scholarly journals A Decentralized Passive Islanding Detection Method Based on the Variations of Estimated Droop Characteristics

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7759
Author(s):  
Juan Roberto Lopez ◽  
Luis Ibarra ◽  
Pedro Ponce ◽  
Arturo Molina
Keyword(s):  
Communication Networks ◽  
Operating Conditions ◽  
Detection Methods ◽  
Electrical Network ◽  
Test Bed ◽  
Electrical Measurements ◽  
Heavy Load ◽  
Load Variations ◽  
Distributed Generators ◽  
Power Frequency

A microgrid including distributed generators can operate connected to the main electrical network or in an isolated manner, referred to as island operation. The transition between both states can occur voluntarily, but a disconnection can also happen unexpectedly. The associated transients can be harmful to the grid, and compensating actions must be triggered to avoid service interruption, preserve power quality, and minimize the possibility of faults; island detection methods are essential to this end. Such techniques typically depend on communication networks or on the introduction of minor electrical disturbances to identify and broadcast unexpected islanding events. However, local energy resources are distributed, variable, and are expected to be integrated in a plug-and-play manner; then, conventional island detection strategies can be ineffective as they rely on specific infrastructure. To overcome those problems, this work proposes a straightforward, distributed island detection technique only relying on local electrical measurements, available at the output of each generating unit. The proposed method is based on the estimated power-frequency ratio, associated with the stiffness of the grid. A “stiffness change” effectively reveals island operating conditions, discards heavy load variations, and enables independent (distributed) operation. The proposal was validated through digital simulations and an experimental test-bed. Results showed that the proposed technique can effectively detect island operation at each generating unit interacting in the microgrid. Moreover, it was about three times faster than other reported techniques.

scholarly journals A Comparative Study on Fault Detection Methods for Gas Turbine Combustion Systems

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 389
Author(s):  
Jinfu Liu ◽  
Zhenhua Long ◽  
Mingliang Bai ◽  
Linhai Zhu ◽  
Daren Yu
Keyword(s):  
Fault Detection ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Operating Conditions ◽  
Detection Methods ◽  
Distribution Model ◽  
Outlet Temperature ◽  
Combustion System ◽  
Comparison Results ◽  
Gas Turbine Combustion

As one of the core components of gas turbines, the combustion system operates in a high-temperature and high-pressure adverse environment, which makes it extremely prone to faults and catastrophic accidents. Therefore, it is necessary to monitor the combustion system to detect in a timely way whether its performance has deteriorated, to improve the safety and economy of gas turbine operation. However, the combustor outlet temperature is so high that conventional sensors cannot work in such a harsh environment for a long time. In practical application, temperature thermocouples distributed at the turbine outlet are used to monitor the exhaust gas temperature (EGT) to indirectly monitor the performance of the combustion system, but, the EGT is not only affected by faults but also influenced by many interference factors, such as ambient conditions, operating conditions, rotation and mixing of uneven hot gas, performance degradation of compressor, etc., which will reduce the sensitivity and reliability of fault detection. For this reason, many scholars have devoted themselves to the research of combustion system fault detection and proposed many excellent methods. However, few studies have compared these methods. This paper will introduce the main methods of combustion system fault detection and select current mainstream methods for analysis. And a circumferential temperature distribution model of gas turbine is established to simulate the EGT profile when a fault is coupled with interference factors, then use the simulation data to compare the detection results of selected methods. Besides, the comparison results are verified by the actual operation data of a gas turbine. Finally, through comparative research and mechanism analysis, the study points out a more suitable method for gas turbine combustion system fault detection and proposes possible development directions.

scholarly journals Predicting the influence of the non-sinusoidal network mode on power transformers

2019 ◽  
Vol 114 ◽  
pp. 04005
Author(s):  
Ngo Van Cuong ◽  
Lidiia I. Kovernikova
Keyword(s):  
Service Life ◽  
Electric Power ◽  
Power Quality ◽  
Electrical Equipment ◽  
Operating Conditions ◽  
Transformer Oil ◽  
Power Transformers ◽  
Electrical Network ◽  
Electrical Networks ◽  
Current Harmonics

The parameters of electrical network modes often do not meet the requirements of Russian GOST 32144-2013 and the guidelines of Vietnam. In the actual operating conditions while there is the non-sinusoidal mode in electrical networks voltage and current harmonics are present. Harmonics result in overheating and damage of power transformers since they cause additional active power losses. Additional losses lead to the additional heat release, accelerating the process of insulating paper, transformer oil and magnetic structure deterioration consequently shortening the service life of a power transformer. In this regard there arises a need to develop certain scientific methods that would help demonstrate that low power quality, for instance could lead to a decrease in the electrical equipment service life. Currently we see a development of automated systems for continuous monitoring of power quality indices and mode parameters of electrical networks. These systems could be supplemented by characteristics calculating programs that give out a warning upon detection of the adverse influence of voltage and current harmonics on various electrical equipment of both electric power providers and electric power consumers. A software program presented in the article may be used to predict the influence of voltage and current harmonics on power transformers.

scholarly journals A Flexible Load Control Strategy for Distribution Network to Reduce the Line Losses and to Eliminate the Transmission Congestion

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Beibei Wang ◽  
Xiaoqing Hu ◽  
Peifeng Shen ◽  
Wenlu Ji ◽  
Yang Cao ◽  
...  
Keyword(s):  
Power Distribution ◽  
Distribution Systems ◽  
Renewable Energy Sources ◽  
Distribution Network ◽  
Test System ◽  
Operating Conditions ◽  
Load Control ◽  
Transmission Congestion ◽  
Heavy Load ◽  
Flexible Load

There are many uncertain factors in the modern distribution network, including the access of renewable energy sources and the heavy load level. The existence of these factors has brought challenges to the stability of the power distribution network, as well as increasing the risk of exceeding transmission capacity of distribution lines. The appearance of flexible load control technology provides a new idea to solve the above problems. Air conditioners (ACs) account for a great proportion of all loads. In this paper, the model of dispatching AC loads in the regional power grid is constructed, and the direct load control (DLC) method is adopted to reduce the load of ACs. An improved tabu search technique is proposed to solve the problem of network dispatch in distribution systems in order to reduce the resistive line losses and to eliminate the transmission congestion in lines under normal operating conditions. The optimal node solution is obtained to find the best location and reduction capacity of ACs for load control. To demonstrate the validity and effectiveness of the proposed method, a test system is studied. The numerical results are also given in this article, which reveal that the proposed method is promising.

scholarly journals A Secured Load Mitigation and Distribution Scheme for Securing SIP Server

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Vennila Ganesan ◽  
Manikandan MSK
Keyword(s):  
Load Distribution ◽  
Test Bed ◽  
Heavy Load ◽  
Server Selection ◽  
Distribution Scheme ◽  
The Mean ◽  
Sip Server ◽  
Second Tier ◽  
Termination Time

Managing the performance of the Session Initiation Protocol (SIP) server under heavy load conditions is a critical task in a Voice over Internet Protocol (VoIP) network. In this paper, a two-tier model is proposed for the security, load mitigation, and distribution issues of the SIP server. In the first tier, the proposed handler segregates and drops the malicious traffic. The second tier provides a uniform load of distribution, using the least session termination time (LSTT) algorithm. Besides, the mean session termination time is minimized by reducing the waiting time of the SIP messages. Efficiency of the LSTT algorithm is evaluated through the experimental test bed by considering with and without a handler. The experimental results establish that the proposed two-tier model improves the throughput and the CPU utilization. It also reduces the response time and error rate while preserving the quality of multimedia session delivery. This two-tier model provides robust security, dynamic load distribution, appropriate server selection, and session synchronization.

Preliminary Study on the Effect of Operating Conditions on the Measurement Accuracy of Electronic Type Electric Energy Meter

2013 ◽  
Vol 834-836 ◽  
pp. 1246-1250
Author(s):  
Hai Bo Yu ◽  
Jia Liu ◽  
Chun Yu Wang ◽  
Li Li ◽  
Rui Ming Tong
Keyword(s):  
Measurement Accuracy ◽  
Reference Conditions ◽  
Electric Energy ◽  
Operating Conditions ◽  
Impulsive Load ◽  
Energy Meter ◽  
Power Frequency ◽  
Working Principle ◽  
Preliminary Study ◽  
Electric Energy Meter

The verification of electronic type electric energy meter is under strict reference conditions, but some special operating conditions at locale will exceed the standard scopes. In order to improve the calculation accuracy and operating reliability of electric energy meter under operating conditions, it is necessary to study the operating conditions. According to the working principle and the standard verification regulation of electronic type electric energy meter, this paper summarizes these operating conditions: low power factor, harmonic waves, dynamic impulsive load, voltage fluctuation and outside magnetic field of power frequency, then analyzes the causes of operating conditions and their influence on electronic type electric energy meter, eventually lays foundation for thorough and systematic study of electric energy meter in the operating conditions, and establishes measurement center database of operating conditions.

scholarly journals Application of Solid-State Transformers in a Novel Architecture of Hybrid AC/DC House Power Systems

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3432 ◽  
Author(s):  
Fabio Bignucolo ◽  
Manuele Bertoluzzo
Keyword(s):  
Solid State ◽  
Power Systems ◽  
Distribution Networks ◽  
Heat Pumps ◽  
Operating Conditions ◽  
Dynamic Simulations ◽  
Load Variations ◽  
Solid State Transformers ◽  
Local Resources ◽  
Induction Cooking

The ongoing diffusion of solid-state DC/DC converters makes possible a partial migration of electric power systems from the present AC paradigm to a future DC scenario. In addition, the power demand in the domestic environment is expected to grow considerably, for example, due to the progressive diffusion of electric vehicles, induction cooking and heat pumps. To face this evolution, the paper introduces a novel electric topology for a hybrid AC/DC smart house, based on the solid-state transformer technology. The electric scheme, voltage levels and converters types are thoroughly discussed to better integrate the spread of electric appliances, which are frequently based on internal DC buses, within the present AC distribution networks. Voltage levels are determined to guarantee high safety zones with negligible electric risk in the most exposed areas of the house. At the same time, the developed control schemes assure high power quality (voltage stability in the case of both load variations and network perturbations), manage power flows and local resources according to ancillary services requirements and increase the domestic network overall efficiency. Dynamic simulations are performed, making use of DIgSILENT PowerFactory software, to demonstrate the feasibility of the proposed distribution scheme for next-generation smart houses under different operating conditions.

Experimental Results of a PEM System Operated on Hydrogen and Reformate

2008 ◽  
Vol 5 (1) ◽  
Author(s):  
M. Minutillo ◽  
E. Jannelli ◽  
F. Tunzio
Keyword(s):  
Fuel Cell ◽  
Natural Gas ◽  
Large Scale ◽  
Pem Fuel Cell ◽  
Proton Exchange ◽  
Operating Conditions ◽  
Cell Performance ◽  
Pure Hydrogen ◽  
Test Bed ◽  
Fuel Cell Performance

The main objective of this study is to evaluate the performance of a proton exchange membrane (PEM) fuel cell generator operating for residential applications. The fuel cell performance has been evaluated using the test bed of the University of Cassino. The experimental activity has been focused to evaluate the performance in different operating conditions: stack temperature, feeding mode, and fuel composition. In order to use PEM fuel cell technology on a large scale, for an electric power distributed generation, it could be necessary to feed fuel cells with conventional fuel, such as natural gas, to generate hydrogen in situ because currently the infrastructure for the distribution of hydrogen is almost nonexistent. Therefore, the fuel cell performance has been evaluated both using pure hydrogen and reformate gas produced by a natural gas reforming system.

Experimental and Numerical Investigation of Centrifugal Pump Performance When Handling Viscous Fluids

2005 ◽  
Author(s):  
M. H. Shojaee Fard ◽  
M. B. Ehghaghi ◽  
F. A. Boyaghchi
Keyword(s):  
Soviet Union ◽  
Centrifugal Pump ◽  
Turbulent Flows ◽  
Characteristic Curve ◽  
Three Dimensional ◽  
Operating Conditions ◽  
Viscous Fluids ◽  
Test Bed ◽  
Flow Process ◽  
Pump Performance

On the test bed of centrifugal pump, the centrifugal pump performance has been investigated using water and viscous oil as Newtonian fluids, whose kinematic viscosities are 1 × 10−6, 43 × 10−6 and 62 × 10−6 m2/s, respectively. Also, the finite volume method is used to model the three dimensional viscous fluids for different operating conditions. For these numerical simulations the SIMPLEC algorithm is used for solving governing equations of incompressible viscous/turbulent flows through the pump. The κ-ε turbulence model is adopted to describe the turbulent flow process. These simulations have been made with a steady calculation and using the multiple reference frame (MRF) technique to take into account the impeller-volute interaction. Numerical results are compared with the experimental characteristic curve for each viscous fluid. The data obtained allow the analysis of the main phenomena existent in this pump, such as: head, efficiency, power and pressure field changes for different operating conditions. Also, the correction factors for oils are obtained from the experimental for part loading (PL), best efficiency point (BEP) and over loading (OL) and the results are compared with proposed factors by American Hydraulic Institute (HIS) and Soviet Union (USSR). The comparisons between the numerical and experimental results show a good agreement.

scholarly journals Analysis of Residual Current Flows in Inverter Based Energy Systems Using Machine Learning Approaches

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 582
Author(s):  
Holger Behrends ◽  
Dietmar Millinger ◽  
Werner Weihs-Sedivy ◽  
Anže Javornik ◽  
Gerold Roolfs ◽  
...  
Keyword(s):  
Machine Learning ◽  
Early Stage ◽  
Residual Current ◽  
Operating Conditions ◽  
Machine Learning Algorithms ◽  
Photovoltaic System ◽  
Detection Methods ◽  
Learning Approaches ◽  
Residual Currents ◽  
Current Flows

Faults and unintended conditions in grid-connected photovoltaic systems often cause a change of the residual current. This article describes a novel machine learning based approach to detecting anomalies in the residual current of a photovoltaic system. It can be used to detect faults or critical states at an early stage and extends conventional threshold-based detection methods. For this study, a power-hardware-in-the-loop approach was carried out, in which typical faults have been injected under ideal and realistic operating conditions. The investigation shows that faults in a photovoltaic converter system cause a unique behaviour of the residual current and fault patterns can be detected and identified by using pattern recognition and variational autoencoder machine learning algorithms. In this context, it was found that the residual current is not only affected by malfunctions of the system, but also by volatile external influences. One of the main challenges here is to separate the regular residual currents caused by the interferences from those caused by faults. Compared to conventional methods, which respond to absolute changes in residual current, the two machine learning models detect faults that do not affect the absolute value of the residual current.

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