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In spite of the strong believes, the progress and maturity in the deployment of smart grids is very slow. The main reasons behind the slow pace are not due to the technical aspects but, perhaps, as a result of an inappropriate business model, not adequately centered to the customers. Nature, with ability to survive and resist, is a splendid example of competitive life. Mathematical models show that natural complex systems are the replication of simple structures. Exploring this approach, smart grids can be seen as an aggregation of mini and micro grids, with the smart user as fundamental stone. The technical aggregation can be paired with a new business model, based on correspondent enterprises, devoted to operation and maintenance. This framework can open new opportunities, favoring innovations, increasing resilience, pushing toward more responsible energy usage behavior while giving tangible economic and social benefits to the customers.

Due to the increasing amount of energy consumption and CO2 emissions, Building Automation Systems have been developed in order to increase energy performance in buildings and guarantee indoor comfort at the same time. However, along with the development of the hardware itself, the need to develop also suitable control systems and methods for improving the management of smart buildings, is arising. In this framework, fuzzy logic may be a valuable tool for developing suitable control systems. In this paper, fuzzy logic has been used in order to optimize comfort features and energy demand in an office. Starting from the model defined in a previous work, the aim of the paper is to simulate different configurations of the room and compare the results in order to evaluate the impact of room variations (window geometry, glass properties and wall reflectance) on the fuzzy control system. Given the same solar radiation inputs, it was noticed that different room configurations require a diversified management of the shading systems and artificial lighting control in order to achieve a good balance between comfort and energy consumption.

This paper presents the control strategies by Proportional-Integral (P-I) and Fuzzy Logic (FL) for a DC-DC boost power converter for high output voltage configuration. Standard DC-DC converters are traditionally used for high voltage direct current (HVDC) power transmission systems. But, lack its performances in terms of efficiency, reduced transfer gain and increased cost with sensor units. Moreover, the internal self-parasitic components reduce the output voltage and efficiency of classical high voltage converters (HVC). This investigation focused on extra high-voltage (EHV) DC-DC boost power converter with inbuilt voltage-lift technique and overcome the aforementioned deficiencies. Further, the control strategy is adapted based on proportional-integral (P-I) and fuzzy logic, closed-loop controller to regulate the outputs and ensure the performances. Complete hardware prototype of EHV converter is realized and experimental tasks are set out with digital signal processor (DSP) TMS320F2812 under different perturbation conditions. Observed set of results is provided and shown good conformity with developed hypothetical predictions.

This paper describes the design and realization of a smart electronic system, based on a Wireless Sensor Network, for wide-area monitoring of availability level and rapid changes of the water presence in the monitored soil in order to guarantee flood prediction, water savings in the optimized farmland irrigation, waste reduction and optimal use of water resources where its availability is low. The designed sensor node, by means of the different embedded sensors, is capable of detecting environmental parameters, the solar radiation level and soil temperature and moisture (i.e. water volume content) values. The sensors communicate with a central processing unit located on board, used both as data processing unit and as Wi-Fi transceiver to receive/transmit the sensors data. The user near a sensor node, by a tablet or smartphone with an appropriate app, can collect information provided from sensors and share them with all users who use the same app on the Cloud, through peer to peer Wi-Fi or other internet connection.