Analiza vremena ispitivanja i greške očitavanja pametnih brojila električne energije u zavisnosti od njihovog podešenja

2021 ◽  
Vol 23 (1) ◽  
pp. 50-55
Author(s):  
Đorđe Dukanac
Keyword(s):  
Energy Loss ◽  
Electrical Energy ◽  
Indirect Measurement ◽  
Phase Voltage ◽  
Additional Error ◽  
Smart Meters ◽  
Accuracy Class ◽  
Periodic Control ◽  
Instrument Transformers ◽  
Secondary Side

The time of checking the registers of smart meters of accuracy class 0.2 S for indirect measurement of active electricity via instrument transformers, during the first, extraordinary or periodic control and verification has been significantly increased according to the latest Rules on meters of active electrical energy of accuracy class 0.2 S from December 23, 2016. This is especially pronounced when the meter is set to show the measured value of electrical energy in kWh on the secondary side of instrument transformers with the often used meter of active electrical energy of accuracy class 0.2 S, rated phase voltage 110 / √3 V and for the rated current 1 A. In that way, the total time as well as the costs of testing such meters has increased a lot. In addition, with electricity meters set in this way with a resolution of three decimal places and a unit in kWh, there is an additional error when reading the measured value of active electrical energy and especially when calculating the energy loss of active electrical energy. A more acceptable approach to setting such meters will be considered.

scholarly journals Real Fault Location in a Distribution Network Using Smart Feeder Meter Data

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3242
Author(s):  
Hamid Mirshekali ◽  
Rahman Dashti ◽  
Karsten Handrup ◽  
Hamid Reza Shaker
Keyword(s):  
Fault Location ◽  
Network Reliability ◽  
Distribution Network ◽  
Estimation Method ◽  
Electrical Energy ◽  
Distribution Networks ◽  
Active Power ◽  
Financial Loss ◽  
Smart Meters ◽  
The Real

Distribution networks transmit electrical energy from an upstream network to customers. Undesirable circumstances such as faults in the distribution networks can cause hazardous conditions, equipment failure, and power outages. Therefore, to avoid financial loss, to maintain customer satisfaction, and network reliability, it is vital to restore the network as fast as possible. In this paper, a new fault location (FL) algorithm that uses the recorded data of smart meters (SMs) and smart feeder meters (SFMs) to locate the actual point of fault, is introduced. The method does not require high-resolution measurements, which is among the main advantages of the method. An impedance-based technique is utilized to detect all possible FL candidates in the distribution network. After the fault occurrence, the protection relay sends a signal to all SFMs, to collect the recorded active power of all connected lines after the fault. The higher value of active power represents the real faulty section due to the high-fault current. The effectiveness of the proposed method was investigated on an IEEE 11-node test feeder in MATLAB SIMULINK 2020b, under several situations, such as different fault resistances, distances, inception angles, and types. In some cases, the algorithm found two or three candidates for FL. In these cases, the section estimation helped to identify the real fault among all candidates. Section estimation method performs well for all simulated cases. The results showed that the proposed method was accurate and was able to precisely detect the real faulty section. To experimentally evaluate the proposed method’s powerfulness, a laboratory test and its simulation were carried out. The algorithm was precisely able to distinguish the real faulty section among all candidates in the experiment. The results revealed the robustness and effectiveness of the proposed method.

scholarly journals Analisa Keseimbangan Energi PLTU Takalar (Punagaya) Unit 2 Berdasarkan Perubahan Beban

2021 ◽  
Vol 18 (2) ◽  
pp. 257
Author(s):  
Makmur Saini ◽  
Nur Hamzah ◽  
Devi Prasetyo Utomo
Keyword(s):  
Energy Balance ◽  
Energy Loss ◽  
Heat Rate ◽  
Electrical Energy ◽  
Optimal Operation ◽  
Steam Power ◽  
Energy Balance Method ◽  
Full Load ◽  
Operation Pattern ◽  
Operating Target

This study aims to calculate the efficiency and heat rate of the unit 2 PLTU Takalar (Punagaya) system with the energy balance calculation method, calculate the NPHR value of PLTU Takalar (Punagaya) unit 2 when the unit is operating, and also to determine the energy loss from the conversion energy results at PLTU Takalar (Punagaya) unit 2 when the unit operates. The PLTU's Net Plant Heat Rate (NPHR) value is a very important role as an indicator of the performance of a steam power plant. The real-time NPHR value calculation using the energy balance method can be used as an evaluation material to control the operation pattern of the generator in order to obtain optimal operation. The method used in this research is to collect direct and indirect data to calculate the energy balance and NPHR of PLTU Takalar (Punagaya) unit 2 during the reliability run period. The calculations carried out include the calculation of the energy balance in the boiler, the energy balance in the steam cycle, the balance of electrical energy, the efficiency of the PLTU and NPHR systems. Based on the results of calculations that have been carried out the efficiency and NPHR of PLTU Takalar (Punagaya) unit 2 is the best during the reliability run of 32.76% and 2801.93 kcal / kWh at full load conditions with an energy loss value of 220.60 MW. The performance of PLTU Takalar (Punagaya) unit 2 during the reliability run is very good where the unit operates continuously and the NPHR value when full load fulfills the contract warranty and the maximum operating target. 

Smart Metering for Applications

2014 ◽  
Vol 960-961 ◽  
pp. 823-827
Author(s):  
Ying Pan ◽  
Bo Jiang
Keyword(s):  
Smart Grid ◽  
Electrical Energy ◽  
Smart Meter ◽  
Smart Metering ◽  
Power Network ◽  
Energy Usage ◽  
Smart Meters ◽  
Additional Information ◽  
Energy Efficiency Improvement ◽  
Energy Meter

As an important part of Smart Grid, smart metering attracts more and more attention all over the world. It is the way for energy consumer to sense the benefit of smart grid directly. Smart meter is an advanced energy meter that measures consumption of electrical energy providing additional information compared to a conventional energy meter. This paper discusses various applications and technologies that can be integrated with a smart meter. Smart meters can be used not only from the supply side monitoring but also for the demand side management as well. It plays an important role to monitor the performance and the energy usage of the grid loadings and power quality. In addition, This paper gives a comprehensive view on the benefit of smart metering in power network such as energy efficiency improvement.

Implementation of Load Control for Smart Metering in Smart Grids

2022 ◽  
pp. 127-164
Author(s):  
Abdelmadjid Recioui ◽  
Fatma Zohra Dekhandji
Keyword(s):  
Smart Grids ◽  
Control Process ◽  
Electrical Energy ◽  
Load Control ◽  
Smart Meters ◽  
Cumulative Energy ◽  
Photovoltaic Panel ◽  
Labview Software ◽  
Data Acquisition Card ◽  
Cost Calculations

The conventional energy meters are not suitable for long operating purposes as they spend much human and material resources. Smart meters, on the other hand, are devices that perform advanced functions including electrical energy consumption recording of residential/industrial users, billing, real-time monitoring, and load balancing. In this chapter, a smart home prototype is designed and implemented. Appliances are powered by the grid during daytime, and a photovoltaic panel stored power during the night or in case of an electricity outage. Second, consumed power from both sources is sensed and further processed for cumulative energy, cost calculations and bill establishment for different proposed scenarios using LABVIEW software. Data are communicated using a USB data acquisition card (DAQ-USB 6008). Finally, a simulation framework using LABVIEW software models four houses each equipped with various appliances. The simulator predicts different power consumption profiles to seek of peak-demand reduction through a load control process.

scholarly journals MACHINE LEARNING AND IOT FOR SMART GRID

2020 ◽  
Vol XLIV-4/W3-2020 ◽  
pp. 233-240
Author(s):  
M. Fouad ◽  
R. Mali ◽  
A. Lmouatassime ◽  
M. Bousmah
Keyword(s):  
Machine Learning ◽  
Energy Consumption ◽  
Smart Grid ◽  
Power Distribution ◽  
Short Term Memory ◽  
Electrical Energy ◽  
Distribution Networks ◽  
Smart Meters ◽  
Power Distribution Networks ◽  
Electricity Grid

Abstract. The current electricity grid is no longer an efficient solution due to increasing user demand for electricity, old infrastructure and reliability issues requires a transformation to a better grid which is called Smart Grid (SG). Also, sensor networks and Internet of Things (IoT) have facilitated the evolution of traditional electric power distribution networks to new SG, these networks are a modern electricity grid infrastructure with increased efficiency and reliability with automated control, high power converters, modern communication infrastructure, sensing and measurement technologies and modern energy management techniques based on optimization of demand, energy and availability network. With all these elements, harnessing the science of Artificial Intelligence (AI) and Machine Learning (ML) methods become better used than before for prediction of energy consumption. In this work we present the SG with their architecture, the IoT with the component architecture and the Smart Meters (SM) which play a relevant role for the collection of information of electrical energy in real time, then we treat the most widely used ML methods for predicting electrical energy in buildings. Then we clarify the relationship and interaction between the different SG, IoT and ML elements through the design of a simple to understand model, composed of layers that are grouped into entities interacting with links. In this article we calculate a case of prediction of the electrical energy consumption of a real Dataset with the two methods Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM), given their precision performances.

scholarly journals Compression Techniques of Electrical Energy Data for Load Monitoring: A Review

2021 ◽  
Vol 18 (3) ◽  
pp. 194-208
Author(s):  
F.M. Dahunsi ◽  
O. A. Somefun ◽  
A.A. Ponnle ◽  
K.B. Adedeji
Keyword(s):  
Electrical Energy ◽  
Reconstruction Error ◽  
Smart Meters ◽  
Compression Efficiency ◽  
Energy Data ◽  
Load Monitoring ◽  
Active Interest ◽  
Efficient Processing ◽  
The Subject ◽  
And Storage

In recent years, the electric grid has experienced increasing deployment, use, and integration of smart meters and energy monitors. These devices transmit big time-series load data representing consumed electrical energy for load monitoring. However, load monitoring presents reactive issues concerning efficient processing, transmission, and storage. To promote improved efficiency and sustainability of the smart grid, one approach to manage this challenge is applying data-compression techniques. The subject of compressing electrical energy data (EED) has received quite an active interest in the past decade to date. However, a quick grasp of the range of appropriate compression techniques remains somewhat a bottleneck to researchers and developers starting in this domain. In this context, this paper reviews the compression techniques and methods (lossy and lossless) adopted for load  monitoring. Selected top-performing compression techniques metrics were discussed, such as compression efficiency, low reconstruction error, and encoding-decoding speed. Additionally reviewed is the relation between electrical energy, data, and sound compression. This review will motivate further interest in developing standard codecs for the compression of electrical energy data that matches that of other domains.

scholarly journals Pengaruh Susut Energi (Losses) Pada Jaringan Distribusi (Studi Kasus: di PT. Krakatau Daya listrik)

2020 ◽  
Vol 12 (2) ◽  
pp. 80-89
Author(s):  
Desmira Desmira
Keyword(s):  
Energy Loss ◽  
Power Plants ◽  
Voltage Drop ◽  
Electrical Energy ◽  
Work Related ◽  
Distribution Process ◽  
The Cost ◽  
Selection Stage ◽  
A Company ◽  
Research Stage

PT. Krakatau Daya Listrik is a company that distributes electricity. In the distribution process of electricity distribution from generators to consumers, there is an inconsistency with the data on electrical energy supplied from power plants to the energy that is consumed. consumers are also the background of this research. The research objective is how much energy losses (losses) in the conductor that flows from the generator to the maximum and minimum consumer consumption during 2018. This research method is 1. Preparation stage by identifying problems with energy loss (Losess), 2. Pre-Research Stage This stage is looking for reference sources that will be used either from books, internet, thesis results or practical work related to the theme taken namely energy loss, 3. Data Selection Stage This stage is data collection in accordance with the targets and objectives of this study. The results of the study were the minimum losses recorded during 2018, which was (-2.041%), and the maximum value was (1.588%). The conclusion of this research is that the smaller the size of the carrier, it means that the lower the cost of distribution. And if the smaller the size that is on the conductor, it means that the voltage drop and the average total value of distribution losses per year will be even greater.

scholarly journals Experimental determination of the parameters of the eight-pole

2019 ◽  
Vol 21 (4) ◽  
pp. 85-94
Author(s):  
G. A. Bol'shanin ◽  
M. P. Plotnikov ◽  
M. A. Shevchenko
Keyword(s):  
Transmission Line ◽  
Experimental Determination ◽  
Transmission Lines ◽  
Power Transmission ◽  
Quantitative Relationship ◽  
Electrical Energy ◽  
Indirect Measurement ◽  
Power Line ◽  
Accurate Information

To determine the results of the transmission of electrical energy through the power line from the source to the consumer, it is necessary to have accurate information about the parameters of such line. Determining these parameters for operating lines with a minimum error is quite a laborious process. But if a researcher is interested only in voltages and currents at the end and at the beginning of a homogeneous section of a three-wire transmission line, then it is sufficient to use the theory of multipoles. In particular, the theory of eight-poles. The article presents the method of experimental determination of the longitudinal and transverse parameters of the studied transmission line. The study used the methods of natural experiment using an appropriate fleet of electrical devices, and methods of indirect measurement of the desired parameters. The experiment consists of six stages; on the basis of the obtained data, it becomes possible to determine the numerical values of the main parameters of the studied section of power transmission lines, with which it is possible to establish a quantitative relationship between the input and output characteristics of electrical energy. In addition, the described method, in principle, can be applied to the analysis of active eight-terminal networks of a similar design. This means that the proposed methodology can provide a comprehensive analysis of the studied object and will help to identify the parameters of an overhead power line at the construction stage or for its connection to the consumer. The article presents the experimental setup scheme, describes the experimental methods, and estimates the error of the calculation results.

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