IMPACT OF DFIG-BASED WIND FARMS ON GENERATOR DISTANCE PHASE BACKUP PROTECTION

Renewable energy technologies are clean sources of energy that have a lower environmental impact than conventional energy technologies. Among all the renewable energy sources, wind energy is clean and plentiful compared to nonrenewable energy sources like fossil fuels and cost-effective compared to other renewable energy sources such as nuclear. Therefore, the potential for wind energy is immense. Nowadays, wind farms are increasingly employed in power systems in order to meet the growing demand of energy as well as the growing environmental awareness. Grid integration of large capacity of wind energy requires, however, new approaches for system operation, control, dynamic enhancement and protection. This thesis reports the results of digital time-domain simulation studies that are carried out to investigate the effect of Doubly-Fed Induction Generator (DFIG)-based wind farms on the performance of generator distance phase backup protection element (Relay (21)) in order to identify important issues that protection engineers need to consider when designing and setting a generator protection system. Such investigation is achieved through incorporating a large DFIG-based wind farm in a study system that inspired from an actual power system. The incorporation takes place under different Relay (21) zone settings. In this context, comparative studies between the relay performance with and without the presence of the DFIG-based wind farm during different faults are presented. The effects of fault location, fault type, generator loading, power flows in the transmission lines in conjunction with wind farm rating and location are also investigated. For validation purposes, time-domain simulations are conducted on benchmark models using the ElectroMagnetic Transients program (EMTP-RV). The results of the investigations carried out in this thesis reveal that DFIG -based wind farm has an effect on the generator distance phase backup protection that leads to error in measured impedance by the generator distance phase backup protection element. This effect varies according to fault type, fault location, generator loading, power flows on transmission lines as well as DFIG-based wind farm rating and location

Calculation of Lightning Transient Responses on Wind Turbine Towers

An efficient method is proposed in this paper for calculating lightning transient responses on wind turbine towers. In the proposed method, the actual tower body is simplified as a multiconductor grid in the shape of cylinder. A set of formulas are given for evaluating the circuit parameters of the branches in the multiconductor grid. On the basis of the circuit parameters, the multiconductor grid is further converted into an equivalent circuit. The circuit equation is built in frequency-domain to take into account the effect of the frequency-dependent characteristic of the resistances and inductances on lightning transients. The lightning transient responses can be obtained by using the discrete Fourier transform with exponential sampling to take the inverse transform of the frequency-domain solution of the circuit equation. A numerical example has been given for examining the applicability of the proposed method

Analysis of islanding detection capabilities of multi-inverter systems

Islanding is one important concern for grid connected distributed resources due to personnel and equipment safety. Inverter-resident islanding detection methods (IDMs) employ locally measured parameters to detect islanding. Passive type IDMs only monitor local variables such as voltage and frequency while active IDMs inject disturbances into the supply system and detect islanding based on system responses. Although very effective in systems with a single inverter, it is believed that active frequency drifting IDMs might have their effectiveness reduced in multi-inverter systems. This thesis investigates the islanding detection capabilities of multi-inverter systems. Three possible scenarios with passive-active, different and same type of active IDMs were discussed. Their performance was assessed using the concept of non-detection zones (NDZs) in a quality factor ( Q f ) vs. load resonant frequency ( f 0 ) load parameter space extended to multi-inverter systems. This thesis also proposes the use of a small dedicated reactive power source (STATCOM) as the sole active component in a multi-inverter system. In this way, interactions between inverters with active IDMs are prevented while effective islanding detection capability is provided by the islanding detection enhancer. The simulation and experiment results were presented to validate the theoretical analysis and the effectiveness of the proposed techniques

LogGD:Detecting Anomalies from System Logs by Graph Neural Networks

Log analysis is one of the main techniques engineers use to troubleshoot faults of large-scale software systems. During the past decades, many log analysis approaches have been proposed to detect system anomalies reflected by logs. They usually take log event counts or sequential log events as inputs and utilize machine learning algorithms including deep learning models to detect system anomalies. These anomalies are often identified as violations of quantitative relational patterns or sequential patterns of log events in log sequences. However, existing methods fail to leverage the spatial structural relationships among log events, resulting in potential false alarms and unstable performance. In this study, we propose a novel graph-based log anomaly detection method, LogGD, to effectively address the issue by transforming log sequences into graphs. We exploit the powerful capability of Graph Transformer Neural Network, which combines graph structure and node semantics for log-based anomaly detection. We evaluate the proposed method on four widely-used public log datasets. Experimental results show that LogGD can outperform state-of-the-art quantitative-based and sequence-based methods and achieve stable performance under different window size settings. The results confirm that LogGD is effective in log-based anomaly detection.Comment: 12 pages, 12 figure

Characteristics of transient pressure performance of horizontal wells in fractured-vuggy tight fractal reservoirs considering nonlinear seepage

International audienceSince the classical seepage theory has limitations in characterizing the heterogeneity of fractured-vuggy tight reservoirs, well test interpretation results are not consistent with actual production by far. Based on the nonlinear percolation theory, a new nonlinear seepage equation considering the boundary layer and yield stress was derived to describe the seepage characteristics of dense matrix blocks and the stress sensitivity and fractal features of fracture systems were characterized by applying the fractal theory. Thus, the nonlinear model of a horizontal well in a fractured-vuggy tight fractal reservoir was established naturally. Then the finite element method was applied to solve the bottom hole pressure based on the processing of internal boundary conditions. After solving the model, the seepage characteristics of different models were summarized by analyzing the bottom hole pressure dynamic curves and the sensitivity analysis of multiple parameters such the nonlinear parameter and fractal index were conducted. Finally, the practicality of the model was proved through a field application. The results show that the pressure dynamic curves can be divided into nine flow stages and the increase of the nonlinear parameter will cause the intensity of the cross flow from matrix blocks to the fracture system to decrease. The fractal index is irrelevant to the intensity of the cross flow while it decides the upwarping degree of the curve at the middle and late flow stages. On the basis of the results of the field application, it can be concluded that the model fits well with actual production and the application of this model can improve the accuracy of well test interpretation

Vertical Fiscal Imbalance and Local Fiscal Discipline: Empirical Evidence from China

Using a nationwide city-level panel dataset for China for the years 1999-2009, this paper examines the effects of vertical fiscal imbalances (VFI) on local fiscal discipline, and explicitly explores the institutional conditions under which these effects may take place. We find that higher VFI levels induce fiscal indiscipline by reducing tax effort of local governments. We exploit the unique Chinese fiscal institution of assigning taxing power for local taxes and shared taxes to two separate authorities (i.e., the local tax bureau and the central tax bureau, respectively) in several ways. We show that local governments respond to the presence of the VFI by lowering their tax effort on local taxes, but do not do so for shared taxes. In addition, we show that the (in)disciplining effect of the VFI is not present for extra-budgetary revenues, which reflects the institutional fact that extra-budgetary revenues are not considered for the determination of central fiscal transfers to local governments, thus creating no incentive for local governments to respond in this are