Open circuit fault diagnosis for a five-level neutral point clamped inverter in a grid-connected photovoltaic system with hybrid energy storage system

Introduction. Recently, the number of high and medium voltage applications has increased dramatically. The connection between these different applications requires series-parallel combinations of power semiconductors. Multilevel converter topologies provide major advantages to these applications. In this paper, a grid-connected photovoltaic system with a hybrid energy storage system using a five-level neutral point clamped inverter is studied. Although the multilevel inverter has many advantages over the two-level inverter, it has a high probability of experiencing an open circuit fault. In this context, the five-level inverter has 24 controllable switches, one of which may experience an open circuit fault at any time. Therefore, it plays an important part in the reliability and robustness of the whole system. The novelty of this paper presents an approach to accurately detect the open circuit fault in all insulated gate bipolar transistors of a five-level neutral point clamped inverter in a photovoltaic power generation application with a hybrid energy storage system. Purpose. Before using fault-tolerant control to ensure service continuity, fault diagnosis techniques must first be used, which are the crucial phase of reliability. Methods. A detection method based on the maximum and minimum error values is proposed. These errors are calculated using the expected and measured line-to-line pole voltages. Results. The open circuit fault detection method is implemented using MATLAB/Simulink. Simulation results showed the accuracy of detecting the open circuit fault in all insulated gate bipolar transistors in a short time. Moreover, this method is adaptable to several applications and is also robust to transient regimes imposed by solar irradiation and load variations.Вступ. Останнім часом різко зросла кількість застосувань високої та середньої напруги. З’єднання між цими різними використаннями вимагає послідовно-паралельних комбінацій силових напівпровідників. Топології багаторівневих перетворювачів надають цим додаткам великі переваги. У цій статті вивчається фотоелектрична система, підключена до мережі, з гібридною системою зберігання енергії, яка використовує п’ятирівневий інвертор із фіксуванням нейтральної точки. Хоча багаторівневий інвертор має багато переваг, порівняно з дворівневим інвертором, він має високу ймовірність виникнення обриву кола. У зв’язку з цим п’ятирівневий інвертор має 24 керовані перемикачі, один з яких будь-якої миті може зіткнутися з обривом кола. Таким чином, він відіграє важливу роль у надійності та стійкості всієї системи. Новизна цієї статті являє собою підхід до точного виявлення несправності розімкнутого кола у всіх біполярних транзисторах із ізольованим затвором п’ятирівневого інвертора з фіксуванням нейтральної точки у фотоелектричних додатках для вироблення електроенергії з гібридною системою зберігання енергії. Мета. Перш ніж використовувати відмовостійкий контроль для забезпечення безперервності обслуговування, необхідно спочатку використовувати методи діагностики несправностей, які є вирішальним етапом надійності. Методи. Запропоновано метод виявлення, заснований на максимальному та мінімальному значеннях помилок. Ці помилки розраховуються з використанням очікуваних та виміряних міжфазних напруг на полюсах. Результати. Метод виявлення обриву кола реалізовано з використанням MATLAB/Simulink. Результати моделювання показали точність виявлення обриву кола у всіх біполярних транзисторах із ізольованим затвором за короткий час. Більш того, цей метод адаптується до кількох застосувань, а також стійкий до перехідних режимів, викликаних сонячним випромінюванням та змінами навантаження

Variance Reduction with Array-RQMC for Tau-Leaping Simulation of Stochastic Biological and Chemical Reaction Networks

We explore the use of Array-RQMC, a randomized quasi-Monte Carlo method designed for the simulation of Markov chains, to reduce the variance when simulating stochastic biological or chemical reaction networks with $\tau$-leaping. The task is to estimate the expectation of a function of molecule copy numbers at a given future time $T$ by the sample average over $n$ sample paths, and the goal is to reduce the variance of this sample-average estimator. We find that when the method is properly applied, variance reductions by factors in the thousands can be obtained. These factors are much larger than those observed previously by other authors who tried RQMC methods for the same examples. Array-RQMC simulates an array of realizations of the Markov chain and requires a sorting function to reorder these chains according to their states, after each step. The choice of sorting function is a key ingredient for the efficiency of the method, although in our experiments, Array-RQMC was never worse than ordinary Monte Carlo, regardless of the sorting method. The expected number of reactions of each type per step also has an impact on the efficiency gain.ERDF, ESF, EXP. 2019/00432, Canada Research Chair, IVADO Research Grant, NSERC Discovery Grant RGPIN-110050

Monte Carlo and Quasi-Monte Carlo Density Estimation via Conditioning

Estimating the unknown density from which a given independent sample originates is more difficult than estimating the mean, in the sense that for the best popular non-parametric density estimators, the mean integrated square error converges more slowly than at the canonical rate of $\mathcal{O}(1/n)$. When the sample is generated from a simulation model and we have control over how this is done, we can do better. We examine an approach in which conditional Monte Carlo yields, under certain conditions, a random conditional density which is an unbiased estimator of the true density at any point. By averaging independent replications, we obtain a density estimator that converges at a faster rate than the usual ones. Moreover, combining this new type of estimator with randomized quasi-Monte Carlo to generate the samples typically brings a larger improvement on the error and convergence rate than for the usual estimators, because the new estimator is smoother as a function of the underlying uniform random numbers.IVADO Research Grant, NSERC-Canada Discorvery Grant, Canada Research Chair, Inria International Chair, ERDF, ESF, EXP. 2019/0043

STATISTICAL ANALYSIS OF BREAKDOWN IN TRANSFORMER OIL.

The statistics of breakdown for transformer oil in a uniform field gap is an important design consideration. The theoretical probability distribution which closely fits the experimental data under 60 Hz ac voltage, positive and negative lightning impulses and positive and negative switching surges is evaluated and a statistical distribution is suggested

Investigation on SVM-Backstepping sensorless control of five-phase open-end winding induction motor based on model reference adaptive system and parameter estimation

This paper deals with a new control technique applied to five-phase induction motor under open-end stator winding (FPIM-OESW) topology using the backstepping nonlinear control. The main objective is to improve the dynamics of this kind of machine, which is intended to be used in high power industrial application, where the maintenance is difficult and the fault tolerant is needed to ensure the continuous motor operating mode with minimized number of interruption. This control technique is combined with the Space Vector Pulse Width Modulation (SVPWM) to maintain a fixed switching frequency. In addition, the Model Reference Adaptive System (MRAS) concept is used for the estimation of the load torque, the rotor flux and the rotor speed to overcome the main drawbacks presented with the previous sensorless systems concepts. However, the great sensitivity to the changes of the motor internal parameters and it operating instability problems, especially in low-speed operating region, that causes an estimation error of the rotor speed, is the most disadvantage of the MRAS technique. Therefore, to solve this problem, an estimation method of the motor internal parameters such as the rotor resistance, the stator resistance and the magnetizing inductance, is proposed in this paper. Where, the main aim is to improve furthermore the control performance, to reduce the computational complexity and to minimize the rotor speed estimation error. The obtained simulation results confirm the enhanced performance and the clear efficacy of the proposed control technique under a variety of cases of different operating conditions. - 2019 Karabuk UniversityScopu

Multiple exciton generation in nano-crystals revisited: Consistent calculation of the yield based on pump-probe spectroscopy

Multiple exciton generation (MEG) is a process in which more than one exciton is generated upon the absorption of a high energy photon, typically higher than two times the band gap, in semiconductor nanocrystals. It can be observed experimentally using time resolved spectroscopy such as the transient absorption measurements. Quantification of the MEG yield is usu- ally done by assuming that the bi-exciton signal is twice the signal from a single exciton. Herein we show that this assumption is not always justified and may lead to significant errors in the estimated MEG yields. We develop a methodology to determine proper scaling factors to the signals from the transient absorption experiments. Using the methodology we find modest MEG yields in lead chalcogenide nanocrystals including the nanorods

Contribution to Collaborative Innovation Studies: Cases of SMES Moroccan Automotive Suppliers and their Client

The aim of this work is to study how collaborative innovation succeeds between a large enterprise and SME relationship (Manufacturer-Equipment) in automotive supply chain using case studies. Data were collected from semi-structured interviews with managers in nine firms. The main intention was to understand how these companies engaged collaborative innovation and what the factors were to make it successful. The study adopted a qualitative approach in the study of these factors. The results show the importance of the internal capacities of SMEs (management style, innovation capacities, knowledge management ...) in the success and valorization of such a project. The study provides important lessons on how these relationships can impact the way businesses operate and how they innovate