Big data analytics in power distribution systems

Abstract

Penetration of advanced sensor systems such as advanced metering infrastructure (AMI), high-frequency overhead and underground current and voltage sensors have been increasing significantly in power distribution systems over the past few years. According to U.S. energy information administration (EIA), the aggregated AMI installation experienced a 17 times increase from 2007 to 2012. The AMI usually collects electricity usage data every 15 minute, instead of once a month. This is a 3,000 fold increase in the amount of data utilities would have processed in the past. It is estimated that the electricity usage data collected through AMI in the U.S. amount to well above 100 terabytes in 2012. To unleash full value of the complex data sets, innovative big data algorithms need to be developed to transform the way we operate and plan for the distribution system. This paper not only proposes promising applications but also provides an in-depth discussion of technical and regulatory challenges and risks of big data analytics in power distribution systems. In addition, a flexible system architecture design is proposed to handle heterogeneous big data analysis workloads.

Power systems data fusion based on belief propagation

“…Computing the integral in (8) is not feasible, in general, for continuous distribution and it can become numerically intractable for discrete distributions. By further assuming that the measurement factions and the state variables in (1) represent Gaussian densities, the factorization in (5) can be expressed as follows:…”

“…The electrical grid is going through a significant transformation towards a more distributed architecture for demand-supply balancing, due to a higher penetration of distributed sources of renewable generation, storage and demand flexibility. Internetof-Things (IOT) technologies are an integral part of the transformation, with energy utilities availing of more and more highly-distributed intelligent devices which produce an everincreasing amount of heterogeneous data significantly different in terms of format, resolution and quality [1], [2].…”

Construction of equivalents of large equations systems of electrical network based on matrix annulators

“…The solution of complete systems of equations covering all the nodes and connections of large power systems, even with simplified models, because of the lack of reliable information on all elements of the network, poses a serious problem, which is complicated by the need to accumulate and store large amounts of information [1] and the corresponding increase in the requirements for the speed of computers [2].…”

Computação em nuvem no contexto das <i>smart grids</i>: uma aplicação para auxílio à localização de faltas em sistemas de distribuição

“…Desenvolver uma infraestrutura de computação em nuvem capaz de fornecer capacidade computacional de grande escala em tempo hábil para suprir as necessidades de armazenamento, e processamento de dados, requeridas pelas smart grids não é uma tarefa trivial, tendo sido objeto de estudo de várias pesquisas [6], [49], [51], [55], [60], [61], [74], [76], [77], [83], [86], [141], [162], [175]- [192], sendo as principais apresentadas a seguir.…”

“…A maioria das propostas de infraestruturas destinadas a processamento paralelo de dados massivos (em [51], [76], [77], [83], [86], [162], [176], [180], [182], [ Com base nas informações obtidas desses trabalhos foi proposta uma arquitetura de computação em nuvem para ser utilizada pelos sistemas de distribuição inteligentes.…”