Advanced Prediction of Technical Losses on Transmission Lines in Real Time

Pavičić, Ivan; Ivanković, Igor; Župan, Alan; Rubesa, Renata; Rekic, Marko

doi:10.23919/smagrimet.2019.8720394

Cited by 8 publications

(10 citation statements)

References 6 publications

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“…There are several methods for calculating electricity losses from known electrical parameters in the system or estimating them on an experimental basis from measured data. The losses on the transmission line can be divided into Joule losses, losses due to the corona effect and losses from insulators (leakage) [10][11][12]. Ideally, for easier and faster calculation, the transmission line can be considered with symmetrical elements and can be presented as a single-phase element with concentrated parameters.…”

Section: Theoretical Background For Losess Calculation On Transmission Linesmentioning

confidence: 99%

“…The calculation of losses on transmission lines is presented as the difference between the sent and received power at two ends of the line. The calculation of the power in the transmission line is performed based on voltage and current measurements, and if the measurements are accurate, the calculation of losses is as well [7,9,10]. In general, existing estimation algorithms perform well when the measurements are accurate.…”

Section: Introductionmentioning

confidence: 99%

“…However, in practice, changing the electrical and physical parameters of the transmission lines and the measurement equipment may contribute to errors in loss calculation. The main reasons for this stem from, e.g., measurement transformer saturation, non-transmission line synchronized measurements, data conversion errors or communication device malfunctions [7,10].…”

Section: Introductionmentioning

confidence: 99%

“…The conducted analysis adopted the approach of predominantly using statistical processing of historical measured data for each 400 kV OHL to determine the total loss and the annual occurrence of loss [10]. All performed analyses were conducted on measured data from electricity meters (ADVANCE for energy recordings) and SCADA systems (for various power system parameter recordings), which both represent the main systems in the management process of the transmission network.…”

Section: Introductionmentioning

confidence: 99%

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Model for 400 kV Transmission Line Power Loss Assessment Using the PMU Measurements

Pavičić¹,

Holjevac

Ivanković³

et al. 2021

Energies

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This paper presents an advanced model for monitoring losses on a 400 kV over-head transmission line (OHL) that can be used for measured data verification and loss assessment. Technical losses are unavoidable physical effects of energy transmission and can be reduced to acceptable levels, with a major share of technical losses on transmission lines being Joule losses. However, at 400 kV voltage levels, the influence of the electrical corona discharge effect and current leakage can have significant impact on power loss. This is especially visible in poor weather conditions, such as the appearance of fog, rain and snow. Therefore, loss monitoring is incorporated into exiting business process to provide transmission system operators (TSO) with the measure of losses and the accurate characterization of measured data. This paper presents an advanced model for loss characterization and assessment that uses phasor measurement unit (PMU) measurements and combines them with end-customer measurements. PMU measurements from the algorithm of differential protection are used to detect differential currents and angles, and this paper proposes further usage of these data for determining the corona losses. The collected data are further processed and used to calculate the amount of corona losses and provide accurate loss assessment and estimation. In each step of the model, cross verification of the measured and calculated data is performed in order to finally provide more accurate loss assessment which is incorporated into the current data acquisition and monitoring systems.

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Section: Theoretical Background For Losess Calculation On Transmission Linesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Model for 400 kV Transmission Line Power Loss Assessment Using the PMU Measurements

Pavičić¹,

Holjevac

Ivanković³

et al. 2021

Energies

View full text Add to dashboard Cite

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“…It can also increase the reliability of the networks integrated with DERs by monitoring and forecasting the demand and generation. Such data is used for applications such as outage management [14], network volt‐var optimisation [15], optimal sizing and placement of custom power devices [16], line loss prediction [17], load forecasting [18], coordination of plug‐in electric vehicles [19], control and monitoring the network [20], and evaluating the DER hosting capacity [21].…”

Section: Introductionmentioning

confidence: 99%

Output power fluctuations of distributed photovoltaic systems across an isolated power system: insights from high‐resolution data

Moghbel

Glenister

Shoeb

et al. 2020

IET Renewable Power Generation

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Deployment of distributed energy resources has rapidly increased during the last few years. The uptake of renewable energy and especially photovoltaic (PV) systems are of interest to utilities in remote and rural areas where the use of conventional power generation is costly. Investigating the effects of such PV systems on isolated power systems at different penetration levels is a relevant research topic. This study reports on the data acquisition system deployed in a remote town in Western Australia and presents some of the findings and observations extracted from the captured real data. It highlights the maximum PV output variations and investigates the underlying factors. The impact of the PV systems on the voltage across the network is also analysed in this study. The studies show that inverter tripping events have led to larger PV output variations in shorter intervals while the cloud movements have contributed to variations in longer intervals.

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