Control and Supervision Requirements for Floating Hybrid Generator Systems.

This work presents a series of devices that generate renewable energy from the marine environment which, in recent years, have aroused increasing interest. In particular, the main types of floating wind generators and marine current turbines are described. Over time, some of these floating generators have evolved in various hybrid modalities, integrating different generation devices into the same system, wind turbines, marine current turbines, wave energy converters, etc., with the objective of multiplying their generation capacity and optimizing the investment made in the floating system. However, this hybridization offers, in some cases, an opportunity to address the problem of controlling the structural stability of the system. Such stability enhancement has been considered a major challenge since the early days of floating wind turbine design. With this objective, in this work, a specific solution is proposed, consisting of a floating hybrid system composed of a wind generation subsystem and a generation subsystem with two marine current turbines. This proposal allows the development of an integrated control system which deals simultaneously with the structural stability of the system and the optimization of the generation capacity. Additionally, other requirements are also highlighted relating to the achievement of economic viability objectives, considering the reliability and availability of the system in the particularly aggressive marine environment, where maintenance operations are especially costly. In this sense, a model of intelligent integration of the tasks of supervision, diagnosis, and predictive maintenance is proposed.

Predictive Diagnosis Based on Predictor Symptoms for Isolated Photovoltaic Systems Using MPPT Charge Regulators.

In this work, new results are presented on the implementation of predictive diagnosis techniques on isolated photovoltaic (PV) systems and installations. The novelties introduced in this research focus on the additional advantages obtained from the point of view of predictive diagnosis of faults caused by partial shading in isolated PV installations using maximum power point tracking (MPPT) regulators. MPPT regulators are comparatively more appropriate than pulse width modulation (PWM) solar regulators in order to implement fault diagnosis systems. MPPT regulators have a physical separation between the electrical parameters belonging to the part of the solar panel with respect to the batteries part. Therefore, these electrical parameters can be used to obtain early predictive symptoms of the effects of partial shading with a greater level of observation and sensitivity. Additionally, modifications are proposed in the PV system assembly to obtain greater homogeneity of all the panels regarding the solar irradiance reception angle.

Efficacy and safety of intramuscular administration of allogeneic adipose tissue derived and expanded mesenchymal stromal cells in diabetic patients with critical limb ischemia with no possibility of revascularization: study protocol for a randomized controlled double-blind phase II clinical trial (The NOMA Trial).

BACKGROUND: Chronic lower limb ischemia develops earlier and more frequently in patients with type 2 diabetes mellitus. Diabetes remains the main cause of lower-extremity non-traumatic amputations. Current medical treatment, based on antiplatelet therapy and statins, has demonstrated deficient improvement of the disease. In recent years, research has shown that it is possible to improve tissue perfusion through therapeutic angiogenesis. Both in animal models and humans, it has been shown that cell therapy can induce therapeutic angiogenesis, making mesenchymal stromal cell-based therapy one of the most promising therapeutic alternatives. The aim of this study is to evaluate the feasibility, safety, and efficacy of cell therapy based on mesenchymal stromal cells derived from adipose tissue intramuscular administration to patients with type 2 diabetes mellitus with critical limb ischemia and without possibility of revascularization. METHODS: A multicenter, randomized double-blind, placebo-controlled trial has been designed. Ninety eligible patients will be randomly assigned at a ratio 1:1:1 to one of the following: control group (n = 30), low-cell dose treatment group (n = 30), and high-cell dose treatment group (n = 30). Treatment will be administered in a single-dose way and patients will be followed for 12 months. Primary outcome (safety) will be evaluated by measuring the rate of adverse events within the study period. Secondary outcomes (efficacy) will be measured by assessing clinical, analytical, and imaging-test parameters. Tertiary outcome (quality of life) will be evaluated with SF-12 and VascuQol-6 scales. DISCUSSION: Chronic lower limb ischemia has limited therapeutic options and constitutes a public health problem in both developed and underdeveloped countries. Given that the current treatment is not established in daily clinical practice, it is essential to provide evidence-based data that allow taking a step forward in its clinical development. Also, the multidisciplinary coordination exercise needed to develop this clinical trial protocol will undoubtfully be useful to conduct academic clinical trials in the field of cell therapy in the near future. TRIAL REGISTRATION: ClinicalTrials.gov NCT04466007 . Registered on January 07, 2020. All items from the World Health Organization Trial Registration Data Set are included within the body of the protocol.

Evaluating the Effect of Stimuli Color and Frequency on SSVEP.

Brain-computer interfaces (BCI) can extract information about the subject's intentions by registering and processing electroencephalographic (EEG) signals to generate actions on physical systems. Steady-state visual-evoked potentials (SSVEP) are produced when the subject stares at flashing visual stimuli. By means of spectral analysis and by measuring the signal-to-noise ratio (SNR) of its harmonic contents, the observed stimulus can be identified. Stimulus color matters, and some authors have proposed red because of its ability to capture attention, while others refuse it because it might induce epileptic seizures. Green has also been proposed and it is claimed that white may generate the best signals. Regarding frequency, middle frequencies are claimed to produce the best SNR, although high frequencies have not been thoroughly studied, and might be advantageous due to the lower spontaneous cerebral activity in this frequency band. Here, we show white, red, and green stimuli, at three frequencies: 5 (low), 12 (middle), and 30 (high) Hz to 42 subjects, and compare them in order to find which one can produce the best SNR. We aim to know if the response to white is as strong as the one to red, and also if the response to high frequency is as strong as the one triggered by lower frequencies. Attention has been measured with the Conner's Continuous Performance Task version 2 (CPT-II) task, in order to search for a potential relationship between attentional capacity and the SNR previously obtained. An analysis of variance (ANOVA) shows the best SNR with the middle frequency, followed by the low, and finally the high one. White gives as good an SNR as red at 12 Hz and so does green at 5 Hz, with no differences at 30 Hz. These results suggest that middle frequencies are preferable and that using the red color can be avoided. Correlation analysis also show a correlation between attention and the SNR at low frequency, so suggesting that for the low frequencies, more attentional capacity leads to better results.

Wave Energy Assessment at Valencia Gulf and Comparison of Energy Production of Most Suitable Wave Energy Converters.

Seaports' energy strategy should rely on the use of renewable energy. Presently, the share of renewable energy used by many of the ports worldwide is negligible. Some initiatives are in the process of implementation to produce some of the energy used by the Port of Valencia, one the largest ports in the Mediterranean Basin. Among these initiatives, a photovoltaic plant with an installed capacity of 5.5 MW is under a tendering process and the assessment studies for the deployment of three to five windmills are close to being finished. However, this is not enough to make it a "zero emissions port" as some of the energy demand would still be covered by fossil fuels. Therefore, we should consider clean alternative energy sources. This article analyses the wave energy resources in the surroundings of the Port of Valencia using a 7-year series of data obtained from numerical modelling (forecast). The spatial distribution of wave power is analysed using data from 3 SIMAR points at Valencia Bay and is compared to the data obtained by the Valencia Buoy I (removed in 2005). The obtained results are used to estimate the power matrices and the average energy output of two wave energy converters suitable to be integrated into the port's infrastructure. Finally, the wave energy converters' production is compared to the average amount of energy that is forecast to be obtained from other renewable sources such as solar and wind. Due to the nature of the Gulf's wave climate (mostly low waves), the main conclusion is that the energy obtainable from the waves in the Valencia Gulf will be in correlation with such climate. However, when dealing with great energy consumers every source of production is worthwhile and further research is needed to optimize the production of energy from renewable sources and its use in an industrial environment such as ports.

Marine NMEA 2000 Smart Sensors for Ship Batteries Supervision and Predictive Fault Diagnosis.

In this paper, an application for the management, supervision and failure forecast of a ship's energy storage system is developed through a National Marine Electronics Association (NMEA) 2000 smart sensor network. Here, the NMEA 2000 network sensor devices for the measurement and supervision of the parameters inherent to energy storage and energy supply are reviewed. The importance of energy storage systems in ships, the causes and models of battery aging, types of failures, and predictive diagnosis techniques for valve-regulated lead-acid (VRLA) batteries used for assisted and safe navigation are discussed. In ships, battery banks are installed in chambers that normally do not have temperature regulation and therefore are significantly conditioned by the outside temperature. A specific method based on the analysis of the time-series data of random and seasonal factors is proposed for the comparative trend analyses of both the battery internal temperature and the battery installation chamber temperature. The objective is to apply predictive fault diagnosis to detect any undesirable increase in battery temperature using prior indicators of heat dissipation process failure-to avoid the development of the most frequent and dangerous failure modes of VRLA batteries such as dry out and thermal runaway. It is concluded that these failure modes can be conveniently diagnosed by easily recognized patterns, obtained by performing comparative trend analyses to the variables measured onboard by NMEA sensors.

Sensor Buoy System for Monitoring Renewable Marine Energy Resources.

In this paper we present a multi-sensor floating system designed to monitor marine energy parameters, in order to sample wind, wave, and marine current energy resources. For this purpose, a set of dedicated sensors to measure the height and period of the waves, wind, and marine current intensity and direction have been selected and installed in the system. The floating device incorporates wind and marine current turbines for renewable energy self-consumption and to carry out complementary studies on the stability of such a system. The feasibility, safety, sensor communications, and buoy stability of the floating device have been successfully checked in real operating conditions.

A modular neural network scheme applied to fault diagnosis in electric power systems.

This work proposes a new method for fault diagnosis in electric power systems based on neural modules. With this method the diagnosis is performed by assigning a neural module for each type of component comprising the electric power system, whether it is a transmission line, bus or transformer. The neural modules for buses and transformers comprise two diagnostic levels which take into consideration the logic states of switches and relays, both internal and back-up, with the exception of the neural module for transmission lines which also has a third diagnostic level which takes into account the oscillograms of fault voltages and currents as well as the frequency spectrums of these oscillograms, in order to verify if the transmission line had in fact been subjected to a fault. One important advantage of the diagnostic system proposed is that its implementation does not require the use of a network configurator for the system; it does not depend on the size of the power network nor does it require retraining of the neural modules if the power network increases in size, making its application possible to only one component, a specific area, or the whole context of the power system.