Measurement of Weather Parameters via Transmission Line Monitoring System for Load Forecasting

Holmukhe, Rajesh M.; Chaudhari, Prajakta; Kulkarni, Purushottam; Deshpande, Kiran; Kulkarni, Prasannati

doi:10.1109/icetet.2010.155

Cited by 7 publications

(5 citation statements)

References 4 publications

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“…As shown in Table 2, the SAA based result is slightly inclusive of both MC and IA results. Since the aim of uncertainty based analysis is finding the worst-case results, as opposed to the punctual method in (6)(7)(8)(9)(10)(11)(12), the slight inclusiveness can be considered as one of the benefits of SAA. Table 3-5 shows the OTL tension, sag and cable length respectively.…”

Section: Resultsmentioning

confidence: 99%

“…The initial design has to consider load capability of the line including environmental factors. Those factors and measuring devices value are not absolute rather they vary between low and high extreme seasonally and change from place to place [7]. A Weakly designed OTLs, which does not consider the worst-case scenario, are unable to deliver power to the substations reliably.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Overhead Transmission Line Parameters with Uncertainty

Abebea¹,

Rao²,

Naik³

2017

IJEM

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Overhead Transmissions Lines (OTL) are outdoor systems, which can easily be affected by weather fluctuation. In the worst-case scenario, temperature variation, horizontal wind and vertical ice-loading make the value of sag, tension and conductor (cable) length to vary between low to high extremes. The temperature and cable length variations have an effect on the resistance of the OTL. This variation leads to a variable voltage drop, which is mostly considered with load variation. In order to calculate resultant loading, sag, tension, cable length and resistances of an OTL, an uncertainty model based on Standard Affine Arithmetic (SAA) is proposed and the result is compared with the probabilistic Monte Carlo (MC) and Interval Arithmetic (IA) approaches. Based on the test results, the SAA based algorithm gives slightly conservative bound than the IA and MC approaches.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis of Overhead Transmission Line Parameters with Uncertainty

Abebea¹,

Rao²,

Naik³

2017

IJEM

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“…Wind speed sensors, temperature sensors, wind direction sensors, humidity sensors, and rain sensors are mainly utilized to measure weather parameters. On the basis of these parameters, we can see how electricity demand fluctuates as weather changes and forecast electricity load . Because weather conditions change slightly in a certain area, only part of the supports need these types of sensors, and all of these sensors are attached to supports (position A).…”

Section: Architecturementioning

confidence: 99%

“…To guarantee the reliability of the grid, the transmission system needs capability of handling an emergency. Based upon the parameters of the transmission line monitoring, a load can be forecasted and the real‐time dynamic current capacity of overhead power lines can be evaluated . Typically, the dynamic rating provides a higher line capability of 98% of the time, and it also provides at least 15–30% additional capability for over 95% of the time .…”

Section: Introductionmentioning

confidence: 99%

Monitoring power transmission lines using a wireless sensor network

Lin

Zhu

Zeng

et al. 2014

Wireless Communications

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Power transmission is the bulk transfer of electrical energy from power plants to sub-stations. A wireless sensor network is a promising technology for transmission line monitoring due to its low cost, easy installation, large-scale coverage, and fault tolerance characteristics. A wireless sensor network is application-specific; therefore, we investigate the new features and requirements of the wireless sensor network used in transmission line monitoring. Then, we propose an efficient wireless sensor network framework, which includes a clustering algorithm to simplify network management and to balance the network's energy consumption and a hybrid media access control (MAC) (H-MAC) protocol to handle traffic variability. The framework takes advantage of the features of network topology and traffic pattern to optimize the protocols' performance on real time and energy efficiency. The results indicate that the H-MAC shows a significant improvement in the network's reliability, real-time performance, and energy efficiency, and the cluster hierarchy can balance the network's energy consumption. Furthermore, the cluster hierarchy also prolongs the network's lifetime.

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“…cable temperature) [4] and weather information (e.g. wind speed, temperature and lightning and pollution level) [7], [9]- [10] as well as anti-theft monitoring [11]. With increasing requirements for online monitoring, there is a need for providing reliable power supply to power the monitoring instruments.…”

mentioning

confidence: 99%