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Shanshan Ma, Da Lu, Yubo Yang, Jing Wang, Xuewei Wang
Influence of Fast Fluctuation of Dynamic Load Current on Dynamic Error of Smart Electricity Meter

This paper is concerned with the influence of the dynamic error of smart electricity meter (hereinafter referred to as smart meter) in the condition of dynamic current. Firstly, the random fluctuation of the dynamic load current amplitude is analysed and two typical run lengths are found out. Secondly, dynamic models of every unit in the smart meter are established. These models reflect the dynamic transfer relationship between the input and output signals of every unit. Thirdly, the dynamic errors of smart meter are simulated and analysed in the condition of dynamic current with typical run lengths. Finally, we verify the simulation results by experiment with On-Off-Key (OOK) dynamic test current signal. The result shows that the gain feedback switching of programmable gain amplifier (PGA) unit leads to the dynamic current signal clipping in dynamic current conditions, and the signal clipping is the main source of the dynamic error of smart meter. Moreover, the dynamic error of the short-time run length of dynamic current is larger than the long-time run length.

Meng Zhu, Da Lu, Yubo Yang, Jing Wang, Xuewei Wang
Research on A New Active Power Measurement Algorithm

With the widely use of non-linear electrical equipment , the load signal in the smart grids exhibits distortion and dynamic characteristics. Simultaneously, non-integer-period sampling is inevitable in the power and energy estimation of the smart meter, which brings errors to the energy accumulation. In this paper, firstly, a new window is proposed based on the traditional filter power measurement algorithm and the frequency characteristics of the window are analyzed. Then, based on the window and structured model of smart meter, a new active power measurement algorithm is proposed. And then, in simulations, adopting different active power algorithms, the electric energy measurement errors are simulated and analyzed under non-integer-period sampling .These simulated waveforms include sinusoidal envelope and OOK envelope dynamic test signals based on fundamental wave and five kinds of distortion waveforms in IEC62052. Finally, the results show that the proposed filter can effectively improve the accuracy of active energy accumulation.

Jianhua Li, Xueshen Wang, Pingwei Lin, Xinhua Chen, Longfa Zhang, Shuo Liu
Indium tin oxide thin films prepared by dc magnetron sputtering for transparent heating

This paper reported a research on conducting tin-doped indium oxide (ITO) films fabricated by dc magnetron sputtering for transparent heating. ITO films with a thickness of 130 nm were deposited on BF33 glass substrates, followed by an annealing process in N 2 atmosphere for 2 h at 450 ?. The crystal structure, surface morphology, optical and electrical properties of ITO films were characterized. The predominant crystal face orientation was (222). The transmittance from 400 nm to 800 nm was 92.5%. The sheet resistance and resistivity increased, and the temperature coefficient of resistance (TCR) decreased with the larger oxygen flow rate. A low TCR and proper resistivity were the key factors for the application of conducting transparent heating.

Xueshen Wang, Jinjin Li, Yuan Zhong, Qing Zhong
Investigation of nano-SQUIDs with Dayem bridges by e-beam lithography and reaction ion etching

Nano-SQUIDs are sensitive devices for quantum detection and precision measurements due to the ultra-low noise level. This paper reports the fabrication and characterization of nano-SQUIDs fabricated by e-beam lithography and reaction ion etching (RIE). The Nano-SQUIDs were comprised by two Dayem nanobridges and a loop based on the monolayer Nb film. The width of the nanobridges was 94 nm and the diameter of the loop was 20 µm. A measurement system based on a physical properties measurement system and source-meters. The voltage-bias current (Ibias-V) properties at different temperatures showed that the working range of the nano-squid was 8.3 K to 7.0 K. The voltage-modulation flux (V-?) were characterized at 8.2 K and the flux modulation depth was large to be 74.5% with the bias current 287 µA. The Ibias-V and V-? (Icoil) showed that the e-beam lithography and RIE process were suitable for fabrication of nano-SQUIDs.

Damiano Crescini, Alessio Galli, Davide Alghisi, Farid Touati
Ambient Monitoring WSNs with Harvesting-aware Power Management

Capillary wireless sensor networks dedicated to air quality monitoring have provided essential information on hazardous air condition, generating early warnings to prevent danger situation for human health. The main challenge of capillary networks is the adoption of environmentally generated energy as primary and/or unique energy source instead of the replacement of hundreds or even thousands of batteries on a regular basis that leads to high costs and practical problems of devices management. We present in this paper a battery-less, autonomous, multi-parametric sensing platform for air quality monitoring, that is harvesting energy from the surrounding environment for perpetual operation. We present a complete system design and experimental results of the evaluation of the energy harvesting section and the budget allocation of the power consumption. Moreover, the paper shows the experimental results of the studies conducted on the sensors section. A tailored calibration process for the sensors' sensitivity and a standard portfolio of different energy sources around the power recovery section could effectively enable the system to trace air quality levels in indoor and outdoor application, in a sort of “set and forget” scenario.

O. Velychko, S. Karpenko
Interlaboratory Comparison for Electric Power Measurements at Industrial Frequency in Ukraine

SE "UKRMETRTESTSTANDARD" provided and carried out the interlaboratory comparison (ILC) as reference measurements provider for all Ukraine accredited calibration laboratories (CL’s) for electric power (EP) measurements at industrial frequency. This paper presents the assessment of CL’s which participated at ILC within EP measurements at industrial frequency. The main goal of this ILC was the assessment of CL’s capabilities that perform calibration in EP measurement.

Oleh Velychko, Tetyana Gordiyenko
Linking results of RMO comparisons and inter-laboratory comparisons for AD/DC voltage transfer difference

The global metrological traceability fully depends on the implementation of international mutual recognition agreements in field of metrology.
The linked results of international comparisons of national standards and national inter-laboratory comparison for AD/DC voltage transfer difference measurements was presented.

Jakub Svatos, Jan Holub
Woodhouse Energy Consumption Measurement System for Diagnostics of Thermal and Technical Properties of Buildings Envelope

To reduce the construction costs and to increase energy savings and the indoor environmental quality in a woodhouse, an energy consumption measuring system for diagnostics of thermal and technical properties of buildings envelope is introduced. At present, the vast majority of calculations for the thermal and technical characteristics of buildings are based on simple mathematical models of building envelope behaviour derived primarily from the thermal conductivity of individual materials. However, the thermal conductivity is measured in a stable laboratory environment. Therefore, the measured values may not match the real behaviour of materials in continually changing climatic conditions. The Energy Consumption Measuring System has been installed to eight woodhouses in different climatic areas to diagnose the thermal and technical properties of buildings envelope. The power consumption, temperature, and humidity of the air and of the wood, CO2 concentration, temperature of the individual layers of the envelope sandwich structure and wind speed and direction are measured. Thanks to the sets of real measurements of the thermal and technical behaviour, the actual dependence of the indoor environment quality on the outdoor climatic conditions are obtained.

Piotr Bilski
Application of the fusion of regression machines for the analog circuit state identification

The paper presents the application of the combined group of regression algorithms to identify state of the analog circuit. Implementing the fusion of regression machines is aimed at obtaining high accuracy of the diagnosed system’s state, especially compared to the single parameter identification algorithm. The large number of simple methods (such as linear regression techniques) is expected to give the high accuracy without the need of time consuming and complex optimization of the selected approach (such as Support Vector Machines – SVM). The approach consists in preparing the ensemble architecture, selecting computational methods, optimizing features extracted from the diagnosed system and testing the approach. The tests were conducted to evaluate efficiency of various fusion architectures, determine their accuracy for different sets of features and confront them against the single optimized regression algorithm. The time analysis verified the ability of the approach to use the framework in the online mode. Obtained results show the potential of the proposed framework for the accurate identification of analog system parameters, which can be used to analyse other types of systems.

Weiqiang Zhao, Eduard Egusquiza, Carme Valero, Mònica Egusquiza, David Valentín, Alexandre Presa
A Novel Condition Monitoring Methodology Based on Neural Network of Pump-Turbines with Extended Operating Range

Due to the entrance of new renewable energies, water-storage energy has to be regulated more frequently to keep the stability of power grid. Consequently, pump-turbines have to work under off- design conditions more than before, which will cause more damage and decrease their useful life. Advanced monitoring methodologies that can balance the degradation of machine and revenues to the power plant has been required. To develop an innovative condition monitoring approach, vibration data was collected from different components of a pump-turbine which is running in an extended operating range. The consequences of operating range extension on the vibration of the pump-turbine have been studied by analysing the vibration signatures. The changing rule of the vibration behavior of the machine with the operating parameters has been obtained. An artificial neural network based model has been applied to build an autoregressive normal behavior model. The results indicated that the normal behavior model based on multi-layer neural net has the ability to predict the vibration characteristics of the machine in different operating conditions. This monitoring method can be adapted to the similar type of hydraulic turbine units.

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