This paper analyzes the behavior of the Incremental Conductance (IC) maximum power point tracking algorithm used in photovoltaic modules. Three variants of the algorithm are compared under both simulations and real world tests with a DSP 1104 card control. The results obtained show that the variant whose simulated behavior is the best, actually is the worst in real world experiments, indicating that it is mandatory to test this kind of algorithms in real facilities. In this case, the facilities are placed in the laboratories of the Faculty of Engineering of Vitoria-Gasteiz (UPV/EHU, Spain), and the photovoltaic modules are on its roof.

This work is aimed at optimizing the wind turbine rotor speed setpoint algorithm. Several intelligent adjustment strategies have been investigated in order to improve a reward function that takes into account the power captured from the wind and the turbine speed error. After different approaches including Reinforcement Learning, the best results were obtained using a Particle Swarm Optimization (PSO)-based wind turbine speed setpoint algorithm. A reward improvement of up to 10.67% has been achieved using PSO compared to a constant approach and 0.48% compared to a conventional approach. We conclude that the pitch angle is the most adequate input variable for the turbine speed setpoint algorithm compared to others such as rotor speed, or rotor angular acceleration.

The objective of this paper is to describe an ongoing work that we are carrying out in the frame of an educational innovation project supported by the Education Advisory Service of the Vicerectorship for Teaching Quality and Innovation (University of the Basque Country, Spain). The project is driven by means of the subject of Industrial Informatics of the degree of Industrial Electronic Engineering and Automatics (University College of Engineering of Vitoria, Basque Country University, Spain). The design of the project is based on the development of a collaborative work distributed among all the students of the subject, grouped in several teams or working groups. The work developed by each of those groups is complementary, and when all these parts of work are finished, all of them will fit together. The conclusion reached until this moment through the continuous tracking of the students is that there is an increased and more active attendance. Besides, the results reached by the students in different evaluations have improved those reached by means of the traditional paradigm of learning

This paper presents the results of a proof-of-concept implementation of a platform for distributed, real-time fault-tolerant control of parallel single-phase inverters, integrated in modular uninterruptible power supplies (UPS) or Battery Energy Storage Systems (BESS). Each inverter controller runs a basic clock which schedules all the real-time control tasks, according to the time-triggered paradigm. The clocks in the different inverters are kept in synchronism with each other, by applying a distributed clock synchronization algorithm. The inverter controllers are connected through two serial buses. The first bus is a TDMA serial bus exclusively dedicated to the interchange of the short and frequent control variables needed to enforce load sharing between inverters. Each inverter applies to these variables a fault-tolerant variant of the averaging load sharing control method. The second bus is a CAN bus, with time stamping of messages, used to interchange the clock synchronization messages and the low bandwidth supervision and control variables.