Donatella Manno

A pico hydropower plant is an energy harvesting system that allows energy production using the power of the water flowing in small watercourses, and in water distribution network. Axial Flow Flux Permanent Magnet Synchronous Generator (AFPMSG) are particularly suitable for this application, being efficient machines that achieve high power with small dimensions. This paper presents a parametrical study of several configurations and topologies of three-phase and single-phase AFPMSG, for pico hydropower application, to assess the most suitable dimensional characteristics for the most energy production using a safe voltage of 25 V. The AFPMSGs here considered has a simple single stator and rotor configuration, commercial-type permanent magnets, and concentric windings, to facilitate their cost-effective construction and the spread of their use also in developing countries. For each AFPMSG considered, the power output was calculated using 3-D modelling and Finite Element Analysis; besides, the different parameters and features that affect the power output were evaluated at different rotational speeds. The results achieving a power density up to 100 W/cm³, at 1000 rpm with energy produced to 1.7 kWh/day.

This paper proposes an innovative approach to classify the losses related to photovoltaic (PV) systems, through the use of thermographic non-destructive tests (TNDTs) supported by artificial intelligence techniques. Low electricity production in PV systems can be caused by an efficiency decrease in PV modules due to abnormal operating conditions such as failures or malfunctions. The most common performance decreases are due to the presence of dirt on the surface of the module, the impact of which depends on many parameters and conditions, and can be identified through the use of the TNDTs. The proposed approach allows one to automatically classify the thermographic images from the convolutional neural network (CNN) of the system, achieving an accuracy of 98% in tests that last a couple of minutes. This approach, compared to approaches in literature, offers numerous advantages, including speed of execution, speed of diagnosis, reduced costs, reduction in electricity production losses.