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

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.

Bulk FDTD Simulation of Distributed Corona Effects and Overvoltage Profiles for HSIL Transmission Line Design

Power system load growth and transmission corridor constraints are driving industry activity in the area of high surge impedance loading (HSIL). Examples include compact structure design and uprating existing transmission lines. Recent research relating electric field uniformity to transmission line capacity and critical flashover voltage underscored the need for better overvoltage data to quantify insulation margins for HSIL design. To that end, this work extends the finite difference time domain (FDTD) method with distributed corona losses to transmission lines with bundled conductors. The model was adapted for practical use in high-volume statistical transient simulation and applied to an example 500 kV line. Transients included line energization and trapped charge reclosing. Overvoltage profiles and statistical distributions were generated from 9500 simulations obtained by random breaker close timing and variation in line length and altitude. Distributed corona losses reduced 98th percentile line-to-ground switching overvoltages by 4%–14% of nominal. The estimated line-to-ground switching surge flashover probability was 54%–80% lower with corona loss. Corona had less impact on line-to-line overvoltages, but the effects were still notable. Results highlight the importance of considering detailed overvoltage profiles and accounting for corona loss attenuation when seeking to carefully quantify insulation design margins.

Corona Loss Minimization on High Voltage Transmission Line Network using Bundled Conductors.

Electrical power generated and transmitted at a long distance away from the power stations is usually affected by inherent transmission line losses. The Ohmic and Corona losses which are predominantly common in power transmission lines are considered in this paper. These two losses are mathematically modeled with and without embedded bundled conductors. The resultant model which is a non-linear multivariable unconstrained optimized equation is minimized using the Hessian matrix determinant method for stability test purposes. The results obtained show that corona losses are minimized with embedded bundled conductors at a very low current value with large spacing distance between the bundled conductors. The decrease in the corona loss which is a consequence of spacing adjustment of the 2, 3, and 4 strands of bundled conductors was plotted using MATLAB 7.14. The plots obtained are in conformity with the inverse relation between corona loss and conductor spacing.

Forecast of Corona Losses using Grey Wolves on Variant Load Condition

Depending upon material science law and guidelines, the factors of overhead lines in network, electric and meteorological data recorded the essential relationships with the corona losses and the states of climate are normally spotted. Corona losses occurred to be characterized just by weighting components for particular states of climate of average twelve Bulgarian territories showing components of complete transmission lattice. A determining unit imply on a measurable procedure worried on an hourly premise corona shortfall is inspected and proposed to have the option to decrease the lopsided characteristics costs. This casing work includes a proposed model of learning for limiting the corona losses. The deficiencies of suggested approach lessen in each situation since it speaks to an effective learning adaptation and at the hour of testing it productively figure heat/temperature giving an extraordinary effect to fundamentally losses decrease. The fundamental purpose for the improvement of learning approach is that the learning approach sums up the information however expectation approach utilizes dynamic choice and disregards past information execution.

Dampak Korona pada SUTET 500 kV Terhadap Radio Interference

Corona can occur in SUTET because SUTET carries a high enough electric current and voltage, this causes excessive electrical pressure that is not proportional to the breakdown strength of the air around the conductor so that there will be a phenomenon where the electric field will collide with free electrons in the air and will form ionisations in the form of new ions and electrons. This process will continue as long as there are currents and voltages on the extra-high-voltage network. This certainly will affect the surrounding environment through which SUTET is included, among others, interference with radio waves (Radio Interference). The addition of the number of sub conductors is considered more effective in reducing corona losses and radio interference in each wicket than increasing the distance of the conductor to the ground. The impact of corona on a 500 kV double-channel SUTET on radio interference in the Greater Jakarta area is still within reasonable limits because it is still below the IEEE standard of 40 dB.

Analisa Pengaruh Luas Penampang Penghantar dan Cuaca Terhadap Rugi Daya Akibat Korona Pada SUTT 150 kV (Studi Kasus: Gardu Induk Bangkalan – Gardu Induk Sampang)

PT. PLN (PERSERO) as a state-owned company responsible in the electricity sector is required to improve the quality of electricity transmission. In the transmission of electrical power to consumers will be got losses of power. Raising the voltage is an alternative to this problem but it creates new problems because the higher the voltage has increased the corona will occur. The impact of the corona in addition to damaging equipment, noise, and disturbing radio waves, the corona also causes power losses that are proportional to the length of the transmission line. This study uses a quantitative method, by calculating the corona power losses by comparing 4 different cross-sectional areas of the conductor and 4 different air temperatures. The results of this study found that the smaller the cross-sectional area of the conductor the power losses due to corona are smaller, conversely the greater the cross-sectional area the greater the power losses. At the smallest cross-sectional area of 282.6 mm2, the power losses that occurred were 2.013% and at the largest cross-sectional area of 378.7 mm2, the power losses were 5.251%. While the influence of air temperature, the lowest corona losses occur at 29 0C which are 1,223,886 kW and the biggest occur at 24 0C which are 1,373,419 kW, so the higher the air temperature the smaller the corona losses, conversely the lower the air temperature than the higher the corona losses that occur.