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Big data in the Energy & Utilities sector

The Value of data in energy planning and cost reduction

How Smart Grid and Data Science support intelligent energy management


Lutech Energy & Utilities solutions

The value of data in energy planning and cost reduction, thanks to Lutech Sinergetica and Mediana's Big data and Advanced analytics solutions

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Energy efficiency, sustainability and reliability are the drivers that players in the Energy & Utilities market must follow in order to be competitive and improve the customer experience for their consumer and enterprise clients.

Smart Grid is the paradigm on which a new approach to energy use rests, satisfying the requirements of producers, retailers and consumers in a more efficient, rational and safe manner: integrated electricity grids and technologies, with reciprocal exchange of data and information, allow monitoring and distribution of electricity from all generation sources in order to meet the different electricity requirements of the connected users.

The big data generated by energy companies and services through smart metering solutions, network equipment and meteorological data, to cite just some of the sources, are essential in creating predictive models with which to perform energy planning, managing the energy demand for end users and reducing costs and carbon emissions. Data Science in the Energy field indeed supports precise forecasting of energy consumption, which influences energy production and therefore prices, and the use of renewable energy sources, given the role of the data from meteorological systems in the predictive analysis.

It is in dynamic energy management, thanks to solutions based on big data analysis and Artificial Intelligence and machine learning algorithms, that the value of energy data is primarily expressed: systems and solutions which manage the power load in an innovative manner, meeting the usage requirements of distributed energy resources, energy savings and temporary loads for industrial production. Solutions which incorporate smart devices for the end user, advanced communications and resources optimize the flows of energy between the generators and consumers. Applying big data analysis to load forecasts and renewable energy sources allows forecasting of performance and provision of intelligent recommendations for energy management.

Still from the point of view of managing costs and faults, for both providers and consumers, specific real-time monitoring solutions of energy consumption metrics allow the peak of activities and therefore demand to be defined, allowing the energy flow to be adapted to the current, concrete demand. Demand response management is an approach which is currently proving its effectiveness, improving end customer experience and satisfaction.

Customer retention in the Energy sector, as well as depending on a secure, reliable service, is also closely linked to transparency and visibility in the service supply process: real-time billing improves customer relations, reducing the chance for misunderstandings and potential disputes. Billing solutions for the energy market are ever-increasingly flexible and configurable, allowing providers to manage billing and payment for huge numbers of customers, and the customer to monitor the process right through to the transaction.

Technologies based on big data and AI play a crucial role in the challenges linked to the management and intelligent consumption of energy, the application of renewable energy sources and protection of the environment, including through other application methods, such as:

  • Machine learning algorithms to predict occasional operational faults and therefore reduce maintenance costs. Fault probability modeling provides significant support in the decision-making processes for energy providers.
  • Innovative data analysis and communication systems for “intelligent” supply interruption, able to foresee and detect potential black-outs from the smart metering system, in specific areas, taking into account various conditions, including the weather. Data analysis allows the application of predictive algorithms to calculate the future possibility of black-outs, as well as providing real-time information to customers on any such issues.
  • Such data intelligence solutions are able to improve the operational and functional aspects, first and foremost by optimizing the timeframes for each activity and by achieving KPIs to intervene with preventive maintenance of grids and systems.

Lutech mette in esecuzione la sua strategia nell’ambito della Business Unit Energy & Utilities investendo in un’offerta completa ed integrata per il settore, che pone le basi in una soluzione di Energy Trading and Risk Management (ETRM), e nelle soluzioni innovative di Lutech Sinergetica e Lutech Mediana

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