• Energy Research
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In this paper, a new learning tool is proposed to train professional figures, such as entrepreneurs, engineers, and technicians, who need to improve their skills in the field of Internet of Energy. The proposed tool aims to cover the lack of experimental knowledge on new energy systems and to layer proper skills, which are useful to deal with challenges required by smart energy management in the new complex distributed configuration of the electric power systems, characterized by demand response services. This tool is based on a small-scale laboratory demonstrator, representative of a smart rural house, equipped with a measurement and control system. This demonstrator can be remotely accessed, through web server applications based on a low cost single-board computer. Trainers can have direct experience on the main concepts related to smart grids, renewable energy sources, electrochemical storage systems, and electric vehicles, through the use of the proposed tool managed by the web software interface.

The paper presents analytical formulas for computation in the time domain of electromagnetic (EM) fields generated by tortuous cloud-to-cloud (CC) lightning channels over a perfectly conducting ground. For the first time, the study was not limited to a horizontal lightning path but was extended to take into account the natural, tortuous geometry of the lightning channel. After the calculation of the step response, a convolution integration was applied for the computation of the fields generated by an arbitrary current source. The produced electric and magnetic fields were then compared with the fields generated by a horizontal channel. The method can be of primary importance to evaluating the hazards for electric and electronic systems of flying aircraft, estimating the voltages induced on overhead transmission lines by CC lightning, and, in general, evaluating the induced effects on sensitive electric and electronic components. Moreover, it may represent a simple, robust, and time-saving tool for estimating important physical parameters that characterize lightning phenomena.