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Microgrids incorporate an increasing number of distributed energy resources (DERs), which induce variability as well as fast dispatch capabilities in power systems. This paper proposes a two-layer real-time scheduling model for microgrids, based on approximate future cost function (AFCF), where the future cost represents the opportunity cost for the operation in the following periods. At the upper layer, the look-ahead rolling scheduling is adopted to optimize microgrid operations, and the future cost function (FCF) in deterministic and stochastic scenarios is approximated by a piecewise linear function. At the lower layer, a real-time parameter updating strategy based on real-time data is proposed. In this case, real-time scheduling readjusts the look-ahead schedule using the immediate cost in the current period and the future cost calculated by the updated AFCF. The proposed two-layer real-time scheduling model uses the offline optimization, in which most computation tasks are completed at the upper layer, and real-time optimization, in which the time-consuming problem is avoided at the lower layer. The effectiveness of the proposed two-layer real-time scheduling model of microgrids is validated using a grid-connected microgrid system. For comparison, other existing real-time scheduling methods are also implemented in the same microgrid system.
Mohammad Shahidehpour; Chunyang Liu; Hengxu Zhang; Quan Zhou; Tao Ding. A Two-layer Model for Microgrid Real-time Scheduling using Approximate Future Cost Function. IEEE Transactions on Power Systems 2021, PP, 1 -1.
AMA StyleMohammad Shahidehpour, Chunyang Liu, Hengxu Zhang, Quan Zhou, Tao Ding. A Two-layer Model for Microgrid Real-time Scheduling using Approximate Future Cost Function. IEEE Transactions on Power Systems. 2021; PP (99):1-1.
Chicago/Turabian StyleMohammad Shahidehpour; Chunyang Liu; Hengxu Zhang; Quan Zhou; Tao Ding. 2021. "A Two-layer Model for Microgrid Real-time Scheduling using Approximate Future Cost Function." IEEE Transactions on Power Systems PP, no. 99: 1-1.
The renewable portfolio standard has been promoted in parallel with the reform of the electricity market, and the flexibility requirement of the power system has rapidly increased. To promote renewable energy consumption and improve power system flexibility, a bi-level optimal operation model of the electricity market is proposed. A probabilistic model of the flexibility requirement is established, considering the correlation between wind power, photovoltaic power, and load. A bi-level optimization model is established for the multi-markets; the upper and lower models represent the intra-provincial market and inter-provincial market models, respectively. To efficiently solve the model, it is transformed into a mixed-integer linear programming model using the Karush–Kuhn–Tucker condition and Lagrangian duality theory. The economy and flexibility of the model are verified using a provincial power grid as an example.
Jinye Yang; Chunyang Liu; Yuanze Mi; Hengxu Zhang; Vladimir Terzija. Optimization operation model of electricity market considering renewable energy accommodation and flexibility requirement. Global Energy Interconnection 2021, 4, 227 -238.
AMA StyleJinye Yang, Chunyang Liu, Yuanze Mi, Hengxu Zhang, Vladimir Terzija. Optimization operation model of electricity market considering renewable energy accommodation and flexibility requirement. Global Energy Interconnection. 2021; 4 (3):227-238.
Chicago/Turabian StyleJinye Yang; Chunyang Liu; Yuanze Mi; Hengxu Zhang; Vladimir Terzija. 2021. "Optimization operation model of electricity market considering renewable energy accommodation and flexibility requirement." Global Energy Interconnection 4, no. 3: 227-238.
With the development of carbon electricity, achieving a low-carbon economy has become a prevailing and inevitable trend. Improving low-carbon expansion generation planning is critical for carbon emission mitigation and a low- carbon economy. In this paper, a two-layer low-carbon expansion generation planning approach considering the uncertainty of renewable energy at multiple time scales is proposed. First, renewable energy sequences considering the uncertainty in multiple time scales are generated based on the Copula function and the probability distribution of renewable energy. Second, a two-layer generation planning model considering carbon trading and carbon capture technology is established. Specifically, the upper layer model optimizes the investment decision considering the uncertainty at a monthly scale, and the lower layer one optimizes the scheduling considering the peak shaving at an hourly scale and the flexibility at a 15-minute scale. Finally, the results of different influence factors on low-carbon generation expansion planning are compared in a provincial power grid, which demonstrate the effectiveness of the proposed model.
Yuanze Mi; Chunyang Liu; Jinye Yang; Hengxu Zhang; Qiuwei Wu. Low-carbon generation expansion planning considering uncertainty of renewable energy at multi-time scales. Global Energy Interconnection 2021, 4, 261 -272.
AMA StyleYuanze Mi, Chunyang Liu, Jinye Yang, Hengxu Zhang, Qiuwei Wu. Low-carbon generation expansion planning considering uncertainty of renewable energy at multi-time scales. Global Energy Interconnection. 2021; 4 (3):261-272.
Chicago/Turabian StyleYuanze Mi; Chunyang Liu; Jinye Yang; Hengxu Zhang; Qiuwei Wu. 2021. "Low-carbon generation expansion planning considering uncertainty of renewable energy at multi-time scales." Global Energy Interconnection 4, no. 3: 261-272.
Practical application of deep learning based non-intrusive load monitoring (NILM) system requires the deep neural network model to generalize on new unseen data. Existing NILM solutions are not suitable for real-world application due to their poor disaggregation accuracy on new unseen data. In order to address this problem, this paper presents a NILM algorithm that uses data augmentation to generate synthetic data for training deep convolutional neural network models for each target appliance. Proposed data augmentation technique works by combining on and off-durations of a target appliance from various datasets, and forms a unified and comprehensive synthetic aggregate and sub-meter profiles. Apart from proposed algorithm, this paper also proposes an evaluation approach that relies on total predicted energy and ground-truth energy of an appliance to provide detailed insights about total overlapping energy, missing energy and extra energy predicted by the algorithm. Comparison results on our proposed evaluation approach showed that proposed disaggregation algorithm was able to predict energy that was 60% overlapping with ground truth energy and 36% energy was extra. Overall results showed that overlapping energy was 2.5 times more, and extra-predicted energy was 60% less than state-of-the-art algorithms in unseen test cases.
Hasan Rafiq; Xiaohan Shi; Hengxu Zhang; Huimin Li; Manesh Kumar Ochani; Aamer Abbas Shah. Generalizability Improvement of Deep Learning-Based Non-Intrusive Load Monitoring System Using Data Augmentation. IEEE Transactions on Smart Grid 2021, 12, 3265 -3277.
AMA StyleHasan Rafiq, Xiaohan Shi, Hengxu Zhang, Huimin Li, Manesh Kumar Ochani, Aamer Abbas Shah. Generalizability Improvement of Deep Learning-Based Non-Intrusive Load Monitoring System Using Data Augmentation. IEEE Transactions on Smart Grid. 2021; 12 (4):3265-3277.
Chicago/Turabian StyleHasan Rafiq; Xiaohan Shi; Hengxu Zhang; Huimin Li; Manesh Kumar Ochani; Aamer Abbas Shah. 2021. "Generalizability Improvement of Deep Learning-Based Non-Intrusive Load Monitoring System Using Data Augmentation." IEEE Transactions on Smart Grid 12, no. 4: 3265-3277.
Numerical modeling of the high impedance arc fault (HIAF) is essential to supplementing the deficiency of real-world fault cases and extending the fault scenarios. Setting the parameters of the model correctly is the basis to reproduce practical fault waveforms. According to the literature, the parameters of HIAF model are mostly determined manually and the basis is mostly subjective. The existing automatic parameter determination methods are mostly used in the other arc modeling areas (such as DC arcs and circuit break-er arcs), which do not include the power networks and are time-consuming. In this paper, after introducing the unique re-quirements in simulating the nonlinearity of HIAFs, a high-efficiency parameter determination method is proposed for HIAF models. The method is realized by interfacing the optimiz-er programmed in Python with the HIAF model and power net-work established in PSCAD. In this process, a combination of pulse controllers is designed and certain configurations are pro-posed, so that the parameter determination procedure can be significantly simplified. Case studies show that, by combining the high-efficiency method with our previously proposed DIST-C HIAF model, fitting accuracy and efficiency can be guaranteed. The time for parameter determination of HIAF model is within minutes, decreasing hundreds of times
Mingjie Wei; Fang Shi; Hengxu Zhang; Fan Yang; Weijiang Chen. A High-Efficiency Method to Determine Parameters of High Impedance Arc Fault Models. IEEE Transactions on Power Delivery 2021, PP, 1 -1.
AMA StyleMingjie Wei, Fang Shi, Hengxu Zhang, Fan Yang, Weijiang Chen. A High-Efficiency Method to Determine Parameters of High Impedance Arc Fault Models. IEEE Transactions on Power Delivery. 2021; PP (99):1-1.
Chicago/Turabian StyleMingjie Wei; Fang Shi; Hengxu Zhang; Fan Yang; Weijiang Chen. 2021. "A High-Efficiency Method to Determine Parameters of High Impedance Arc Fault Models." IEEE Transactions on Power Delivery PP, no. 99: 1-1.
Eigenvalue Method can analyze the operating features of the system. The trajectory section eigenvalue method combines the model and trajectory, and extends the equilibrium point eigenvalue to the unbalanced point of the cross section at any time on the disturbed trajectory, which well solves the non-linearity and the time-varying issues of the system. Based on the theoretical basis of clarifying the trajectory section eigenvalue (TSE) method, the paper establishes a stability evaluation framework based on the time-varying second-order resonant circuit, which extrates the damping feature and frequency feature information in the eigenvalue sequence of the trajectory section, then compares it with the results of signal processing. The influence mechanism of time-varying factors on system stability is clarified, and the advantages of the trajectory section eigenvalue method in stability evaluation are demonstrated.
Jiacheng Ruan; Hengxu Zhang; Yongji Cao. Stability Assessment Approach Based on Trajectory Section Eigenvalue. E3S Web of Conferences 2021, 256, 02042 .
AMA StyleJiacheng Ruan, Hengxu Zhang, Yongji Cao. Stability Assessment Approach Based on Trajectory Section Eigenvalue. E3S Web of Conferences. 2021; 256 ():02042.
Chicago/Turabian StyleJiacheng Ruan; Hengxu Zhang; Yongji Cao. 2021. "Stability Assessment Approach Based on Trajectory Section Eigenvalue." E3S Web of Conferences 256, no. : 02042.
Non-synchronous renewable energy sources (RESs) have strong volatility and low inertia, which brings about great challenges on the accommodation of RESs and the security and stability of power systems. This paper proposes a bi-level power system dispatch and control architecture based on the grid-friendly virtual power plant (GVPP), so as to accommodate RESs flexibly and securely. The typical dispatch and control system of the power system in China is presented, and the particular challenges stemming from non-synchronous RESs are analyzed. The functional requirements, concept, and fundamental design of the GVPP are provided, which is distinguished from traditional virtual power plants (VPPs) for its active participation in power system stability control. Based on the cloud platform, a bi-level dispatch and control architecture considering two objectives is established. First, in the inner level, the GVPP operates to promote the accommodation of RESs under normal condition. Then, from the perspective of out-level power systems, GVPPs serve as spinning reserves for power support under contingencies. Besides, the key problems to be solved in the development of the GVPP-based architecture are summarized. Although the architecture is proposed for the power system in China, it can be applied to any power systems with similar challenges.
Qingwen Xu; Yongji Cao; Hengxu Zhang; Wen Zhang; Vladimir Terzija. Bi-Level Dispatch and Control Architecture for Power System in China Based on Grid-Friendly Virtual Power Plant. Applied Sciences 2021, 11, 1282 .
AMA StyleQingwen Xu, Yongji Cao, Hengxu Zhang, Wen Zhang, Vladimir Terzija. Bi-Level Dispatch and Control Architecture for Power System in China Based on Grid-Friendly Virtual Power Plant. Applied Sciences. 2021; 11 (3):1282.
Chicago/Turabian StyleQingwen Xu; Yongji Cao; Hengxu Zhang; Wen Zhang; Vladimir Terzija. 2021. "Bi-Level Dispatch and Control Architecture for Power System in China Based on Grid-Friendly Virtual Power Plant." Applied Sciences 11, no. 3: 1282.
Numerical simulation is the key technique for large scale power system analysis. Redistribution of global renewable power via international interconnections requires new simulation tools to study the interconnected systems with different nominal frequencies as a whole. This paper introduces an open source simulation toolkit for electrical power systems (STEPS) which is hosted at Github. Its kernel is coded in C++ with major functions of power flow and electro-mechanical dynamic simulation. Flexible options are provided and configurable to improve power flow solution and dynamic simulation. Common devices and models are supported in STEPS for AC/DC hybrid system studies. Studies of interconnected systems with different nominal frequencies is supported in STEPS for research of international interconnection. Application program interfaces are provided and wrapped with Python to enable high-level interfaces for general applications. STEPS is thread safe and parallel computation is supported in both kernel and script levels to accelerate simulation. It is portable and works on Windows and GNU/Linux platforms. Cases from small to large scale systems are thoroughly tested to validate the toolkit with commercial packages as benchmarks.
Changgang Li; Yue Wu; Hengxu Zhang; Hua Ye; Yutian Liu; Yilu Liu. STEPS: A Portable Dynamic Simulation Toolkit for Electrical Power System Studies. IEEE Transactions on Power Systems 2020, 36, 3216 -3226.
AMA StyleChanggang Li, Yue Wu, Hengxu Zhang, Hua Ye, Yutian Liu, Yilu Liu. STEPS: A Portable Dynamic Simulation Toolkit for Electrical Power System Studies. IEEE Transactions on Power Systems. 2020; 36 (4):3216-3226.
Chicago/Turabian StyleChanggang Li; Yue Wu; Hengxu Zhang; Hua Ye; Yutian Liu; Yilu Liu. 2020. "STEPS: A Portable Dynamic Simulation Toolkit for Electrical Power System Studies." IEEE Transactions on Power Systems 36, no. 4: 3216-3226.
Distribution networks in China and several other countries are predominantly neutral inefficiently grounding systems (NIGSs), and more than 80% of the faults in distribution networks are single-phase-to-ground (SPG) faults. Because of the weak fault current and imperfect monitoring equipment configurations, methods used to determine the faulty line sections with SPG faults in NIGSs are ineffective. The development and application of distribution-level phasor measurement units (PMUs) provide further comprehensive fault information for fault diagnosis in a distribution network. When an SPG fault occurs, the transient energy of the faulted line section tends to be higher than the sum of the transient energies of other line sections. In this regard, transient energy-based fault location algorithms appear to be a promising resolution. In this study, a field test plan was designed and implemented for a 10 kV distribution network. The test results demonstrate the effectiveness of the transient energy-based SPG location method in practical distribution networks.
Wei Xie; Xuewen Wang; Chen Fang; Hengxu Zhang; Fang Shi; Xiaodong Xing; Baicong Sun. Field experiment using transient energy method to locate a single-phase to ground fault. Global Energy Interconnection 2020, 3, 585 -594.
AMA StyleWei Xie, Xuewen Wang, Chen Fang, Hengxu Zhang, Fang Shi, Xiaodong Xing, Baicong Sun. Field experiment using transient energy method to locate a single-phase to ground fault. Global Energy Interconnection. 2020; 3 (6):585-594.
Chicago/Turabian StyleWei Xie; Xuewen Wang; Chen Fang; Hengxu Zhang; Fang Shi; Xiaodong Xing; Baicong Sun. 2020. "Field experiment using transient energy method to locate a single-phase to ground fault." Global Energy Interconnection 3, no. 6: 585-594.
Accompanying the continuous increase in wind power penetration, the power system inertia is reduced, and the system frequency regulation performance deteriorates. Wind turbine generators are required to participate in primary frequency regulation (PFR) to support system frequency. Here, the PFR capability of the widely-used doubly-fed induction generator (DFIG) is evaluated to estimate the participation of the DFIG in system frequency control. The frequency regulation model of the DFIG is established and briefly discussed. The equivalent PFR droop coefficient is then deduced from the model using a small signal increment method to evaluate the DFIG’s PFR capability. Key factors affecting the equivalent droop coefficient are studied, and the droop control is optimized to keep the equivalent droop coefficient in the desired range. The proposed method is verified utilizing a provincial power grid model of China.
Changgang Li; Zhi Hang; Hengxu Zhang; Qi Guo; Yihua Zhu; Vladimir Terzija. Evaluation of DFIGs’ Primary Frequency Regulation Capability for Power Systems with High Penetration of Wind Power. Energies 2020, 13, 6178 .
AMA StyleChanggang Li, Zhi Hang, Hengxu Zhang, Qi Guo, Yihua Zhu, Vladimir Terzija. Evaluation of DFIGs’ Primary Frequency Regulation Capability for Power Systems with High Penetration of Wind Power. Energies. 2020; 13 (23):6178.
Chicago/Turabian StyleChanggang Li; Zhi Hang; Hengxu Zhang; Qi Guo; Yihua Zhu; Vladimir Terzija. 2020. "Evaluation of DFIGs’ Primary Frequency Regulation Capability for Power Systems with High Penetration of Wind Power." Energies 13, no. 23: 6178.
As more and more inverter interfaced distributed generators (IIDGs) such as PV are connected to the distribution network (DN), the existing relay protection system may malfunction due to the impact of the IIDGs. In order to evaluate that impact, the fault analysis of the DN with IIDGs is needed and the fault modelling of IIDG is of great significant for the fault analysis and the protection system validation and improvement. This paper proposes a new fault modelling method of IIDG that could consider the detailed characteristics of the inverter in different situations including the limitation of the modulation. The symmetrical fault model of PQ controlled IIDG is deduced by the proposed method, based on which the symmetrical fault analysis of the DN with IIDGs is carried out. The proposed model depicts IIDG as a voltage-controlled current source or a voltage-controlled voltage source according to whether the modulation is limited, therefore covers the full characteristics of the inverter under different conditions, improving the modelling accuracy. The case study based on the modified IEEE 13 nodes system shows that the fault analysis results obtained from the proposed model are more consistent with electromagnetic transient simulation than that of the state-of-art fault model, verifying its effectiveness.
Xiaohan Shi; Hengxu Zhang; Chuanzhi Wei; Zeyu Li; Shi Chen. Fault Modeling of IIDG Considering Inverter’s Detailed Characteristics. IEEE Access 2020, 8, 183401 -183410.
AMA StyleXiaohan Shi, Hengxu Zhang, Chuanzhi Wei, Zeyu Li, Shi Chen. Fault Modeling of IIDG Considering Inverter’s Detailed Characteristics. IEEE Access. 2020; 8 (99):183401-183410.
Chicago/Turabian StyleXiaohan Shi; Hengxu Zhang; Chuanzhi Wei; Zeyu Li; Shi Chen. 2020. "Fault Modeling of IIDG Considering Inverter’s Detailed Characteristics." IEEE Access 8, no. 99: 183401-183410.
Power system analysis (PSA) is the first comprehensive curriculum for the major of electrical engineering at the undergraduate stage. It helps students obtain an overview of the power system, and systematically learn about fundamental theories. However, the traditional teaching of PSA course excessively focuses on the class lecture, and is combined with hardware-based experiments that are restricted due to concerns of security and cost. Enhancing the PSA course has been attempted at Shandong University, China, since 2016, which combines class lecture, laboratory exercises, and practical activities into the daily teaching. In laboratory exercises, project-based learning (PBL) is carried out by using the hardware experimental equipment and self-developed teaching software, VTPCE, hence to enhance students’ understandings of knowledge, hands-on abilities, and researching skills. Practical activities are organized by visiting the topic-related institutes to establish the relationships between theories and practices. This paper introduces the architecture, the intended learning objects (ILOs), and the detailed arrangement of the reformed PSA course. The assessment procedures for students are also presented, as well as the satisfaction surveys.
Mingjie Wei; Hengxu Zhang; Tianyu Fang. Enhancing the course teaching of power system analysis with virtual simulation platform. The International Journal of Electrical Engineering & Education 2020, 1 .
AMA StyleMingjie Wei, Hengxu Zhang, Tianyu Fang. Enhancing the course teaching of power system analysis with virtual simulation platform. The International Journal of Electrical Engineering & Education. 2020; ():1.
Chicago/Turabian StyleMingjie Wei; Hengxu Zhang; Tianyu Fang. 2020. "Enhancing the course teaching of power system analysis with virtual simulation platform." The International Journal of Electrical Engineering & Education , no. : 1.
Detection of the high impedance fault (HIF) in distribution systems is significant for power utilization safety. However, many HIFs are challenging to be identified due to low currents and diverse characteristics. Particularly, the slight nonlinearity during weak arcing processes, the distortion offset caused by various heat dissipations, and the interference of noises could lead to malfunctions of traditional algorithms. This paper proposes a distortion-based algorithm to improve the reliability of HIF detection. Firstly, the challenges brought by the diversity of HIF characteristics are illustrated with field experiments in a 10kV real-world system. HIFs are classified into five types according to their various distortions. Secondly, an interval slope is defined to describe waveform distortions. The interval slope is extracted by linear least square filtering (LLSF) and Grubbs-criterion-based robust local regression smoothing (Grubbs-RLRS), so that distortions under different fault conditions can be uniformly described. Thirdly, an algorithm is proposed to judge the features presented by the interval slope, and distinguish from non-fault conditions. Finally, the reliability and security of the proposed algorithm are thoroughly analyzed with real-world HIFs and the simulated HIFs in IEEE 34-bus and IEEE 123-bus systems. Improvements of the proposed algorithm are shown by comparing with other algorithms.
Mingjie Wei; Weisheng Liu; Hengxu Zhang; Fang Shi; Weijiang Chen. Distortion-Based Detection of High Impedance Fault in Distribution Systems. IEEE Transactions on Power Delivery 2020, 36, 1603 -1618.
AMA StyleMingjie Wei, Weisheng Liu, Hengxu Zhang, Fang Shi, Weijiang Chen. Distortion-Based Detection of High Impedance Fault in Distribution Systems. IEEE Transactions on Power Delivery. 2020; 36 (3):1603-1618.
Chicago/Turabian StyleMingjie Wei; Weisheng Liu; Hengxu Zhang; Fang Shi; Weijiang Chen. 2020. "Distortion-Based Detection of High Impedance Fault in Distribution Systems." IEEE Transactions on Power Delivery 36, no. 3: 1603-1618.
Large frequency deviation degrades the operation performance of the boiler and its auxiliaries. It affects the output of thermal power units. A significant change in power generation leads to a great frequency deviation. An extended frequency response model for long-term frequency stability assessment is constructed to consider the effects of frequency deviations on boiler auxiliaries. The static power-frequency characteristic of the thermal power unit within an extensive frequency variation range is analyzed. It reveals that the active power output of the generating unit is not monotonically increasing with frequency dropping. An inflection point is observed on the static power-frequency characteristic curve when considering boiler auxiliary frequency characteristics. In the range of greater frequency deviation, the output power decreases rapidly with frequency declination, and an unstable equilibrium point (UEP) of frequency stability is identified. A quantitative index is proposed for frequency stability assessment based on UEP. The stability characteristic and the frequency stability quantitative index based on UEP are analyzed. The frequency dynamic behaviors of the extended model are demonstrated to analyze frequency stability characteristics within an extensive frequency variation range by a single machine system and the IEEE 39-bus system with considering boilers and its auxiliaries.
Yuzheng Xie; Changgang Li; Hengxu Zhang; Huadong Sun; Vladimir Terzija. Long-Term Frequency Stability Assessment Based on Extended Frequency Response Model. IEEE Access 2020, 8, 122444 -122455.
AMA StyleYuzheng Xie, Changgang Li, Hengxu Zhang, Huadong Sun, Vladimir Terzija. Long-Term Frequency Stability Assessment Based on Extended Frequency Response Model. IEEE Access. 2020; 8 (99):122444-122455.
Chicago/Turabian StyleYuzheng Xie; Changgang Li; Hengxu Zhang; Huadong Sun; Vladimir Terzija. 2020. "Long-Term Frequency Stability Assessment Based on Extended Frequency Response Model." IEEE Access 8, no. 99: 122444-122455.
Non-intrusive load monitoring (NILM) is a process of estimating operational states and power consumption of individual appliances, which if implemented in real-time, can provide actionable feedback in terms of energy usage and personalized recommendations to consumers. Intelligent disaggregation algorithms such as deep neural networks can fulfill this objective if they possess high estimation accuracy and lowest generalization error. In order to achieve these two goals, this paper presents a disaggregation algorithm based on a deep recurrent neural network using multi-feature input space and post-processing. First, the mutual information method was used to select electrical parameters that had the most influence on the power consumption of each target appliance. Second, selected steady-state parameters based multi-feature input space (MFS) was used to train the 4-layered bidirectional long short-term memory (LSTM) model for each target appliance. Finally, a post-processing technique was used at the disaggregation stage to eliminate irrelevant predicted sequences, enhancing the classification and estimation accuracy of the algorithm. A comprehensive evaluation was conducted on 1-Hz sampled UKDALE and ECO datasets in a noised scenario with seen and unseen test cases. Performance evaluation showed that the MFS-LSTM algorithm is computationally efficient, scalable, and possesses better estimation accuracy in a noised scenario, and generalized to unseen loads as compared to benchmark algorithms. Presented results proved that the proposed algorithm fulfills practical application requirements and can be deployed in real-time.
Hasan Rafiq; Xiaohan Shi; Hengxu Zhang; Huimin Li; Manesh Kumar Ochani. A Deep Recurrent Neural Network for Non-Intrusive Load Monitoring Based on Multi-Feature Input Space and Post-Processing. Energies 2020, 13, 2195 .
AMA StyleHasan Rafiq, Xiaohan Shi, Hengxu Zhang, Huimin Li, Manesh Kumar Ochani. A Deep Recurrent Neural Network for Non-Intrusive Load Monitoring Based on Multi-Feature Input Space and Post-Processing. Energies. 2020; 13 (9):2195.
Chicago/Turabian StyleHasan Rafiq; Xiaohan Shi; Hengxu Zhang; Huimin Li; Manesh Kumar Ochani. 2020. "A Deep Recurrent Neural Network for Non-Intrusive Load Monitoring Based on Multi-Feature Input Space and Post-Processing." Energies 13, no. 9: 2195.
The accurate modelling of the arc is significant for the researches on the high impedance arcing fault (HIAF), which performs sig-nificant variations of nonlinearity under different fault conditions. The diversity of the waveform distortions during HIAFs is rarely investigated previously. This paper proposes a black-box HIAF model to simulate the nonlinear current distortions with im-proved controllability and higher accuracy. Firstly, with field HIAF faults experimented in a 10kV distribution network, three major characteristics varying in the distortions of the fault cur-rent are summarized and illustrated, including the offset, extent, and duration. Secondly, a distortion-controllable (DIST-C) HIAF model is proposed based on the heat balance equation of the arc after reasonable assumptions and transformations. The three characteristics of distortions can be independently and directly controlled. Then, the implementation of the DIST-C model in PSCAD is detailedly illustrated. An automatic parameter deter-mination method using particle swarm optimization in a Py-thon-PSCAD-MATLAB co-simulation platform is presented. Finally, the controllability and accuracy of the proposed model are verified by comparing it with the other existing typical black-box models.
Mingjie Wei; Weisheng Liu; Fang Shi; Hengxu Zhang; Zongshuai Jin; Weijiang Chen. Distortion-Controllable Arc Modeling for High Impedance Arc Fault in the Distribution Network. IEEE Transactions on Power Delivery 2020, 36, 52 -63.
AMA StyleMingjie Wei, Weisheng Liu, Fang Shi, Hengxu Zhang, Zongshuai Jin, Weijiang Chen. Distortion-Controllable Arc Modeling for High Impedance Arc Fault in the Distribution Network. IEEE Transactions on Power Delivery. 2020; 36 (1):52-63.
Chicago/Turabian StyleMingjie Wei; Weisheng Liu; Fang Shi; Hengxu Zhang; Zongshuai Jin; Weijiang Chen. 2020. "Distortion-Controllable Arc Modeling for High Impedance Arc Fault in the Distribution Network." IEEE Transactions on Power Delivery 36, no. 1: 52-63.
Frequency drop due to loss of massive generation is a threat to power system frequency stability. Under-frequency load shedding (UFLS) is the principal measure to prevent successive frequency declination and blackouts. Based on traditional stage-by-stage UFLS scheme, a new continuous UFLS scheme is proposed in this paper to shed loads proportional to frequency deviation. The characteristic of the proposed scheme is analyzed with a closed-form solution of frequency dynamics. Frequency threshold and time delay are added to make the proposed scheme practical. A line-by-line scheme based on precise load control is introduced to implement the continuous scheme for systems without enough continuously controllable loads. The load shedding scale factor of the proposed scheme is tuned with an analytical method to achieve adaptability to different operating conditions. The adaptability of the proposed scheme is validated with 39-bus New England model and simplified Shandong Power Grid of China.
Changgang Li; Yue Wu; Yanli Sun; Hengxu Zhang; Yutian Liu; Yilu Liu; Vladimir Terzija. Continuous Under-Frequency Load Shedding Scheme for Power System Adaptive Frequency Control. IEEE Transactions on Power Systems 2019, 35, 950 -961.
AMA StyleChanggang Li, Yue Wu, Yanli Sun, Hengxu Zhang, Yutian Liu, Yilu Liu, Vladimir Terzija. Continuous Under-Frequency Load Shedding Scheme for Power System Adaptive Frequency Control. IEEE Transactions on Power Systems. 2019; 35 (2):950-961.
Chicago/Turabian StyleChanggang Li; Yue Wu; Yanli Sun; Hengxu Zhang; Yutian Liu; Yilu Liu; Vladimir Terzija. 2019. "Continuous Under-Frequency Load Shedding Scheme for Power System Adaptive Frequency Control." IEEE Transactions on Power Systems 35, no. 2: 950-961.
As a result of small fault current, high level of noise and a large penetration of distributed generators (DG), in the neutral non-effectively grounded medium-voltage (MV) distribution networks, it is quite difficult to locate the faulted line section for single phase to ground faults. In this paper, using a technique based on synchronized measurements in distribution networks, a fault location method based on the analysis of the energy of the transient zero-sequence current in the selected frequency band (SFB) is proposed. The equivalent impedance of the distribution network with lateral branches is studied with an equivalent network, and the phase-frequency characteristics of the equivalent impedance are analyzed. The SFB, within which the transient energy of the faulty line section is larger than that of the healthy line sections is determined. A combined fault-section location criterion is proposed and the implementation scheme is illustrated with the distribution level phasor measurement units. Numerical simulations of the IEEE 34 node system and the field experiments of a 10kV distribution network validate the feasibility and effectiveness of the proposed method.
Xuewen Wang; Hengxu Zhang; Fang Shi; Qiuwei Wu; Vladimir Terzija; Wei Xie; Chen Fang. Location of Single Phase to Ground Faults in Distribution Networks Based on Synchronous Transients Energy Analysis. IEEE Transactions on Smart Grid 2019, 11, 774 -785.
AMA StyleXuewen Wang, Hengxu Zhang, Fang Shi, Qiuwei Wu, Vladimir Terzija, Wei Xie, Chen Fang. Location of Single Phase to Ground Faults in Distribution Networks Based on Synchronous Transients Energy Analysis. IEEE Transactions on Smart Grid. 2019; 11 (1):774-785.
Chicago/Turabian StyleXuewen Wang; Hengxu Zhang; Fang Shi; Qiuwei Wu; Vladimir Terzija; Wei Xie; Chen Fang. 2019. "Location of Single Phase to Ground Faults in Distribution Networks Based on Synchronous Transients Energy Analysis." IEEE Transactions on Smart Grid 11, no. 1: 774-785.
Grounding arc fault (GAF) happening in the medium-voltage (MV) distribution system may result in great damages to devices and human security. However, difficulties still exist in identifying those faults with higher grounding impedances due to the weaker feature and the varieties when grounded with different surfaces. This paper presents an integrated algorithm to detect the high impedance arc faults (HIAFs) with high-resolution waveform data provided by distribu-tion-level PMUs (D-PMUs) deployed in the system. An im-proved arc model is proposed which can continuously imitate the randomness and intermittence during the ‘unstable arcing period’ of arc faults. The integrated algorithm consists of two branches. Firstly, the variations of HIAFs during unstable arcing period is identified with the unified harmonic energy and global randomness index, which can unify the scale of harmonic content in different fault situations and enlarge the disparities from non-fault conditions. Then, the waveform distortions of HIAFs during the stable arcing period are identified with discrete wavelet transform (DWT) to extract the detailed distribution characteristics. The reliability and security of the proposed algorithm is verified with numerical simulations and field tests in a 10kV distribution system.
Mingjie Wei; Fang Shi; Hengxu Zhang; Zongshuai Jin; Vladimir Terzija; Jinan Zhou; Hailong Bao. High Impedance Arc Fault Detection Based on the Harmonic Randomness and Waveform Distortion in the Distribution System. IEEE Transactions on Power Delivery 2019, 35, 837 -850.
AMA StyleMingjie Wei, Fang Shi, Hengxu Zhang, Zongshuai Jin, Vladimir Terzija, Jinan Zhou, Hailong Bao. High Impedance Arc Fault Detection Based on the Harmonic Randomness and Waveform Distortion in the Distribution System. IEEE Transactions on Power Delivery. 2019; 35 (2):837-850.
Chicago/Turabian StyleMingjie Wei; Fang Shi; Hengxu Zhang; Zongshuai Jin; Vladimir Terzija; Jinan Zhou; Hailong Bao. 2019. "High Impedance Arc Fault Detection Based on the Harmonic Randomness and Waveform Distortion in the Distribution System." IEEE Transactions on Power Delivery 35, no. 2: 837-850.
Sudden loss of bulk power generation will result in significant power shortage and power flow redistribution, which may lead to insecurity and/or stability problems. Under this condition, load shedding (LS) and corrective line switching (CLS) can be used to guarantee a reliable electricity supply. However, at present, the above two procedures are implemented separately, which may deteriorate each other and cause unnecessary load loss. To address this issue, a coordination optimization method is proposed to coordinate event-driven LS and CLS for enhancing power system security and stability as well as reducing LS amount simultaneously. A two-loop integrated algorithm is designed to solve the constrained optimization problem, which takes the transient frequency/voltage deviation and overload capacity of the transmission lines as constraints. In the inner loop, iterative optimization of the LS for frequency/voltage security is achieved based on linearized sensitivity analysis, and then step-by-step summation is employed to get the LS amount for alleviating overload. Neighbor search is used in the outer loop to coordinate event-driven LS and CLS so as to optimize the total LS amount. The effectiveness of the proposed method is validated in a modified IEEE 39 bus test system and an industrial power system. The results show that the proposed scheme can decrease the LS amount without improve the transient security while maintaining the transient security and alleviating overload.
Fang Shi; Hengxu Zhang; Yongji Cao; Huadong Sun; Yun Chai. Enhancing Event-Driven Load Shedding by Corrective Switching With Transient Security and Overload Constraints. IEEE Access 2019, 7, 101355 -101365.
AMA StyleFang Shi, Hengxu Zhang, Yongji Cao, Huadong Sun, Yun Chai. Enhancing Event-Driven Load Shedding by Corrective Switching With Transient Security and Overload Constraints. IEEE Access. 2019; 7 ():101355-101365.
Chicago/Turabian StyleFang Shi; Hengxu Zhang; Yongji Cao; Huadong Sun; Yun Chai. 2019. "Enhancing Event-Driven Load Shedding by Corrective Switching With Transient Security and Overload Constraints." IEEE Access 7, no. : 101355-101365.