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Predicting energy consumption using telecom and electricity Big Data

As part of electricity work LIRNEasia has made recommendations on the importance of DSM in Sri Lanka. Effective DSM is not possible without smart meters and that was an important part of the message, when we were invited by the Colombo Electricity Board (CEB) to share our research with their senior management.

So it was with great interest that I perused the research of one of the winning finalists  from a Big Data Challenge conducted by Telecom Italia (and partners) with data pertaining to the territories of Milan and of the Autonomous Province of Trento in Italy. The datasets covered telecommunications, energy, weather, public and private transport, social networks and events.

The researchers utilized smart meter data and behavioral data extracted from the Telecom Italia’s transaction generated data to predict peak daily energy consumption and also the average daily energy consumption for each line through the electrical grid of the Trentino Province.

More details HERE.

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