attacks. Sufficient conditions for the proposed FDIA model are also developed. Various attack vectors and attacking regions are studied in the IEEE 39-bus system, showing that the proposed FDIA method can successfully bypass the bad data detection and launch targeted large deviation attacks with very high probabilities.
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- 2021
10. A Data-Driven Energy Storage System-Based Algorithm for Monitoring the Small-Signal Stability of Power Grids with Volatile Wind Power
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Ilias Zenelis, Georgia Pierrou, and Xiaozhe Wang
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020209 energy ,0202 electrical engineering, electronic engineering, information engineering ,FOS: Electrical engineering, electronic engineering, information engineering ,02 engineering and technology ,Systems and Control (eess.SY) ,7. Clean energy ,Electrical Engineering and Systems Science - Systems and Control - Abstract
In this paper, we propose a data-driven energy storage system (ESS)-based method to enhance the online small-signal stability monitoring of power networks with high penetration of intermittent wind power. To accurately estimate inter-area modes that are closely related to the system's inherent stability characteristics, a novel algorithm that leverages on recent advances in wide-area measurement systems (WAMSs) and ESS technologies is developed. It is shown that the proposed approach can smooth the wind power fluctuations in near real-time using a small additional ESS capacity and thus significantly enhance the monitoring of small-signal stability. Dynamic Monte Carlo simulations on the IEEE 68-bus system are used to illustrate the effectiveness of the proposed algorithm in smoothing wind power and estimating the inter-area mode statistical properties., Comment: Accepted for presentation in IEEE PES General Meeting 2021
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- 2021
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11. Online purely data-driven estimation of inertia and center-of-inertia frequency for power systems with VSC-interfaced energy sources
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Jinpeng Guo, Xiaozhe Wang, and Boon-Teck Ooi
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020208 electrical & electronic engineering ,0103 physical sciences ,0202 electrical engineering, electronic engineering, information engineering ,Energy Engineering and Power Technology ,02 engineering and technology ,Electrical and Electronic Engineering ,010303 astronomy & astrophysics ,01 natural sciences - Published
- 2022
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12. Nonlinear negative damping caused August 10, 1996-WECC blackout
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Boon-Teck Ooi, Xiaozhe Wang, and Jinpeng Guo
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Phase portrait ,Computer science ,020209 energy ,Blackout ,02 engineering and technology ,Nonlinear system ,Computer Science::Systems and Control ,Linearization ,Control theory ,0202 electrical engineering, electronic engineering, information engineering ,medicine ,Transient (oscillation) ,medicine.symptom ,Damping torque - Abstract
This paper shows that the August 10, 1996-WECC blackout originated from negative damping arising from sin6 nonlinearity. The proof is based on keeping the nonlinearity in the dynamic equation of a turbine-generator swinging against an infinite bus. Small signal perturbation linearization can predict the occurrence of negative damping. But the linear approach cannot produce the negatively damped waveform of the WECC blackout. Therefore, the graphical Phase Plane method is resorted to. As MatLab, MATHEMATICA, Wolfram MathWorld, etc. offer software plotters, the phase plane method is not difficult to use. Phase portraits show that the “Swing Equation” has stable and unstable regions. The WECC blackout happened because the initial states fell in the unstable region. Although dismissed as being limited to two-dimensions, the paper makes a contribution by showing that phase plane can be used to study the impact of 3 independent controllers. A worked-example shows when the independent controllers (turbine torque, the generator counter-torque and the damping torque) cannot meet the Transient Stability Limit after a line short circuit fault, local blackout occurs. The global WECC blackout is considered to be a scaled up local blackout. Instead of a turbine-generator swinging against an infinite bus, the last stage of the August 10, 1996-WECC blackout is assumed to be the Seattle-area swinging against the California-area. A phase portrait is found in the unstable region whose trajectory unravels in several cycles. Time-domain simulation shows a waveform oscillating with same number of cycles, which qualitatively matches the waveform of the August 10, 1996-WECC blackout.
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- 2020
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13. Measurement-Based Estimation of System State Matrix for AC Power Systems with Integrated VSCs
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Boon-Teck Ooi, Xiaozhe Wang, and Jinpeng Guo
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Signal Processing (eess.SP) ,Work (thermodynamics) ,Basis (linear algebra) ,Computer science ,020209 energy ,System of measurement ,Systems and Control (eess.SY) ,02 engineering and technology ,Converters ,Network topology ,Electrical Engineering and Systems Science - Systems and Control ,Matrix (mathematics) ,Control theory ,FOS: Electrical engineering, electronic engineering, information engineering ,0202 electrical engineering, electronic engineering, information engineering ,Voltage source ,State (computer science) ,Electrical Engineering and Systems Science - Signal Processing - Abstract
In this paper, a wide-area measurement system (WAMS)-based method is proposed to estimate the system state matrix for AC system with integrated voltage source converters (VSCs) and identify the electromechanical modes. The proposed method is purely model-free, requiring no knowledge of accurate network topology and system parameters. Numerical studies in the IEEE 68-bus system with integrated VSCs show that the proposed measurementbased method can accurately identify the electromechanical modes and estimate the damping ratios, the mode shapes, and the participation factors. The work may serve as a basis for developing WAMS-based damping control using VSCs in the future., Copyright 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
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- 2020
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14. Online PMU-Based Method for Estimating Dynamic Load Parameters in Ambient Conditions
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Georgia Pierrou and Xiaozhe Wang
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Computer science ,Noise (signal processing) ,020209 energy ,020208 electrical & electronic engineering ,1. No poverty ,Process (computing) ,Recursion (computer science) ,Ornstein–Uhlenbeck process ,02 engineering and technology ,Systems and Control (eess.SY) ,Electrical Engineering and Systems Science - Systems and Control ,Dynamic load testing ,Electric power system ,Control theory ,Robustness (computer science) ,0202 electrical engineering, electronic engineering, information engineering ,FOS: Electrical engineering, electronic engineering, information engineering ,Online algorithm - Abstract
This paper proposes a novel purely measurement-based method for estimating dynamic load parameters in near real-time when stochastic load fluctuations are present. By leveraging on the regression theorem for the Ornstein-Uhlenbeck process, the proposed method can provide highly accurate estimation without requiring any information about the power system model. Furthermore, by exploiting recursion, an online algorithm is developed to estimate the dynamic load parameters in near real-time. Simulation studies on the IEEE 39-Bus system demonstrate the accuracy of the model-free method, its robustness against measurement noise, as well as its satisfactory performance in tracking real-time changes of the load parameters., To appear in 2020 IEEE PES General Meeting, August 2-6 2020, Montreal, Quebec, Canada. Accepted on 3rd February 2020
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- 2020
15. Online PMU-Based Wide-Area Damping Control for Multiple Inter-Area Modes
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Ilias Zenelis, Innocent Kamwa, and Xiaozhe Wang
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0209 industrial biotechnology ,General Computer Science ,Computer science ,020209 energy ,Control (management) ,System identification ,02 engineering and technology ,Systems and Control (eess.SY) ,Phasor measurement unit ,Electrical Engineering and Systems Science - Systems and Control ,Noise ,Electric power system ,020901 industrial engineering & automation ,Test case ,Modal ,Control theory ,0202 electrical engineering, electronic engineering, information engineering ,FOS: Electrical engineering, electronic engineering, information engineering ,Network model - Abstract
This paper presents a new phasor measurement unit (PMU)-based wide-area damping control (WADC) method to suppress the critical inter-area modes of large-scale power systems. Modal participation factors, estimated by a practically model-free system identification approach, are used to select the most suitable synchronous generators for control through the proposed WADC algorithm. It is shown that multiple inter-area modes can be sufficiently damped by the proposed approach without affecting the rest of the modes, while only a few machines are needed to perform the control. The proposed technique is applied to the IEEE 68-bus and the IEEE 145-bus systems, including the test cases with PMU measurement noise and with missing PMUs. The simulation results clearly demonstrate the good adaptivity of the control strategy subjected to network model changes, its effective damping performance comparing to power system stabilizers (PSSs), and its great potential for near real-time implementation., Comment: Copyright 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
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- 2020
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16. An Approach to Constructing Analytical Energy Function for Synchronous Generator Models With Subtransient Dynamics
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Dmitry Rimorov, Innocent Kamwa, Xiaozhe Wang, and Geza Joos
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Computer science ,020209 energy ,Energy Engineering and Power Technology ,02 engineering and technology ,Permanent magnet synchronous generator ,Function (mathematics) ,Potential energy ,Stability (probability) ,Electric power system ,Control theory ,0202 electrical engineering, electronic engineering, information engineering ,Benchmark (computing) ,Transient (oscillation) ,Electrical and Electronic Engineering ,Energy (signal processing) - Abstract
Direct methods have been a promising development for decades, receiving, however, less attention recently. One of the reasons is the limited capacity to include more realistic models of the power systems equipment. This paper derives a structure-preserving analytical energy function for a sixth-order synchronous generator model with subtransient dynamics included. The procedure used to construct the energy function is demonstrated to be applicable to simple governor models as well. The energy function is used to assess critical clearing times for multiple contingencies via a potential energy boundary surface method in the IEEE 10-generator 39-bus benchmark system. Some comparative analysis with transient fourth-order models is performed. The results are validated against simulations using a commercial transient stability package.
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- 2018
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17. Wide-Area Damping Control for Interarea Oscillations in Power Grids Based on PMU Measurements
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Ilias Zenelis and Xiaozhe Wang
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Control and Optimization ,Computer science ,020209 energy ,Control (management) ,Systems and Control (eess.SY) ,02 engineering and technology ,Electrical Engineering and Systems Science - Systems and Control ,Phasor measurement unit ,Stability (probability) ,Power (physics) ,Electric power system ,Wide area ,Computer Science::Systems and Control ,Control and Systems Engineering ,Control theory ,FOS: Electrical engineering, electronic engineering, information engineering ,0202 electrical engineering, electronic engineering, information engineering ,Control methods - Abstract
In this letter, a phasor measurement unit (PMU)-based wide-area damping control method is proposed to damp the interarea oscillations that threaten the modern power system stability and security. Utilizing the synchronized PMU data, the proposed almost model-free approach can achieve an effective damping for the selected modes using a minimum number of synchronous generators. Simulations are performed to show the validity of the proposed wide-area damping control scheme.
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- 2018
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18. Integrated optimization on aerodynamics-structure coupling and flight stability of a large airplane in preliminary design
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Xiaozhe Wang, Zhu Liu, Zhiqiang Wan, and Chao Yang
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020301 aerospace & aeronautics ,business.product_category ,Computer science ,Iterative method ,Mechanical Engineering ,Stability (learning theory) ,Aerospace Engineering ,TL1-4050 ,02 engineering and technology ,Aerodynamics ,Aeroelasticity ,01 natural sciences ,010305 fluids & plasmas ,Airplane ,0203 mechanical engineering ,Inviscid flow ,Control theory ,0103 physical sciences ,Genetic algorithm ,Design process ,business ,Motor vehicles. Aeronautics. Astronautics - Abstract
The preliminary phase is significant during the whole design process of a large airplane because of its enormous potential in enhancing the overall performance. However, classical sequential designs can hardly adapt to modern airplanes, due to their repeated iterations, long periods, and massive computational burdens. Multidisciplinary analysis and optimization demonstrates the capability to tackle such complex design issues. In this paper, an integrated optimization method for the preliminary design of a large airplane is proposed, accounting for aerodynamics, structure, and stability. Aeroelastic responses are computed by a rapid three-dimensional flight load analysis method combining the high-order panel method and the structural elasticity correction. The flow field is determined by the viscous/inviscid iteration method, and the cruise stability is evaluated by the linear small-disturbance theory. Parametric optimization is carried out using genetic algorithm to seek the minimal weight of a simplified plate-beam wing structure in the cruise trim condition subject to aeroelastic, aerodynamic, and stability constraints, and the optimal wing geometry shape, front/rear spar positions, and structural sizes are obtained simultaneously. To reduce the computational burden of the static aeroelasticity analysis in the optimization process, the Kriging method is employed to predict aerodynamic influence coefficient matrices of different aerodynamic shapes. The multidisciplinary analyses guarantee computational accuracy and efficiency, and the integrated optimization considers the coupling effect sufficiently between different disciplines to improve the overall performance, avoiding the limitations of sequential approaches utilized currently. Keywords: Aeroelasticity, Integrated optimization, Multidisciplinary analysis, Large airplane, Preliminary design
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- 2018
19. A Framework for Dynamic Stability Analysis of Power Systems With Volatile Wind Power
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Hsiao-Dong Chiang, Tao Wang, Jianhui Wang, Hui Liu, and Xiaozhe Wang
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Mathematical optimization ,Wind power ,business.industry ,Computer science ,020209 energy ,Systems and Control (eess.SY) ,02 engineering and technology ,Stability (probability) ,Wind speed ,Power (physics) ,Stochastic differential equation ,Electric power system ,FOS: Electrical engineering, electronic engineering, information engineering ,0202 electrical engineering, electronic engineering, information engineering ,Trajectory ,Computer Science - Systems and Control ,Probability distribution ,Electrical and Electronic Engineering ,business - Abstract
We propose a framework employing stochastic differential equations to facilitate the long-term stability analysis of power grids with intermittent wind power generations. This framework takes into account the discrete dynamics which play a critical role in the long-term stability analysis, incorporates the model of wind speed with different probability distributions, and also develops an approximation methodology (by a deterministic hybrid model) for the stochastic hybrid model to reduce the computational burden brought about by the uncertainty of wind power. The theoretical and numerical studies show that a deterministic hybrid model can provide an accurate trajectory approximation and stability assessments for the stochastic hybrid model under mild conditions. In addition, we discuss the critical cases that the deterministic hybrid model fails and discover that these cases are caused by a violation of the proposed sufficient conditions. Such discussion complements the proposed framework and methodology and also reaffirms the importance of the stochastic hybrid model when the system operates close to its stability limit., The paper has been accepted by IEEE Journal on Emerging and Selected Topics in Circuits and Systems
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- 2017
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20. A Hybrid Quasi Steady-State Model for Long-Term Stability Analysis of Electric Power Networks: Model Development and Theoretical Basis
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Xiaozhe Wang and Hsiao-Dong Chiang
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Control and Optimization ,Basis (linear algebra) ,Computer Networks and Communications ,020209 energy ,Stability (learning theory) ,Steady State theory ,02 engineering and technology ,Term (time) ,Control and Systems Engineering ,Control theory ,Signal Processing ,0202 electrical engineering, electronic engineering, information engineering ,Decomposition (computer science) ,Electric power ,Stability Model ,Numerical stability ,Mathematics - Abstract
The quasi steady-state (QSS) model based on time-scale decomposition was developed to reduce the computational burden for long-term stability analysis. However, it was shown that the QSS model may not provide accurate stability assessments for the complete dynamic model in long-term stability analysis. In this paper, a hybrid QSS model, which serves as a remedy to the QSS model, is proposed. The proposed model can provide accurate approximations for the long-term stability model with much less computational time. The hybrid QSS model proves to be capable of consistently providing accurate approximations for the long-term stability model. In addition, numerical algorithms for the hybrid QSS model are elaborated for practical implementation. Numerical examples show that the hybrid QSS model can quickly screen out stable contingencies and accurately capture unstable contingencies for the long-term stability model in cases where the QSS model fails.
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- 2017
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21. Integrated aerodynamics/structure/stability optimization of large aircraft in conceptual design
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Xiaozhe Wang, Chao Yang, and Zhiqiang Wan
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Structure (mathematical logic) ,020301 aerospace & aeronautics ,0209 industrial biotechnology ,Engineering ,business.industry ,Mechanical Engineering ,Multidisciplinary design optimization ,Stability (learning theory) ,Aerospace Engineering ,Control engineering ,02 engineering and technology ,Aerodynamics ,Aeroelasticity ,020901 industrial engineering & automation ,0203 mechanical engineering ,Conceptual design ,Stiffness design ,business - Abstract
The multidisciplinary design optimization is suitable for modern large aircraft, and it has the potential in conceptual phase of aircraft design especially. An integrated optimization method considering the disciplines of aerodynamics, structure and stability for large aircraft design in conceptual phase is presented. The objective is the minimum stiffness of a beam-frame wing structure subject to aeroelasticity, aerodynamics, and stability constraints. The aeroelastic responses are computed by commercial software MSC. Nastran, and the cruise stability is evaluated by the linear small-disturbance equations. A viscous-inviscid iteration method, which is composed of a computational fluid dynamics tool solving the Euler equations and a viscous correction method, is used for computing the flow over the model. The method ensures effective and rapid computation. In this paper, a complete aircraft model is optimized, and all the responses are computed in the trim condition with a fixed maximum takeoff weight. Genetic algorithm is utilized for global optimizations, and the optimal jig shape, the elastic axis positions and the stiffness distribution can be attained adequately. The results show that the method has a value of application in engineering optimizations. For the satisfaction of the total drag and stability constraints, the structure weight usually needs a price to pay. The integrated optimization captures the tradeoff between aerodynamics, structure and stability, and the repeated design can be avoided.
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- 2017
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22. The Effect of the Uncertainty of Load and Renewable Generation on the Dynamic Voltage Stability Margin
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Georgia Pierrou and Xiaozhe Wang
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Signal Processing (eess.SP) ,0209 industrial biotechnology ,Computer science ,business.industry ,020209 energy ,Load margin ,Monte Carlo method ,Systems and Control (eess.SY) ,02 engineering and technology ,Electrical Engineering and Systems Science - Systems and Control ,7. Clean energy ,Renewable energy ,Stochastic differential equation ,Voltage stability ,Electric power system ,020901 industrial engineering & automation ,13. Climate action ,Margin (machine learning) ,Control theory ,FOS: Electrical engineering, electronic engineering, information engineering ,0202 electrical engineering, electronic engineering, information engineering ,Renewable generation ,Electrical Engineering and Systems Science - Signal Processing ,business - Abstract
In this paper, the impact of stochastic load and renewable generation uncertainty on the dynamic voltage stability margin is studied. Stochastic trajectories describing the uncertainty of load, wind and solar generation have been incorporated in the power system model as a set of Stochastic Differential-Algebraic Equations (SDAEs). A systematic study of Monte Carlo dynamic simulations on the IEEE 39-Bus system has been conducted to compute the stochastic load margin with all dynamic components active. Numerical results show that the uncertainty of both demand and generation may lead to a decrease on the size of the dynamic voltage stability margin, yet the variability of renewable generators may play a more significant role. Given that the integration of renewable energy will continue growing, it is of paramount importance to apply stochastic and dynamic approaches in the voltage stability study., Comment: Accepted in 2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)
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- 2019
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23. Metaheuristic Approaches to Solve a Complex Aircraft Performance Optimization Problem
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Dianzi Liu, Xiaozhe Wang, and Guirong Dong
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Mathematical optimization ,Optimization problem ,Computer science ,0211 other engineering and technologies ,Genetic programming ,02 engineering and technology ,evolutionary design ,lcsh:Technology ,lcsh:Chemistry ,Conceptual design ,Genetic algorithm ,0202 electrical engineering, electronic engineering, information engineering ,genetic algorithm ,General Materials Science ,Instrumentation ,Metaheuristic ,lcsh:QH301-705.5 ,021106 design practice & management ,Fluid Flow and Transfer Processes ,metamodel ,lcsh:T ,Process Chemistry and Technology ,Multidisciplinary design optimization ,General Engineering ,lcsh:QC1-999 ,Computer Science Applications ,Metamodeling ,optimal Latin hypercube ,Latin hypercube sampling ,lcsh:Biology (General) ,lcsh:QD1-999 ,lcsh:TA1-2040 ,020201 artificial intelligence & image processing ,genetic programming ,lcsh:Engineering (General). Civil engineering (General) ,lcsh:Physics ,multidisciplinary analysis and optimization - Abstract
The increasing demands for travelling comfort and reduction of carbon dioxide emissions have been considered substantially in the stage of conceptual aircraft design. However, the design of a modern aircraft is a multidisciplinary process, which requires the coordination of information from several specific disciplines, such as structures, aerodynamics, control, etc. To address this problem with adequate accuracy, the multidisciplinary analysis and optimization (MAO) method is usually applied as a systematic and robust approach to solve such complex design issues arising from industries. Since MAO method is tedious and computationally expensive, genetic programming (GP)-based metamodeling techniques incorporating MAO are proposed as an effective approach to minimize the wing stiffness of a large aircraft subject to aerodynamic, aeroelastic and stability constraints in the conceptual design phase. Based on the linear small-disturbance theory, the state-space equation is employed for stability analysis. In the process of multidisciplinary analysis, aeroelastic response simulations are performed using Nastran. To construct metamodels representing the responses of the interests with high accuracy as well as less computational burden, optimal Latin hypercube design of experiments (DoE) is applied to determine the optimized distribution of sampling points. Following that, parametric optimization is carried out on metamodels to obtain the optimal wing geometry shape, elastic axis positions and stiffness distribution, and then the solution is verified by finite element simulations. Finally, the superiority of the GP-based metamodel technique over genetic algorithm is demonstrated by multidisciplinary design optimization of a representative beam-frame wing structure in terms of accuracy and efficiency. The results also show that GP metamodel-based strategy for solving MAO problems can provide valuable insights to tailoring parameters for the effective design of a large aircraft in the conceptual phase.
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- 2019
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24. Analysis of Negative Influence of Harmonic Circulation between Parallel STATCOMs and Suppression Method
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Guoqing Li, Yang Hu, Xiaozhe Wang, Jikai Chen, Peng Wang, Hui Shao, and Jiangchao Qin
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Physics ,Correctness ,020209 energy ,020208 electrical & electronic engineering ,02 engineering and technology ,Instability ,Resonance (particle physics) ,Transfer function ,Circulation (fluid dynamics) ,Control theory ,0202 electrical engineering, electronic engineering, information engineering ,Harmonic ,Output impedance ,Virtual impedance - Abstract
In this paper, the cascaded H-bridge STATCOM parallel system is taken as the research object to analyze the instability of STATCOM system caused by the interaction between parallel STATCOMs in wind farm afflux station. Firstly, the inherent relation of harmonic circulation and low-frequency disturbance will be revealed by CPS-PWM theory. Then, the output impedance and transfer function of STATCOM give an insight into the interaction between STATCOMs and low-frequency resonance, and the virtual impedance method is proposed to shape the resonant peak. Finally, the correctness of theoretical analysis is verified by real-time simulation.
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- 2019
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25. An Effective Average Value Model for Modular Multilevel Converters under Startup Process
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Weixing Li, Xiaozhe Wang, Boon-Teck Ooi, Jinling Qi, and Haihao Jiang
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010302 applied physics ,Process modeling ,Differential equation ,business.industry ,020208 electrical & electronic engineering ,02 engineering and technology ,Insulated-gate bipolar transistor ,Modular design ,Converters ,01 natural sciences ,law.invention ,Capacitor ,law ,Control theory ,Ordinary differential equation ,0103 physical sciences ,0202 electrical engineering, electronic engineering, information engineering ,Process control ,business - Abstract
The detailed physics model of the modular multilevel converters (MMCs) consumes excessive computational resources because of massive submodules (SMs). To deal with this problem, several simplified modeling methods have been proposed. However, the startup process modeling techniques attract little attention. In this paper, two common startup processes of MMC are analyzed, including the ac-side and dc-side pre-charge. Firstly, a charging index is defined to represent the charging state of the arm capacitors. Based on the charging index, the ordinary differential equations of MMC under startup process are derived. Furthermore, an average value model (AVM) of MMC is proposed based on the ordinary differential equations. The proposed model is compared and validated by the IGBT-based MMC model in PSCAD/EMTDC.
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- 2019
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26. Online Measurement-Based Estimation of Dynamic System State Matrix in Ambient Conditions
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Hao Sheng and Xiaozhe Wang
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Signal Processing (eess.SP) ,General Computer Science ,Computer science ,Noise (signal processing) ,020209 energy ,Phasor ,Topology (electrical circuits) ,02 engineering and technology ,Network topology ,Units of measurement ,Matrix (mathematics) ,FOS: Electrical engineering, electronic engineering, information engineering ,0202 electrical engineering, electronic engineering, information engineering ,Electrical Engineering and Systems Science - Signal Processing ,Algorithm ,Independence (probability theory) ,Network model - Abstract
In this paper, a purely measurement-based method is proposed to estimate the dynamic system state matrix by applying the regression theorem of the multivariate Ornstein-Uhlenbeck process. The proposed method employs a recursive algorithm to minimize the required computational effort, making it applicable to the real-time environment. One main advantage of the proposed method is model independence, i.e., it is independent of the network model and the dynamic model of generators. Among various applications of the estimated matrix, detecting and locating unexpected network topology change is illustrated in details. Simulation studies have shown that the proposed measurement-based method can provide an accurate and efficient estimation of the dynamic system state matrix under the occurrence of unexpected topology change. Besides, various implementation conditions are tested to show that the proposed method can provide accurate approximation despite measurement noise, missing PMUs, and the implementation of higher-order generator models with control devices., 11 pages, 13 figures
- Published
- 2019
27. Operation optimization of Household Intelligent Electrical Equipment Based on Time-of-Use Price
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Kejun Qian, Linjun Shi, Xiaozhe Wang, Qihang Yang, Haoqing Zhu, and Shilong Wang
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Consumption (economics) ,Water heating ,Smart grid ,Mains electricity ,Computer science ,020209 energy ,Electrical equipment ,020208 electrical & electronic engineering ,0202 electrical engineering, electronic engineering, information engineering ,02 engineering and technology ,Plan (drawing) ,Time of use ,Reliability engineering - Abstract
In the future, household electricity consumption is used as part of the smart grid. It is of great significance to study the optimal operation of household intelligent electrical equipment. Firstly, the mathematical model of typical household intelligent electrical equipment in the future is established, and then based on the time-of-use electricity price, an optimized operation model of intelligent electrical equipment in the future home with the aim of economic and user comfort is proposed, which is convenient for users to formulate a power consumption plan that meets their own needs. Finally, taking a typical home user as an example, the genetic algorithm is used to optimize the operation of the home intelligent electrical equipment by establishing a typical daily simulation scenario. The simulation results show the effectiveness of the established optimization model.
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- 2019
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28. Investigating the Impacts of Stochastic Load Fluctuation on Dynamic Voltage Stability Margin using Bifurcation Theory
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Georgia Pierrou and Xiaozhe Wang
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Signal Processing (eess.SP) ,Stochastic process ,020209 energy ,020208 electrical & electronic engineering ,Monte Carlo method ,02 engineering and technology ,Power (physics) ,Electric power system ,Bifurcation theory ,Margin (machine learning) ,Control theory ,FOS: Electrical engineering, electronic engineering, information engineering ,0202 electrical engineering, electronic engineering, information engineering ,Electrical Engineering and Systems Science - Signal Processing ,Bifurcation ,Numerical stability ,Mathematics - Abstract
This paper studies the impacts of stochastic load fluctuations, namely the fluctuation intensity and the changing speed of load power, on the size of the voltage stability margin. To this end, Stochastic Differential-Algebraic Equations (SDAEs) are used to model the stochastic load variation; bifurcation analysis is carried out to explain the influence of stochasticity. Numerical study and Monte Carlo simulations on the IEEE 14-bus system demonstrate that a larger fluctuation intensity or a slower load power changing speed may lead to a smaller voltage stability margin. Particularly, this work may represent the first attempt to reveal the influence of the time evolution property of the driving parameters on the voltage stability margin in power systems.
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- 2019
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29. Analytical Study of the Impacts of Stochastic Load Fluctuation on the Dynamic Voltage Stability Margin Using Bifurcation Theory
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Xiaozhe Wang and Georgia Pierrou
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Stochastic process ,020209 energy ,020208 electrical & electronic engineering ,Monte Carlo method ,02 engineering and technology ,Systems and Control (eess.SY) ,Electrical Engineering and Systems Science - Systems and Control ,Power (physics) ,Electric power system ,Bifurcation theory ,13. Climate action ,Margin (machine learning) ,Control theory ,0202 electrical engineering, electronic engineering, information engineering ,FOS: Electrical engineering, electronic engineering, information engineering ,Electrical and Electronic Engineering ,Intensity (heat transfer) ,Mathematics ,Numerical stability - Abstract
This paper studies the impacts of stochastic load fluctuations, namely the fluctuation intensity and the load power variation speed, on power system dynamic voltage stability. Additionally, the trade-off relationship between the two parameters is revealed, which provides important insights regarding the potential of using energy storage to maintain voltage stability under high uncertainty. To this end, Stochastic Differential-Algebraic Equations (SDAEs) are used to model the stochastic load variation; bifurcation analysis is carried out to explain the influence of stochasticity. Numerical study and Monte Carlo simulations on the IEEE 14-bus system demonstrate that a larger fluctuation intensity or a slower load power variation speed may lead to a smaller voltage stability margin. To the best of authors' knowledge, this work uncovers the impacts of the time evolution property of the driving parameters, i.e., the load power variation speed and its trade off effect with the fluctuation intensity on the size of the dynamic voltage stability margin., Comment: 10 pages, Accept by IEEE Transactions on Circuits and Systems-I: Regular Papers on September 17, 2019
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- 2019
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30. Probabilistic Power Flow Calculation using Non-intrusive Low-rank Approximation Method
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Hao Sheng and Xiaozhe Wang
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Signal Processing (eess.SP) ,Mathematical optimization ,Polynomial chaos ,Computer science ,020209 energy ,Monte Carlo method ,Probabilistic logic ,Energy Engineering and Power Technology ,Low-rank approximation ,Probability density function ,02 engineering and technology ,AC power ,Polynomial basis ,0202 electrical engineering, electronic engineering, information engineering ,FOS: Electrical engineering, electronic engineering, information engineering ,Electrical and Electronic Engineering ,Electrical Engineering and Systems Science - Signal Processing ,Randomness - Abstract
In this paper, a novel non-intrusive probabilistic power flow (PPF) analysis method based on the low-rank approximation (LRA) is proposed, which can accurately and efficiently estimate the probabilistic characteristics (e.g., mean, variance, probability density function) of the PPF solutions. This method aims at building up a statistically-equivalent surrogate for the PPF solutions through a small number of power flow evaluations. By exploiting the retained tensor-product form of the univariate polynomial basis, a sequential correction-updating scheme is applied, making the total number of unknowns to be linear rather than exponential to the number of random inputs. Consequently, the LRA method is particularly promising for dealing with high-dimensional problems with a large number of random inputs. Numerical studies on the IEEE 39-bus, 118-bus, and 1354-bus systems show that the proposed method can achieve accurate probabilistic characteristics of the PPF solutions with much less computational effort compared to the Monte Carlo simulations. Even compared to the polynomial chaos expansion method, the LRA method can achieve comparable accuracy, while the LRA method is more capable of handling higher-dimensional problems. Moreover, numerical results reveal that the randomness brought about by the renewable energy resources and loads may inevitably affect the feasibility of dispatch/planning schemes., Comment: 12 pages, 5 figures, Accepted by IEEE Transactions on Power Systems on January 27, 2019. arXiv admin note: text overlap with arXiv:1810.08156
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- 2019
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31. A Periodogram-Based Method to Identify Forced and Natural Oscillations Using PMUs
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Qinye Tang and Xiaozhe Wang
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0106 biological sciences ,Oscillation ,Computer science ,020209 energy ,Spectral density ,Natural frequency ,02 engineering and technology ,Systems and Control (eess.SY) ,01 natural sciences ,010601 ecology ,Electric power system ,Control theory ,Limit cycle ,0202 electrical engineering, electronic engineering, information engineering ,FOS: Electrical engineering, electronic engineering, information engineering ,Computer Science - Systems and Control ,Periodogram ,Sustained oscillations ,Forced oscillation - Abstract
Sustained oscillations in power systems are dangerous. There are various mechanisms, for instance, limit cycle and forced oscillation, that may lead to sustained oscillations, which nevertheless are hard to differentiate. In this paper, a novel periodogram-based method to distinguish different oscillation mechanism is proposed, which can quantitatively extract essential signatures of different mechanisms from power spectral density. Numerical study shows that the proposed method can accurately distinguish different oscillation mechanisms even when the forced oscillation frequency is close to the natural frequency., Comment: IEEE PES General Meeting 2019 accepted
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- 2019
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32. Data-Driven Diagnostics of Mechanism<?Pub _newline ?>and Source of Sustained Oscillations
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Xiaozhe Wang and Konstantin Turitsyn
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Oscillation ,Mechanism (biology) ,Noise (signal processing) ,Computer science ,020209 energy ,Phasor ,Energy Engineering and Power Technology ,02 engineering and technology ,Data-driven ,Electric power system ,Units of measurement ,Control theory ,0202 electrical engineering, electronic engineering, information engineering ,Electrical and Electronic Engineering ,Bifurcation - Abstract
Sustained oscillations observed in power systems can damage equipment, degrade the power quality and increase the risks of cascading blackouts. There are several mechanisms that can give rise to oscillations, each requiring different countermeasure to suppress or eliminate the oscillation. This work develops mathematical framework for analysis of sustained oscillations and identifies statistical signatures of each mechanism, based on which a novel oscillation diagnosis method is developed via real-time processing of phasor measurement units (PMUs) data. Case studies show that the proposed method can accurately identify the exact mechanism for sustained oscillation, and meanwhile provide insightful information to locate the oscillation sources.
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- 2016
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33. An improved coordination method of multi-terminal MMC-HVDC system suitable for wind farm clusters integration
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Xiaozhe Wang, Guoqing Li, Hao Sheng, Lin Li, Chu Sun, Jikai Chen, and Dong Feifei
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Wind power ,Computer science ,business.industry ,020209 energy ,020208 electrical & electronic engineering ,Energy Engineering and Power Technology ,02 engineering and technology ,Transmission system ,Control theory ,Control system ,0202 electrical engineering, electronic engineering, information engineering ,Voltage droop ,High-voltage direct current ,Electrical and Electronic Engineering ,business ,Lead–lag compensator ,Inner loop - Abstract
With the continuous expansion of wind farm clusters, the multi-terminal modular multilevel converter based high voltage direct current (MMC-HVDC) transmission has been employed for wind power delivery. To improve the control flexibility, dynamic voltage adjustment speed and rationality of power allocation, various coordination control methods have been recently investigated in multi-terminal MMC-HVDC transmission system. An attempt is made in this paper to contribute to the optimization of coordination control in the multi-terminal MMC-HVDC system connected to wind farms. Based on the analysis of DC voltage, power deviation and droop coefficient, an improved droop control strategy with adjustable coefficients is first proposed and thereby applied to multi-terminal MMC-HVDC transmission system with wind farm clusters. Arguably, the droop coefficient correction should be an effective method for optimizing power allocation and reducing DC voltage deviation between the receiving converters. In addition, a lag compensator is introduced to improve the response speed of the inner loop controller when the improved droop control is adopted. Furthermore, the influence of droop coefficients on the stability of the control system is discussed, and the dynamic response of the improved control system is also analyzed under the different droop and time coefficients, which can provide guidelines for the control optimization of multi-terminal MMC-HVDC system. Finally, a model of a five-terminal MMC-HVDC transmission system is built based on the RT-LAB simulator, and the simulation results show that the proposed method can not only optimize the voltage control and power allocation, but also improve the system response speed.
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- 2020
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34. Synchrophasor-Based State Estimation for Voltage Stability Monitoring in Power Systems
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Dmitry Rimorov, Xinyun Lu, Geza Joos, Xiaozhe Wang, and Hao Sheng
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Electric power system ,Situation awareness ,Warning system ,Computer science ,020209 energy ,Continuous monitoring ,0202 electrical engineering, electronic engineering, information engineering ,02 engineering and technology ,Time series ,Stability (probability) ,Power (physics) ,Voltage ,Reliability engineering - Abstract
Power distribution systems require continuous monitoring as the integration of renewable energy resources is increasing and the load demand is growing. The implementation of synchrophasors in distribution systems enhances the situational awareness of the system and provides a unique opportunity for developing new monitoring algorithms. This paper proposes a voltage monitoring algorithm based on the synchrophasor-based linear state estimation method. Particularly, the voltage monitoring algorithm combines a set of early warning indicators and the BDS independence test which can detect the voltage instability in a timely manner while avoiding false alarms when the system is still away from the stability boundary. Numerical study has been conducted in the Quebec test feeder to show the effectiveness of the method.
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- 2018
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35. Applying Polynomial Chaos Expansion to Assess Probabilistic Available Delivery Capability for Distribution Networks with Renewables
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Hao Sheng and Xiaozhe Wang
- Subjects
Signal Processing (eess.SP) ,Mathematical optimization ,Polynomial chaos ,Computer science ,business.industry ,020209 energy ,Monte Carlo method ,Probabilistic logic ,Energy Engineering and Power Technology ,02 engineering and technology ,7. Clean energy ,Renewable energy ,0202 electrical engineering, electronic engineering, information engineering ,FOS: Electrical engineering, electronic engineering, information engineering ,Probability distribution ,Electrical Engineering and Systems Science - Signal Processing ,Electrical and Electronic Engineering ,Marginal distribution ,business ,Random variable ,Randomness - Abstract
Considering the increasing penetration of renewable energy sources and electrical vehicles in utility distribution feeders, it is imperative to study the impacts of the resulting increasing uncertainty on the delivery capability of a distribution network. In this paper, probabilistic available delivery capability (ADC) is formulated for a general distribution network integrating various RES and load variations. To reduce the computational efforts by using conventional Monte Carlo simulations, we develop and employ a computationally efficient method to assess the probabilistic ADC, which combines the up-to-date sparse polynomial chaos expansion (PCE) and the continuation method. Particularly, the proposed method is able to handle a large number of correlated random inputs with different marginal distributions. Numerical examples in the IEEE 13 and IEEE 123 node test feeders are presented, showing that the proposed method can achieve accuracy and efficiency simultaneously. Numerical results also demonstrate that the randomness brought about by the RES and loads indeed leads to a reduction in the delivery capability of a distribution network., Comment: 10 pages, 4 figures, journal paper accepted by IEEE Transactions on Power Systems
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- 2018
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36. Estimating Participation Factors and Mode Shapes for Electromechanical Oscillations in Ambient Conditions
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Ilias Zenelis and Xiaozhe Wang
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Signal Processing (eess.SP) ,Computer science ,Oscillation ,020209 energy ,02 engineering and technology ,Identification (information) ,Matrix (mathematics) ,Modal ,Normal mode ,Control theory ,0202 electrical engineering, electronic engineering, information engineering ,FOS: Electrical engineering, electronic engineering, information engineering ,Electrical Engineering and Systems Science - Signal Processing ,Eigenvalues and eigenvectors - Abstract
In this paper, a new technique is applied to conduct mode identification using ambient measurement data. The proposed hybrid measurement- and model-based method can accurately estimate the system state matrix in ambient conditions, the eigenvalues and eigenvectors of which readily provide all the modal knowledge including frequencies, damping ratios, mode shapes, and more importantly, participation factors. Numerical simulations show that the proposed technique is able to provide accurate estimation of modal knowledge for all modes. In addition, the discrepancy between the participation factor and the mode shape is shown through a numerical example, demonstrating that using the mode shape may not effectively pinpoint the best location for damping control. Therefore, the proposed technique capable of estimating participation factors may greatly facilitate designing damping controls.
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- 2018
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37. Probabilistic Available Delivery Capability Assessment of General Distribution Network with Renewables
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Xiaozhe Wang and Hao Sheng
- Subjects
Signal Processing (eess.SP) ,Mathematical optimization ,Polynomial chaos ,General distribution ,business.industry ,Computer science ,020209 energy ,Node (networking) ,Probabilistic logic ,02 engineering and technology ,Continuation method ,Renewable energy ,CHAOS (operating system) ,FOS: Electrical engineering, electronic engineering, information engineering ,0202 electrical engineering, electronic engineering, information engineering ,Probabilistic analysis of algorithms ,Electrical Engineering and Systems Science - Signal Processing ,business - Abstract
Rapid increase of renewable energy sources and electric vehicles in utility distribution feeders introduces more and more uncertainties. To investigate how such uncertainties may affect the available delivery capability (ADC) of the distribution network, it is imperative to employ a probabilistic analysis framework. In this paper, a formulation for probabilistic ADC incorporating renewable generators and load variations is proposed; a computationally efficient method to solve the probabilistic ADC is presented, which combines the up-to-date sparse polynomial chaos expansion (PCE) and the continuation method. A numerical example in the IEEE 13 node test feeder is given to demonstrate the accuracy and efficiency of the proposed method., 6 pages, 3 figures, Conference paper, Published in the IEEE Canada Electrical Power and Energy Conference 2017
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- 2017
38. PMU-Based Estimation of Dynamic State Jacobian Matrix and Dynamic System State Matrix in Ambient Conditions
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Konstantin Turitsyn, Xiaozhe Wang, and Janusz Bialek
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State-transition matrix ,020209 energy ,Energy Engineering and Power Technology ,02 engineering and technology ,State (functional analysis) ,Systems and Control (eess.SY) ,Network topology ,Stability (probability) ,symbols.namesake ,Matrix (mathematics) ,Control theory ,Jacobian matrix and determinant ,0202 electrical engineering, electronic engineering, information engineering ,symbols ,FOS: Electrical engineering, electronic engineering, information engineering ,Computer Science - Systems and Control ,Electrical and Electronic Engineering ,Mathematics ,Network model - Abstract
In this paper, a hybrid measurement- and model-based method is proposed which can estimate the dynamic state Jacobian matrix and the dynamic system state matrix in near real-time utilizing statistical properties extracted from PMU measurements. The proposed method can be used to detect and identify network topology changes that have not been reflected in an assumed network model. Additionally, an application of the estimated system state matrix in online dynamic stability monitoring is presented., To appear in IEEE Transactions on Power Systems
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- 2017
39. Estimating Dynamic Load Parameters from Ambient PMU Measurements
- Author
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Xiaozhe Wang
- Subjects
Electric power system ,Disturbance (geology) ,Computer science ,Control theory ,Robustness (computer science) ,020209 energy ,0202 electrical engineering, electronic engineering, information engineering ,FOS: Electrical engineering, electronic engineering, information engineering ,Computer Science - Systems and Control ,02 engineering and technology ,Numerical models ,Systems and Control (eess.SY) ,Dynamic load testing - Abstract
In this paper, a novel method to estimate dynamic load parameters via ambient PMU measurements is proposed. Unlike conventional parameter identification methods, the proposed algorithm does not require the existence of large disturbance to power systems, and is able to provide up-to-date dynamic load parameters consistently and continuously. The accuracy and robustness of the method are demonstrated through numerical simulations., Comment: The paper has been accepted by IEEE PES general meeting 2017
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- 2017
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40. PMU-Based Estimation of Dynamic State Jacobian Matrix
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Xiaozhe Wang and Konstantin Turitsyn
- Subjects
Computer science ,020209 energy ,MathematicsofComputing_NUMERICALANALYSIS ,Systems and Control (eess.SY) ,02 engineering and technology ,Variation (game tree) ,State (functional analysis) ,Network topology ,symbols.namesake ,Jacobian matrix and determinant ,FOS: Electrical engineering, electronic engineering, information engineering ,0202 electrical engineering, electronic engineering, information engineering ,symbols ,Computer Science - Systems and Control ,Algorithm ,Network model - Abstract
In this paper, a hybrid measurement and model-based method is proposed which can estimate the dynamic state Jacobian matrix in near real-time. The proposed method is computationally efficient and robust to the variation of network topology. Since the estimated Jacobian matrix carries significant information on system dynamics and states, it can be utilized in various applications. In particular, two application of the estimated Jacobian matrix in online oscillation analysis, stability monitoring and control are illustrated with numerical examples. In addition, a side-product of the proposed method can facilitate model validation by approximating the damping of generators., submitted to IEEE Transactions on Power Systems
- Published
- 2015
41. A hybrid solution for extracting structured medical information from unstructured data in medical records via a double-reading/entry system
- Author
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Liping Li, Jiajia Hu, Ligang Luo, Boulin Hou, Lue Ping Zhao, Tianze Zhang, and Xiaozhe Wang
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Adult ,Male ,Information privacy ,China ,Lung Neoplasms ,020205 medical informatics ,Electronic data capture ,Computer science ,Electronic medical record ,Big data ,Structured data and unstructured data ,Information Storage and Retrieval ,Cloud computing ,Health Informatics ,02 engineering and technology ,Clinical decision support system ,computer.software_genre ,Health informatics ,Clinical research ,03 medical and health sciences ,0302 clinical medicine ,Double data entry ,Health service research ,0202 electrical engineering, electronic engineering, information engineering ,Big medical data ,Electronic Health Records ,Humans ,030212 general & internal medicine ,business.industry ,Health Policy ,eMix ,Unstructured data ,Middle Aged ,Decision Support Systems, Clinical ,Computer Science Applications ,Technical Advance ,Cloud-based system ,Female ,Data mining ,Health Services Research ,business ,computer - Abstract
Background Healthcare providers generate a huge amount of biomedical data stored in either legacy system (paper-based) format or electronic medical records (EMR) around the world, which are collectively referred to as big biomedical data (BBD). To realize the promise of BBD for clinical use and research, it is an essential step to extract key data elements from unstructured medical records into patient-centered electronic health records with computable data elements. Our objective is to introduce a novel solution, known as a double-reading/entry system (DRESS), for extracting clinical data from unstructured medical records (MR) and creating a semi-structured electronic health record database, as well as to demonstrate its reproducibility empirically. Methods Utilizing the modern cloud-based technologies, we have developed a comprehensive system that includes multiple subsystems, from capturing MRs in clinics, to securely transferring MRs, storing and managing cloud-based MRs, to facilitating both machine learning and manual reading, and to performing iterative quality control before committing the semi-structured data into the desired database. To evaluate the reproducibility of extracted medical data elements by DRESS, we conduct a blinded reproducibility study, with 100 MRs from patients who have undergone surgical treatment of lung cancer in China. The study uses Kappa statistic to measure concordance of discrete variables, and uses correlation coefficient to measure reproducibility of continuous variables. Results Using the DRESS, we have demonstrated the feasibility of extracting clinical data from unstructured MRs to create semi-structured and patient-centered electronic health record database. The reproducibility study with 100 patient’s MRs has shown an overall high reproducibility of 98 %, and varies across six modules (pathology, Radio/chemo therapy, clinical examination, surgery information, medical image and general patient information). Conclusions DRESS uses a double-reading, double-entry, and an independent adjudication, to manually curate structured data elements from unstructured clinical data. Further, through distributed computing strategies, DRESS protects data privacy by dividing MR data into de-identified modules. Finally, through internet-based computing cloud, DRESS enables many data specialists to work in a virtual environment to achieve the necessary scale of processing thousands MRs within days. This hybrid system represents probably a workable solution to solve the big medical data challenge. Electronic supplementary material The online version of this article (doi:10.1186/s12911-016-0357-5) contains supplementary material, which is available to authorized users.
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