Essential for technological and economic progress, electrical energy requires well-founded solutions and strategies for efficient and sustainable management. Existing consumer units, lacking
modern technological resources, need gradual alternatives to optimize energy use, making the
most of pre-established resources. In this context, retrofit offers an effective update for these
infrastructures. Systematic models and strategies can standardize and ensure the replication of
these solutions in different contexts through abstractions known as frameworks. However, there
is a lack of frameworks to enable the implementation of systematic retrofit strategies for energy
management, especially in the low-voltage energy sector. To fill this gap, this thesis presents
the SmartLVEnergy framework, proposed to guide the design of innovative retrofit strategies
to modernize legacy low-voltage installations with IoT, AIoT, and distributed computing solutions, optimizing energy management with distributed technological resources and advanced
predictive capabilities. The experiments conducted in this thesis are presented in the format of
aggregated scientific articles, which contributed to the conception of the SmartLVEnergy framework. As a result, it was possible to implement energy management tools in existing building
and industrial scenarios in a systematic manner, based on the premises of the proposed framework. The main focus was the analysis and prediction of the energy demand of the installations
and their respective circuits, allowing to anticipate and mitigate demand overrun events of the
consumer units, following the guidelines of the Brazilian National Electric Energy Agency. The
strategies conceived included the development, use, and integration of sensing, communication,
and computing resources, distributed locally, in the cloud, and at the edge, according to the principles of the SmartLVEnergy framework, maximizing the use of existing resources according
to the specific needs of each installation. The proposed framework is flexible and allows the integration, expandability, and interoperability of technological solutions across legacy systems,
enabling operations according to the peculiarities and resources of each pre-existing context.
This versatility confirms the relevance of this work as a robust and sustainable proposal to promote energy efficiency today, especially in legacy low-voltage systems.
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