• Energy Research
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Editorial Complex Optimization and Simulation in Power Systems

Abstract With the rapid advancement in wearable electronics, energy harvesting devices based on triboelectric nanogenerators (TENGs) have been intensively investigated for providing sustainable power supply for them. However, the fabrication of wearable TENGs still remains great challenges, such as flexibility, breathability and washability. Here, a route to develop a new kind of woven-structured triboelectric nanogenerator (WS-TENG) with a facile, low-cost, and scalable electrospinning technique is reported. The WS-TENG is fabricated with commercial stainless-steel yarns wrapped by electrospun polyamide 66 nanofiber and poly(vinylidenefluoride-co-trifluoroethylene) nanofiber, respectively. Triggered by diversified friction materials under a working principle of freestanding mode, the open-circuit voltage, short-circuit current and maximum instantaneous power density from the WS-TENG can reach up to 166 V, 8.5 µA and 93 mW/m2, respectively. By virtue of high flexibility, desirable breathability, washability and excellent durability, the fabricated WS-TENG is demonstrated to be a reliable power textile to light up 58 light-emitting diodes (LED) connected serially, charge commercial capacitors and drive portable electronics. A smart glove with stitched WS-TENGs is made to detect finger motion in different circumstances. The work presents a new approach for self-powered textiles with potential applications in biomechanical energy harvesting, wearable electronics and human motion monitoring.

Upwelling processes bring nutrient-rich waters from the deep ocean to the surface. Areas of upwelling are often associated with high productivity, offering great economic value in terms of fisheries. The sensitivity of spring/summer-time coastal upwelling systems to climate change has recently received a lot of attention. Several studies have suggested that their intensity may increase in the future while other authors have shown decreasing intensity in their equatorward portions. Yet, recent observations do not show robust evidence of this intensification. The Senegalo-Mauritanian upwelling system (SMUS) located at the southern edge of the north Atlantic system (12°N–20°N) and most active in winter/spring has been largely excluded from these studies. Here, the seasonal cycle of the SMUS and its response to climate change is investigated in the database of the Coupled Models Inter comparison Project Phase 5 (CMIP5). Upwelling magnitude and surface signature are characterized by several sea surface temperature and wind stress indices. We highlight the ability of the climate models to reproduce the system, as well as their biases. The simulations suggest that the intensity of the SMUS winter/spring upwelling will moderately decrease in the future, primarily because of a reduction of the wind forcing linked to a northward shift of Azores anticyclone and a more regional modulation of the low pressures found over Northwest Africa. The implications of such an upwelling reduction on the ecosystems and local communities exploiting them remains very uncertain.

AbstractIn this paper a complete vehicle system simulation tool chain which applies a Multi Objective Optimization (MOO) methodology for designing the Electric Powertrain (ePT) of Battery Electric Vehicles (BEV) is presented. Optimization scope includes all relevant electric powertrain components from battery, inverter, electric machine to gear box. In addition to cost, vehicle dynamics, energy consumption and range are further optimization targets. For an overall minimal system cost design a multiplicity of interactions between all powertrain components has to be taken into account. High system complexity prevents an expert to consider all relevant correlations without the support of numeric simulation tools. The presented simulation tool chain enables fast identification of the best cost/benefit trade off regarding system cost while considering all defined system performance requirements. The approach enables experts to find unconventional solutions which would have been overlooked applying a classical straight forward approach and, thus, helps to sharpen the expert's knowledge in cause-effect relationships on the system level. Typical use cases are given and illustrated by several practical examples.

Abstract This work aims to predict the general performances of a pilot parabolic trough collector during transient periods. To do so, a one-dimensional thermal model has been developed. It has been validated with experimental results from two different experimental setups, in steady-state conditions, with a transmitted power maximum error of 3.4%. Since the model only predicts the collector's thermal behavior, the parabolic trough collector has been first optically qualified. Then, optical efficiencies were used as input for the model. Experimental results were obtained in steady-state conditions and compared to the model. Then, experimental and numerical results were compared during two period of time with varying inlet conditions (i.e. dynamic condition tests): the first one with stable conditions, and the other one with harsh conditions. The developed model showed a good capability of predicting the thermal behavior of the parabolic trough collector with unstable environment (DNI, mass flow, inlet temperature), with a 9.6% relative standard error in the worst case. As a conclusion, while previous studies only focused on steady-state conditions, it has been showed that this kind of model can be used to precisely predict the dynamic behavior of large power plants.

AbstractWe devise a methodology to predict failures in wind turbine drive‐train components and quantify its utility. The methodology consists of two main steps. The first step is the set up of a predictive model for shutdown events, which is able to raise an alarm in advance of the fault‐induced shutdown. The model is trained on data for shutdown events retrieved from the alarm log of an offshore wind farm. Here, it is assumed that the timely prediction of low‐severity events, typically caused by abnormal component operation, allows for an intervention that can prevent premature component failures. The prediction models are based on statistical classification using only supervisory control and data acquisition (SCADA) data. In the second step, the shutdown prediction model is combined with a cost model to provide an estimate of the benefits associated with implementing the predictive maintenance system. This is achieved by computing the maximum net utility attainable as a function of the model performance and efficiency of intervention carried out by the user. Results show that the system can be expected to be cost‐effective under specific conditions. A discussion about potential improvements of the approach is provided, along with suggestions for further research in this area.

In this study, feasibility of selected nutrient sequestration during hydrothermal carbonization (HTC) was tested for three different HTC temperatures (180, 230, and 300 °C). To study the nutrient sequestration in solid from liquid solution, sugar and salt solutions were chosen as HTC feedstock. Glucose was used as carbohydrate source and various salts e.g., ammonium hydrophosphate, potassium chloride, potassium sulfate, and anhydrous ferric chloride were used as source of nitrogen and phosphorus, potassium, and iron, respectively. Solid hydrochar was extensively characterized by means of elemental, ICP-OES, SEM-EDX, surface area, pore volume and size, and ATR-FTIR to determine nutrients’ sequestration as well as hydrochar quality variation with HTC temperatures. The spherical mesoporous hydrochars produced during HTC have low surface area in the range of 1.0–3.5 m2 g?1. Hydrochar yield was increased about 10% with the increase of temperature from 180 °C to 300 °C. Nutrient sequestration was also increased with HTC temperature. In fact, around 71, 31, and 23 wt% nitrogen, iron, and phosphorus were sequestered at 300 °C, respectively. Potassium sequestration was very low throughout the HTC and maximum 5.2% was observed in solid during HTC.