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Real-time monitoring is a key tool for several automated features in distribution system. However, due to the limited number of real-time measurements, distribution system monitoring generally relies on load modeling procedures. This paper presents field results for a real-time monitoring tool that was implemented on a Brazilian distribution utility to provide load values for service restoration software. The implemented tool comprises two steps. The first step consists of preprocessing routines that provide the required information for a real-time load estimator that is executed in the second step. The field results provide evidence of the practical viability of the implemented real-time monitoring tool, demonstrating the tool overcomes some usual limitations of real-time load estimation procedures. More specifically, the implemented tool is able to handle multiple and different types of real-time measurements, treat real-time measurements on the feeder and not only in the head of the feeder, handle obviously bad data, and to satisfy the performance requirements on practically sized distribution systems. Besides proposing and confirming a real-time monitoring tool on a real distribution system, this paper shares valuable utility experience on providing new insights and the challenges faced for real-time monitoring projects. [ABSTRACT FROM PUBLISHER]

Estimating the amount of materials necessary for deploying electrical systems in buildings is a difficult task since these systems are complex and highly correlated with the design of other building systems. In Brazil, the usual method for estimating the consumption of electrical materials relies on constant rates per electrical points, incurring in large estimation errors. Furthermore, these rates can only be used in advanced project phases. This paper proposes a novel method for estimating the consumption of electrical materials, based on artificial neural networks (ANNs), by using information from early project stages. A dataset with project attributes was used to construct the ANN estimation models. In order to evaluate these new models, their estimates were compared to results from linear regression and constant rate models. Results showed that the ANN models have better performance when compared to other methods, supporting that ANNs are well suited for nonlinear and multidimensional problems. This investigation, therefore, supports that the method proposed could also be used by construction companies for estimating the consumption of other materials. [ABSTRACT FROM AUTHOR]

A new tomographic method was developed with the main goal of mapping the ionosphere in the region of Brazil. The ionospheric background was estimated based on ionosonde and radio-occultation measurements to overcome the lack of data provided by climatological models in low-latitude regions. A new method of performing iterations of the conventional multiplicative algebraic reconstruction technique (MART) was also used in order to avoid nonilluminated cells and improve the spatial resolution. The quality assessment using independent ionosonde data during two weeks in 2013 showed a better performance of the proposed method in comparison to the international reference ionosphere, providing improvements of 31% for the F-layer peak height ${h}_{m}$ and 24% for the ionospheric peak of electron density ${N}_{m}$. The tomographic technique was also evaluated in the estimation of the total electron content (TEC) and in the single-frequency precise point positioning (PPP). Improvements of 59% in TEC and 31% in the single-frequency PPP were obtained in comparison to the results derived from global ionospheric maps. In addition, a better daily description of the ionosphere was obtained using the proposed method, where it was possible to detect the peak height increasing associated with the prereversal enhancement of the vertical plasma drift that occurs near sunset hours. The results reveal that the modified form of the MART tomographic technique can be considered a useful tool for technical and scientific communities involved in space weather, spatial geodesy, and telecommunications. [ABSTRACT FROM AUTHOR]