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This article presents an isolated microgrid which combines two renewable power generators: a Hydraulic-Turbine-Generator (HTG) and a Wind-Turbine-Generator (WTG) with a Li-ion battery-energy-storage (BES). Depending on the generator(s) which supply active power, the microgrid can operate in three modes: Hydro-Only (HO), Wind-Hydro (WH) and Wind-Only (WO). In WH mode, the HTG supplies the difference between the power demanded by the consumers and the power supplied by the WTG. This net demanded power can be negative when the WTG power is greater than the load and this situation can lead to a microgrid collapse. This article shows by means of simulations how the BES is controlled to consume the WTG power excess guaranteeing the microgrid stability. Additionally, when the negative net demanded load is persistent the microgrid must transition from WH mode to WO mode, where only the WTG supplies active power, and this WH-WO transition is also simulated. In the simulations in WO mode, the BES is controlled to regulate the microgrid frequency. The needed controls to command the BES in WH and WO modes and in the WH-WO transition are also explained. The simulations show the effectiveness of using the BES since the microgrid stability and reliability is improved. [ABSTRACT FROM AUTHOR]

The combination of machine learning methods together with computational modeling and simulation of the cardiovascular system brings the possibility of obtaining very valuable information about new therapies or clinical devices through in-silico experiments. However, the application of machine learning methods demands access to large cohorts of patients. As an alternative to medical data acquisition and processing, which often requires some degree of manual intervention, the generation of virtual cohorts made of synthetic patients can be automated. However, the generation of a synthetic sample can still be computationally demanding to guarantee that it is clinically meaningful and that it reflects enough inter-patient variability. This paper addresses the problem of generating virtual patient cohorts of thoracic aorta geometries that can be used for in-silico trials. In particular, we focus on the problem of generating a cohort of patients that meet a particular clinical criterion, regardless the access to a reference sample of that phenotype. We formalize the problem of clinically-driven sampling and assess several sampling strategies with two goals, sampling efficiency, i.e., that the generated individuals actually belong to the target population, and that the statistical properties of the cohort can be controlled. Our results show that generative adversarial networks can produce reliable, clinically-driven cohorts of thoracic aortas with good efficiency. Moreover, non-linear predictors can serve as an efficient alternative to the sometimes expensive evaluation of anatomical or functional parameters of the organ of interest. [ABSTRACT FROM AUTHOR]

Modeling the cardiac conduction system is a challenging problem in the context of computational cardiac electrophysiology. Its ventricular section, the Purkinje system, is responsible for triggering tissue electrical activation at discrete terminal locations, which subsequently spreads throughout the ventricles. In this paper, we present an algorithm that is capable of estimating the location of the Purkinje system triggering points from a set of random measurements on tissue. We present the properties and the performance of the algorithm under controlled synthetic scenarios. Results show that the method is capable of locating most of the triggering points in scenarios with a fair ratio between terminals and measurements. When the ratio is low, the method can locate the terminals with major impact in the overall activation map. Mean absolute errors obtained indicate that solutions provided by the algorithm are useful to accurately simulate a complete patient ventricular activation map. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Wind–diesel power systems (WDPS) are isolated microgrids which combine diesel generators (DGs) with wind turbine generators (WTGs). The WDPS modelled in this study consists of one 275 kW‐WTG, one 300 kVA‐DG, a 240 V/390.625 Ah Ni–MH battery energy storage system (BESS) and consumer load. The WDPS working modes considered are: Wind Diesel (WD) mode where both the DG and WTG supply power and wind‐only (WO) mode where only the WTG produces active power. First, the dynamic models of the enumerated WDPS components are described. Then, WDPS control requirements in WD and WO modes are studied and a control system to govern the consumed/supplied BESS active power is presented. Finally, the WDPS is simulated and graphs of the system frequency and voltage, active power in each component and the battery current/voltage/state of charge are shown. The simulations cover: the WD mode, where it is shown that the BESS filters the load and WTG power variations and avoids a DG reverse power situation, the WD to WO mode transition where the BESS makes possible a bumpless transition and the WO mode where the BESS regulates the system frequency. Simulations demonstrate that the BESS increases the WDPS stability, reliability and security. [ABSTRACT FROM AUTHOR]

This study presents the modelling and dynamic simulation of a high penetration wind diesel power system (WDPS) consisting of a diesel generator (DG), a wind turbine generator (WTG), consumer load, dump load and a battery energy storage system (BESS). First the WDPS architecture and the models of the WDPS components are described. The WDPS is simulated in wind-only (WO) mode where the DG is not running and the WTG supply active power and in wind-diesel (WD) mode where both DG and WTG supply power. The simulation results are given showing graphs of the main electric variables in the WDPS (system frequency and voltage and active power in each component) and main battery variables (current, voltage and state of charge). The results in the WO mode show how the BESS, under the command of a proportional-integral-derivative (PID) controller, supplies/stores active power to regulate the isolated system frequency. The WD control enables the BESS to smooth the load and wind power variations, so that the isolated system power quality is improved. Also it is shown in the WD mode a peak shaving application where the control orders the BESS to supply active power temporarily to support system frequency in a DG overload situation. [ABSTRACT FROM AUTHOR]

This study presents the modelling and dynamic simulation of a high penetration wind diesel power system (WDPS) consisting of a diesel generator (DG), a wind turbine generator (WTG), consumer load, dump load and a battery energy storage system (BESS). First the WDPS architecture and the models of the WDPS components are described. The WDPS is simulated in wind‐only (WO) mode where the DG is not running and the WTG supply active power and in wind‐diesel (WD) mode where both DG and WTG supply power. The simulation results are given showing graphs of the main electric variables in the WDPS (system frequency and voltage and active power in each component) and main battery variables (current, voltage and state of charge). The results in the WO mode show how the BESS, under the command of a proportional‐integral‐derivative (PID) controller, supplies/stores active power to regulate the isolated system frequency. The WD control enables the BESS to smooth the load and wind power variations, so that the isolated system power quality is improved. Also it is shown in the WD mode a peak shaving application where the control orders the BESS to supply active power temporarily to support system frequency in a DG overload situation. [ABSTRACT FROM AUTHOR]

Atrial arrhythmias, and specifically atrial fibrillation (AF), induce rapid and irregular activation patterns that appear on the torso surface as abnormal P-waves in electrocardiograms and body surface potential maps (BSPM). In recent years both P-waves and the BSPM have been used to identify the mechanisms underlying AF, such as localizing ectopic foci or high-frequency rotors. However, the relationship between the activation of the different areas of the atria and the characteristics of the BSPM and P-wave signals are still far from being completely understood. In this work we developed a multi-scale framework, which combines a highly-detailed 3D atrial model and a torso model to study the relationship between atrial activation and surface signals in sinus rhythm. Using this multi scale model, it was revealed that the best places for recording P-waves are the frontal upper right and the frontal and rear left quadrants of the torso. Our results also suggest that only nine regions (of the twenty-one structures in which the atrial surface was divided) make a significant contribution to the BSPM and determine the main P-wave characteristics. [ABSTRACT FROM AUTHOR]

WDPS dynamic modeling and simulation allows short-term simulations to obtain detailed electrical variables transients, so that the WDPS stability and power quality can be tested. Wind diesel power systems (WDPS) are isolated microgrids which combine diesel generators (DGs) with wind turbine generators (WTGs). Additionally, the related topics of logistic simulation of WDPS or studies about the sizing of the WDPS different components are also included. [Extracted from the article]

Passive damping is the most adopted method to guarantee the stability of LCL-filter-based grid converters. The method is simple and, if the switching and sampling frequencies are sufficiently high, the damping losses are negligible. This letter proposes the tuning of different passive damping methods and an analytical estimation of the damping losses allowing the choice of the minimum resistor value resulting in a stable current control and not compromising the LCL-filter effectiveness. Stability, including variations in the grid inductance, is studied through root locus analysis in the z-plane. The analysis is validated both with simulation and with experiments. [ABSTRACT FROM AUTHOR]

Wind diesel isolated microgrids (WDIMs) combine wind turbine generators (WTGs) with diesel generators (DGs) to supply electricity to remote consumers. WDIMs are low-inertia isolated power systems where large system frequency and voltage variations occur. WDIM dynamic modeling allows short-term simulations to be performed and detailed electrical variable transients to be obtained so that the WDIM power quality and stability can be tested. This paper presents a literature review about WDIM dynamic simulation. The review classifies articles according to factors such as the different WDIM operation modes (diesel only, wind–diesel and wind only) simulated, the types of WTGs used in the WDIM (constant- and variable-speed types), or the use of different short-term energy storage technologies (batteries, ultracapacitors, flywheels) to improve the WDIM power quality, stability and reliability. Papers about the dynamic simulation of related isolated microgrids are also reviewed. Finally, as an example of WDIM dynamic simulation, a WDIM with one WTG, one DG, load and a discrete dump load (DL) is modeled and simulated. The WDIM response to variations of wind speed and load consumption is shown by graphs of the main electrical variables. The simulations show how the DL is used to improve the WDIM stability and reliability. [ABSTRACT FROM AUTHOR]

Isolated microgrids are microgrids which operate autonomously. This paper presents an isolated microgrid which combines a Hydraulic Turbine Generator (HTG) with a Wind Turbine Generator (WTG) to supply consumers forming a Wind Hydro Isolated Microgrid (WHIM). The WHIM includes a Dump Load (DL) to dissipate the active power excess. The WHIM has been modeled and its operation has been simulated in two modes: Wind-Hydro (WH), where both HTG and WTG supply power, and Wind-Only (WO) mode, where the WTG is the active power supplier and the HTG keeps connected to the grid with null power to generate the grid voltage. In WO, a fast frequency regulation is achieved by means of a controller which commands the DL to consume the WTG power excess. Additionally, the simulation of the mode transition from WO to WH, which is triggered by a system active power deficit in WO mode, is shown. A kick starting system designed to speed up the HTG power production improves the transient from WO to WH mode change. Finally, the simulations in WH mode show the interaction between the HTG and WTG. The two controls proposed have been proved effective and the simulations show a good WHIM dynamic performance. [ABSTRACT FROM AUTHOR]

Isolated microgrids are microgrids which operate autonomously. This paper presents an isolated microgrid which combines a Hydraulic Turbine Generator (HTG) with a Wind Turbine Generator (WTG) to supply consumers forming a Wind Hydro Isolated Microgrid (WHIM). The WHIM includes a Dump Load (DL) to dissipate the active power excess. The WHIM has been modeled and its operation has been simulated in two modes: Wind-Hydro (WH), where both HTG and WTG supply power, and Wind-Only (WO) mode, where the WTG is the active power supplier and the HTG keeps connected to the grid with null power to generate the grid voltage. In WO, a fast frequency regulation is achieved by means of a controller which commands the DL to consume the WTG power excess. Additionally, the simulation of the mode transition from WO to WH, which is triggered by a system active power deficit in WO mode, is shown. A kick starting system designed to speed up the HTG power production improves the transient from WO to WH mode change. Finally, the simulations in WH mode show the interaction between the HTG and WTG. The two controls proposed have been proved effective and the simulations show a good WHIM dynamic performance. [ABSTRACT FROM AUTHOR]

Reinforcement learning is one of the most promising machine learning techniques to get intelligent behaviors for embodied agents in simulations. The output of the classic Temporal Difference family of Reinforcement Learning algorithms adopts the form of a value function expressed as a numeric table or a function approximator. The learned behavior is then derived using a greedy policy with respect to this value function. Nevertheless, sometimes the learned policy does not meet expectations, and the task of authoring is difficult and unsafe because the modification of one value or parameter in the learned value function has unpredictable consequences in the space of the policies it represents. This invalidates direct manipulation of the learned value function as a method to modify the derived behaviors. In this paper, we propose the use of Inverse Reinforcement Learning to incorporate real behavior traces in the learning process to shape the learned behaviors, thus increasing their trustworthiness (in terms of conformance to reality). To do so, we adapt the Inverse Reinforcement Learning framework to the navigation problem domain. Specifically, we use Soft Q-learning, an algorithm based on the maximum causal entropy principle, with MARL-Ped (a Reinforcement Learning-based pedestrian simulator) to include information from trajectories of real pedestrians in the process of learning how to navigate inside a virtual 3D space that represents the real environment. A comparison with the behaviors learned using a Reinforcement Learning classic algorithm (Sarsa(λ)) shows that the Inverse Reinforcement Learning behaviors adjust significantly better to the real trajectories. [ABSTRACT FROM AUTHOR]

Wind Diesel Power Systems (WDPS) are isolated microgrids which combine Wind Turbine Generators (WTGs) with Diesel Generators (DGs). The WDPS modelled in this article is composed of a DG, a WTG, consumer load, Dump Load (DL) and a Flywheel Energy Storage System (FESS). In the Wind-Diesel (WD) mode both the DG and WTG supply power to the consumers. The WDPS is simulated in the WD mode in the case that the WTG produced power exceeds the load consumption. This WTG excess power case is simulated in the subcases of DL and FESS turned off, only-DL and only-FESS. Simulations for the DL and FESS-off case show that the WTG excess power leads to a continuous system frequency increase, so that the tripping of the WTG Circuit Breaker (CB) is required to guarantee the WDPS power supply continuity. Simulations for the only-DL/only-FESS cases show that commanding the DL/FESS to consume controlled power, so that the required DG power to balance the system active power is positive, enables the DE speed governor to regulate the system frequency. Furthermore, the frequency and voltage variations in the DL/FESS cases are moderate and there is no need to trip the WTG-CB, so that the WDPS reliability and power quality are greatly improved. Additionally, the only-FESS case obtains better WDPS relative stability than the only-DL case. [ABSTRACT FROM AUTHOR]