Medina , S.; Graells, M.; Guillén, G.; Espuña, A.; Puigjaner, L. Energy conversion and management Vol. 149, p. 722-737 DOI: 10.1016/j.enconman.2017.02.060 Data de publicació: 2017-10-01 Article en revista
Sustainable processes have recently awaked an increasing interest in the process systems engineering literature. In industry, this kind of problems inevitably required a multi-objective analysis to evaluate the environmental impact in addition to the economic performance. Bio-based processes have the potential to enhance the sustainability level of the energy sector. Nevertheless, such processes very often show variable conditions and present an uncertain behavior. The approaches presented for solving multi-objective problems under uncertainty have neglected the potential effects of different quality streams on the overall system. Here, it is presented an alternative approach, based on a State Task Network formulation, capable of optimizing under uncertain conditions, considering multiple selection criteria and accounting for the material quality effect. The resulting set of Pareto solutions are then assessed using the Elimination and Choice Expressing Reality-IV method, which identify the ones showing better overall performance considering the uncertain parameters space
In this paper, a novel procedure for fault detection and diagnosis in the direct current (DC) side of PV system, based on probabilistic neural network (PNN) classifier, is proposed. The suggested procedure consists of four main stages: (i) PV module parameters extraction, (ii) PV array simulation and experimental validation (iii) elaboration of a relevant database of both healthy and faulty operations, and (iv) network construction, training and testing. In the first stage, the unknown electrical parameters of the one diode model (ODM) are accurately identified using the best-so-far ABC algorithm. Then, based on these parameters the PV array is simulated and experimentally validated by using a PSIM™/Matlab™ co-simulation. Finally, efficient fault detection and diagnosis procedure based on PNN classifier is implemented. Four operating cases were tested in a grid connected PV system of 9.54 kWp: Healthy system, three modules short-circuited in one string, ten modules short-circuited in one string, and a string disconnected from the array. Moreover, the PNN method was compared, under real operating conditions, with the feed forward back-propagation Artificial Neural Network (ANN) classifiers method, for noiseless and noisy data to evaluate the suggested method’s accuracy and test its aptitude to support noisy data. The obtained results have demonstrated the high efficiency of the proposed method to detect and diagnose DC side anomalies for both noiseless and noisy data cases.
Improving the humidification of polymer electrolyte membrane fuel-cells (PEMFC) is essential to optimize its performance and stability. Therefore, this paper presents an experimentally validated model of a low temperature PEMFC cathode humidifier for control/observation design purposes. A multi-input/multi-output non-linear fourth order model is derived, based on the mass and heat dynamics of circulating air. In order to validate the proposed model and methodology, experimental results are provided. Finally, a non-linear control strategy based on second order sliding mode is designed and analyzed in order to show suitability and usefulness of the approach.
Kichou, S.; Abaslioglu, E.; Silvestre, S.; Nofuentes Garrido, Gustavo; Torres-Ramirez, M.; Chouder, A. Energy conversion and management Vol. 120, p. 109-119 DOI: 10.1016/j.enconman.2016.04.093 Data de publicació: 2016-07-15 Article en revista
The analysis of the degradation of tandem Micromorph thin-film photovoltaic (TFPV) modules and its impact on the output power of a PV array under outdoor long term exposure located in Jaen (Spain) is addressed in this work. Furthermore, the evolution of main solar cell model parameters is evaluated by means of parameters extraction techniques from monitored data of the PV system in real operation of work. The degradation rate and the stabilization period of micromorph TFPV modules are evaluated. The analysis of the degradation rate, together to results obtained for the evolution of each of the solar cell model parameters along the outdoor long-term exposure allow a better understanding of changes in performance of micromorph TFPV modules and the behavior of the output power of the PV generator.
Lighting systems are usually one of the largest electrical end-uses in underground metro stations. Taking into account that budget restrictions in publicly owned companies hinder energy efficiency retrofit projects that require high initial investments, affordable energy saving strategies are needed. This paper presents a low-cost approach for reducing lighting electricity use in underground stations, without affecting passengers' comfort or the metro operator's service. For this purpose, an adaptive lighting strategy of dimming the illuminance levels of artificial light sources has been developed. Dimming controls are based on the occupancy of the station, and the preventive maintenance and cleaning cycles of the luminaires. The stations' monthly occupancy patterns are defined through the k-means clustering technique. To illustrate its effectiveness, the method was applied to 115 underground stations of the Barcelona metro network. The results revealed overall electricity savings of 255.47 MW h on a biannual basis, which represents 36.22% of the stations' baseline lighting consumption. Individual energy savings were found to range from 25 to 87.5 MW h/year in the stations of the Barcelona metro network, depending on the number and profile of station users. The research findings will undoubtedly be useful for the future energy efficiency project plans of worldwide metro operators and managers of other underground spaces.
Carbó, A.; Oró, E.; Salom, J.; Canuto, M.; Macias, M.; Guitart, J. Energy conversion and management Vol. 112, p. 135-145 DOI: 10.1016/j.enconman.2016.01.003 Data de publicació: 2016-03-15 Article en revista
The rapid increase of data centre industry has stimulated the interest of both researchers and professionals in order to reduce energy consumption and carbon footprint of these unique infrastructures. The implementation of energy efficiency strategies and the use of renewables play an important role to reduce the overall data centre energy demand. Information Technology (IT) equipment produce vast amount of heat which must be removed and therefore waste heat recovery is a likely energy efficiency strategy to be studied in detail. To evaluate the potential of heat reuse a unique liquid cooled data centre test bench was designed and built. An extensive thermal characterization under different scenarios was performed. The effective liquid cooling capacity is affected by the inlet water temperature. The lower the inlet water temperature the higher the liquid cooling capacity; however, the outlet water temperature will be also low. Therefore, the requirements of the heat reuse application play an important role in the optimization of the cooling configuration. The experimental data was then used to validate a dynamic energy model developed in TRNSYS. This model is able to predict the behaviour of liquid cooling data centres and can be used to study the potential compatibility between large data centres with different heat reuse applications. The model also incorporates normalized power consumption profiles for heterogeneous workloads that have been derived from realistic IT loads.
This paper analyses, from a steady state point of view, the potential benefit of a Wind Power Plant (WPP) control strategy whose main objective is to maximise its total energy yield over its lifetime by taking into consideration that the wake effect within the WPP varies depending on the operation of each wind turbine. Unlike the conventional approach in which each wind turbine operation is optimised individually to maximise its own energy capture, the proposed control strategy aims to optimise the whole system by operating some wind turbines at sub-optimum points, so that the wake effect within the WPP is reduced and therefore the total power generation is maximised. The methodology used to assess the performance of both control approaches is presented and applied to two particular study cases. It contains a comprehensive wake model considering single, partial and multiple wake effects among turbines. The study also takes into account the Blade Element Momentum (BEM) theory to accurately compute both power and thrust coefficient of each wind turbine. The results suggest a good potential of the proposed concept, since an increase in the annual energy captured by the WPP from 1.86% up to 6.24% may be achieved (depending on the wind rose at the WPP location) by operating some specific wind turbines slightly away from their optimum point and reducing thus the wake effect. (C) 2015 Elsevier Ltd. All rights reserved.
Mancilla, F.; Dominguez, J.; de Prada, M.; Gomis-Bellmunt, O.; Singh, M.; Muljadi, E. Energy conversion and management Vol. 97, p. 315-322 DOI: 10.1016/j.enconman.2015.03.069 Data de publicació: 2015-06-01 Article en revista
The rapid increase of wind power penetration into power systems around the world has led transmission system operators to enforce stringent grid codes requiring novel functionalities from renewable energy-based power generation. For this reason, there exists a need to asses whether wind turbines (WTs) will comply with such functionalities to ensure power system stability. This paper demonstrates that Type-2 WTs may induce sub-synchronous resonance (SSR) events when connected to a series-compensated transmission line, and with proper control, they may also suppress such events. The paper presents a complete dynamic model tailored to study, via eigenanalysis, SSR events in the presence of Type-2 WTs, and a systematic procedure to design a power system stabilizer using only local and measurable signals. Results are validated through a case study based on the IEEE first benchmark model for SSR studies, as well as with transient computer simulations. (C) 2015 Elsevier Ltd. All rights reserved.
Fault tolerant control of five-phase brushless direct current (BLDC) machines is gaining more importance in high-safety applications such as offshore wind generators and automotive industries. In many applications, traditional controllers (such as PI controllers) are used to control the stator currents under faulty conditions. These controllers have good performance with dc signals. However, in the case of missing one or two of the phases, appropriate reference currents of these machines have oscillatory dynamics both in phase- and synchronous-reference frames. Non-constant nature of these reference values requires the implication of fast current controllers. In this paper, model predictive deadbeat controllers are proposed to control the stator currents of five-phase BLDC machines under normal and faulty conditions. Open circuit fault is considered for both one and two stator phases, and the behaviour of proposed controlling method is evaluated. This evaluation is generally focused on first, sensitivity of proposed controlling method and second, its speed in following reference current values under transient states. Proposed method is simulated and is verified experimentally on a five-phase BLDC drive. (C) 2015 Elsevier Ltd. All rights reserved.
Silvestre, S.; Aires, M.; Guasch, D.; Chouder, A.; Karatepe, E. Energy conversion and management Vol. 86, p. 241-249 DOI: 10.1016/j.enconman.2014.05.008 Data de publicació: 2014-10-01 Article en revista
In this work we present a new procedure for automatic fault detection in grid connected photovoltaic (PV) systems. This method is based on the evaluation of new current and voltage indicators. Thresholds for these indicators are defined taking into account the PV system configuration: number of PV modules included and series and parallel interconnection to form the array. The procedure to calculate the thresholds that allow the identification of the faults is described. A simulation study was carried out to verify the evaluation of current and voltage indicators and their corresponding thresholds for a set of PV systems with different sizes and different configurations of interconnection of PV modules. The developed method was experimentally validated and has demonstrated its effectiveness in the detection of main faults present in grid connected applications. The computational analysis has been reduced and the number of monitoring sensors minimized. The fault detection procedure can be integrated into the inverter without using simulation software or additional external hardware. (C) 2014 Elsevier Ltd. All rights reserved.
In this work we present a new procedure for automatic fault detection in grid connected photovoltaic (PV) systems. This method is based on the evaluation of new current and voltage indicators. Thresholds
for these indicators are defined taking into account the PV system configuration: number of PV modules included and series and parallel interconnection to form the array. The procedure to calculate the thresholds
that allow the identification of the faults is described. A simulation study was carried out to verify
the evaluation of current and voltage indicators and their corresponding thresholds for a set of PV systems
with different sizes and different configurations of interconnection of PV modules. The developed
method was experimentally validated and has demonstrated its effectiveness in the detection of main
faults present in grid connected applications. The computational analysis has been reduced and the number
of monitoring sensors minimized. The fault detection procedure can be integrated into the inverter
without using simulation software or additional external hardware.
This paper is focused on reducing the Switched Reluctance Machines (SRMs) control sampling frequency in order to save processor real time resources, while keeping the stability and also the performance, in terms of average torque and torque ripple. Reducing the CPU cost either by implementing the control algorithm in a less performing CPU or more importantly reducing the percentage of the CPU demand is an attractive goal, especially for the electrical vehicle industry from where the SRM used in this research has been designed for. Once low sampling periods are applied in the current loop, a strong degradation in the averaged torque and torque ripple arises. Such problem degenerates with the speed, becoming unbearable at high speeds and eventually making the control unstable. In this paper two solutions are proposed. The first one, which is just software feasible, consists on anticipating the voltage supply in order to tackle the noncoincident calculated turn on and off angles and the actual sampling instants. The second solution, which must be implemented at a very low hardware level, uses a basic function to allow the process to emulate continuous control and therefore independent of the sampling instants. Finally, experimental results on a 8/6 SRM illustrate the validity of the novel strategies in terms of average torque performance and torque ripple minimization. (C) 2014 Elsevier Ltd. All rights reserved.
In this paper, we present a new approach for detecting the faults in the photovoltaic systems based on the satellite image approach for estimating solar radiation data and DC output power calculations for detecting the failures. At first stage, the estimation of the hourly global horizontal solar radiation data has been evaluated by using the GISTEL (Gisement solaire par teledetection: Solar Radiation by Teledectection) model improved by the fuzzy logic technique. Thus, the results were compared with the ground solar radiation measurements. On the other hand, the comparison between the simulated and measured output DC powers was reached to find the nature of the faults in the PV array.; The results showed a good accuracy and the simple implementation of the proposed approach. The estimation of the hourly solar radiation presents an NRMSE <0.22 using GISTEL model improved by fuzzy logic comparing with the estimation without fuzzy logic with an NRMSE = 0.2885 for clear sky and NRMSE = 0.2852 comparing with NRMSE = 0.3121 for cloudy sky. (C) 2014 Elsevier Ltd. All rights reserved.
Interturn faults in permanent magnet synchronous motors (PMSMs) may develop fast into more severe faults such as coil-to-coil, phase-to-phase and phase-to-ground short circuits. These faults are very destructive and may irreversibly damage the PMSM. Therefore, it is highly desirable to develop suitable methods for the early detection of such faults. The effects of interturn faults are visible in both the stator currents and the zero-sequence voltage component (ZSVC) spectra. By designing appropriate fault diagnosis schemes based on the analysis of the harmonic content of such electric variables it is possible to detect short circuit faults in its early stage. However, the stator winding configuration of the PMSM deeply impacts the harmonic content of both spectra. This paper studies the effects of different stator winding configurations in both the stator currents and the ZSVC spectra of healthy and faulty machines. Results presented may help to develop fault diagnosis schemes based on the acquisition and further analysis of the stator currents and/or the ZSVC harmonic components.
With the increasing use of photovoltaic (PV) systems, the research studies to improve the efficiency of PV systems have gained greater interest in recent years, especially under non-uniform operating conditions. However, there is a little attention on fault diagnosis of PV arrays. This paper develops and demonstrates a method that can efficiently detect the number of open and short circuit faults and discriminate between them and partial shading conditions. This method is based on only the measurement of operating voltage of PV string and ambient temperature. In that manner, the proposed method takes into consideration of the minimum number of sensors to reduce the cost of the system, as one of the main purposes of this study. The simulation and experimental results are presented to demonstrate the effectiveness of the proposed method under both uniform and non-uniform irradiance conditions.
Pérez, G.; Rincon, L.; Vila, A.; Gonzalez, J.M.; Cabeza, L. F. Energy conversion and management Vol. 52, num. 4, p. 1861-1867 DOI: 10.1016/j.enconman.2010.11.008 Data de publicació: 2011-04 Article en revista