The use of wearable biomedical sensors for the continuous monitoring of physiological signals will facilitate the involvement of the patients in the prevention and management of chronic diseases. The fabrication of small biomedical sensors transmitting physiological data wirelessly is possible as a result of the tremendous advances in ultra-low power electronics and radio communications. However, the widespread adoption of these devices depends very much on their ability to operate for long periods of time without the need to frequently change, recharge or even use batteries. In this context, energy harvesting (EH) is the disruptive technology that can pave the road towards the massive utilisation of wireless wearable sensors for patient self-monitoring and daily healthcare. Radio-frequency (RF) transmissions from commercial telecommunication networks represent reliable ambient energy that can be harvested as they are ubiquitous in urban and suburban areas. The state-of-the-art in RF EH for wearable biomedical sensors specifically targeting the global system of mobile 900/1800 cellular and 700 MHz digital terrestrial television networks as ambient RF energy sources are showcased. Furthermore, guidelines for the choice of the number of stages for the RF energy harvester are presented, depending on the requirements from the embedded system to power supply, which is useful for other researchers that work in the same area. The present authors' recent advances towards the development of an efficient RF energy harvester and storing system are presented and thoroughly discussed too.

Standalone microgrids with photovoltaic (PV) solutions could be a promising solution for powering up off-grid communities. However, this type of application requires the use of energy storage systems (ESS) to manage the intermittency of PV production. The most commonly used ESSs are lithium-ion batteries (Li-ion), but this technology has a low lifespan, mostly caused by the imposed stress. To reduce the stress on Li-ion batteries and extend their lifespan, hybrid energy storage systems (HESS) began to emerge. Although the utilization of HESSs has demonstrated great potential to make up for the limitations of Li-ion batteries, a proper power management strategy is key to achieving the HESS objectives and ensuring a harmonized system operation. This paper proposes a novel power management strategy based on an artificial neural network for a standalone PV system with Li-ion batteries and super-capacitors (SC) HESS. A typical standalone PV system is used to demonstrate and validate the performance of the proposed power management strategy. To demonstrate its effectiveness, computational simulations with short and long duration were performed. The results show a minimization in Li-ion battery dynamic stress and peak current, leading to an increased lifespan of Li-ion batteries. Moreover, the proposed power management strategy increases the level of SC utilization in comparison with other well-established strategies in the literature.

In this article, an energy storage system (ESS) and its entire monitoring system are implemented. A new charging algorithm is developed based on the parameters of the battery pack in real time, extending the battery lifespan, improving the capacity usage and performance of the ESS. The proposed algorithm analyses, in real time, the difference between the desired voltage and the mean voltage of the cells, the temperature of the pack, and the difference of voltage between cells. Based on the obtained information, by trilinear interpolation, the algorithm calculates the charging current. The proposed charging algorithm also combines a balancing algorithm. This represents an innovation compared to the existing methods in the literature. The experimental results demonstrate that the proposed algorithm can successfully charge Li-ion battery packs with different capacities and life cycles, providing a better charging time and a much lower temperature increase.

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Home energy management systems operating with storage systems in markets with differentiated tariff, should identify ideal solutions for transacting stored energy with the electricity grid, minimizing customer costs. On the other hand, in scenarios of power outage due to severe weather events, the stored energy can be an indispensable asset to maintain the supply of the load during the event. However, the use of energy stored by management systems in arbitrage processes, for example, can lead to a situation of low state of charge at a time when the priority is the uninterrupted service of the load. Thus, this thesis presents an innovative Home Energy Storage Management System (HESMS) that incorporates the dynamic characteristic of the state of charge of the storage and probabilistic of the interaction between the electrical system and the local meteorological condition, to predict a possible power outage and prepare local storage as a temporary backup system in the event’s eminence, thus contributing to the increase the home energy resilience. By incorporating a proprietary methodology into the system to carry out local power outage prediction due to severe weather events, a spatial and temporal assertiveness is obtained that allows the load to be serviced, seeking the minimum intervention in the daily use of the storage system. It is a system developed to operate with different types of storage technology, integrated with different energy management systems and in different geographic regions. In order to validate the proposed methodology, case studies with real meteorological and power outage data are implemented. The results demonstrate that the GAER system contributes to increase the home energy resilience with minimal interference in the standard operation of the storage system.

A transição energética é um conceito que pode ser observado no setor elétrico de diferentes países, dentre os temas abordados estão as mudanças climáticas, as fontes de baixa emissão de carbono, a eletrificação e a digitalização. Tais fatores e o alto custo da energia elétrica explicam a mudança dirigida pela inovação tecnológica no setor elétrico brasileiro. De forma geral, a transição energética é vista como a descarbonização, descentralização e digitalização. Porém, os sistemas de distribuição de energia elétrica ainda são dimensionados seguindo normativas conservadoras e pouco atuais. Neste contexto, este trabalho avalia, por meio da simulação de um estudo de caso, as mudanças relacionadas à transição energética em um sistema de distribuição existente, avaliando diferentes temas e o impacto no projeto da rede de distribuição. Assim, propõe-se uma investigação com foco no conceito de recursos energéticos distribuídos, particularmente no que se refere à inserção de fontes de energia renováveis e armazenamento, tendo como premissa a qualidade da energia e do projeto elétrico dos sistemas de distribuição de energia elétrica. Os resultados obtidos mostraram que a simulação computacional é essencial para a compreensão da integração dos diferentes recursos energéticos descentralizados, e que a transição energética pode trazer benefícios, mesmo para redes que não foram dimensionadas com esta premissa. O desenvolvimento deste estudo destaca a importância de novas investigações sobre o tema da transição energética em sistemas de distribuição de energia elétrica para contribuir com sistemas mais confiáveis, robustos e eficientes.