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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.

The present work focuses on the sampling procedure and quantification of the PAH yield from the fast pyrolysis of waste softwood. In particular, fast pyrolysis experiments were conducted using a CDS Pyroprobe 5200 at temperatures between 500 °C and 1000 °C, at a heating rate of 600 °C/s for a sample size of 30 mg. High performance liquid chromatography (HPLC) was used for the determination of the PAH compounds present in the liquid sample fraction, while a micro – GC was employed for the analysis of the main gaseous products (CO, CO2, CH4 and H2). An alternative tar sampling protocol was proposed, which employed the use of a cold trap (50 °C) and an isopropanol filled impinger bottle for the collection of the condensable products. The experiments were compared to heated foil reactor based pyrolysis tests within the same temperature range and heating rate, except for a slightly lower sample size (10 mg). The Pyroprobe and adapted sampling system proved to be more efficient regarding PAH capture and quantification compared to the heated foil reactor. Naphthalene, acenaphthylene and phenanthrene were the main PAH compounds detected. The PAH yields increased with pyrolysis temperature, up to values corresponding to roughly 0.2 wt% of the overall yield at 1000 °C. From the results it was derived that PAH evolution is mainly a product of secondary decomposition of primary tar, since the char yield stabilized for higher temperatures and the yields of CO, H2 and CH4 increased. Overall mass balance closure values were around 80 wt% on average. Char and gas yields were determined with high reproducibility, however gravimetric liquid analysis lacked due to the inability to gravimetrically measure the yield condensing in the impinger bottle. Future work is aimed on improving on this particular aspect. Overall, the alternative tar sampling system proposed was successful in the quantification of PAH from biomass fast pyrolysis experiments offering increased flexibility, accuracy and practicality of use.

Abstract The use of photovoltaic solar power generation is rising as worldwide energy demand increases. Therefore, reliability, safety, life cycle, and improved efficiency of photovoltaic plants have all become a major concern in research nowadays. In this context, monitoring systems are necessary to guarantee the required operating productivity and to avoid overpriced maintenance costs. This paper studies the non-ideal operating conditions for grid-connected photovoltaic plants and proposes an anomaly detection methodology that combines the advantages of the 2-sigma, short-window simple-moving average control charts with shading strength and irradiance transition parameters to detect early deviation in photovoltaic plant operational data. The key aspect of proposed methodology is that it requires neither historical data for model training procedure nor parameters from previous simulation. Only instantaneous meteorological and electrical parameters are required. The efficiency of the condition monitoring methodology has been validated through experimental results conducted in actual operating conditions. Results demonstrated that the proposed methodology is effective to identify non-ideal operating conditions for grid-connected photovoltaic plants, i.e., (i) normal operating condition, (ii) natural dynamic shading, (iii) artificial dynamic shading, and (iv) artificial static shading. Moreover, a low-cost and non-invasive internet-of-things-based embedded architecture is proposed to monitor photovoltaic plant operation in real-time.

Abstract For Solid Oxide Fuel Cells (SOFCs) to become an economically attractive energy conversion technology, suitable materials and structures which enable operation at lower temperatures, while retaining high cell performance, must be developed. Recently, the perovskite-type La 0.6 Ca 0.4 Fe 0.8 Ni 0.2 O 3 oxide has shown potential as an intermediate temperature SOFC cathode. An equivalent circuit describing the cathode polarization resistances was constructed from analyzing impedance spectra recorded at different temperatures in oxygen. A competitive electrode polarization resistance is reported for this oxygen electrode using a Ce 0.8 Gd 0.2 O 1.9 electrolyte, determined by impedance spectroscopy studies of symmetrical cells sintered at 800 °C and 1000 °C. Scanning electron microscopy (SEM) studies of the symmetrical cells revealed the absence of any reaction layer between cathode and electrolyte, and a porous electrode microstructure even when sintered at a temperature of only 800 °C. The performance of this cathode shows favorable oxygen reduction reaction (ORR) properties potentially making it an excellent choice for IT-SOFC application.

Abstract This paper presents a novel load frequency control (LFC) model for an interconnected thermal two-area power system in the presence of wind turbine generation and redox flow battery (RFB). The study model includes frequency and voltage excitation loops with needed interactions between them along with the power system stabilizer. A two-degree of freedom (2DOF)-based controller called 2DOF-Hybrid controller is developed as secondary controller in automatic generation control (AGC) to adjust the power outputs of generator and RFB. Also, the dynamic performance of the proposed controller in the RFB loop is evaluated. The Hybrid controller comprises a fractional-order proportional-integral-derivative (FOPID) controller and a tilt-integral-derivative (TID) controller. In order to obtain accurate and realistic results, the outputs of thermal power plants are restricted by considering the limitations of the governor dead-band and generation rate constraint. Since the controller performance depends on its parameters, these parameters are optimized using a modified sine–cosine algorithm (MSCA). The dynamic performance of the proposed 2DOF-Hybrid controller as secondary controller of the AGC loop is compared with integral-double-derivative (IDD), integral-tilt-derivative, proportion-integral–derivative (PID)-DD, 2DOF-PID, 2DOF-TID, and 2DOF-FOPID ones under different scenarios. In addition, the superiority of the MSCA is compared with benchmark metaheuristic methods including an SCA, a genetic algorithm, a particle swarm optimization, and a differential evolution. The sensitivity analysis is also carried out to show the robustness of the proposed controller versus the changes of the parameters. The simulation studies on two-area and New England 39-bus power systems are carried out to examine the advantage of the presented LFC scheme. A range of power system signals such as frequencies of areas, terminal voltages, and tie-line power flow is demonstrated to compare the controllers. The results disclose that the proposed LFC scheme provides better dynamic performance compared to other ones. Moreover, RFB modeling based on the proposed controller is superior to conventional RFB modeling in reducing the amplitude of the oscillations.

Abstract Building materials with high thermal and hygric inertia can moderate the fluctuation of indoor temperature and relative humidity, and thus can improve the indoor thermal comfort and reduce the building energy consumption passively. In this study, a novel hygrothermal control material was prepared based on Metal-Organic Frameworks (MOFs) and microencapsulated phase change material (MicroPCM). The new MOF/MicroPCM composite has a dual functionality of adsorption and desorption of both heat and moisture, can offer an accurate passive control of the indoor hygrothermal environment. N-octadecane was encapsulated by polymethylmetracrylate (PMMA) as MicroPCM for the thermal buffering. MIL-100(Fe) was prepared by the hydrothermal reaction method as the humidity buffering material. A series of hygrothermal control composite materials were obtained by grinding MicroPCM and MIL-100(Fe). Physicochemical properties of the synthesized materials were characterized by SEM, TEM, XRD, FTIR, N2 physisorption, Water vapor sorption isotherm, DSC and TGA techniques. Hygrothermal properties of the composites were analyzed in comparison to pure MicroPCM and MIL-100(Fe). The thermal and humidity buffering behavior of the composites containing 50% MicroPCM was analyzed by numerical simulations. The results show that the composites possess an excellent thermal and humidity buffer capacity, which can be used for building energy-saving and improving thermal comfort.

The aim of this study was to determine favorable operation conditions for ceiling panels containing phase change materials (PCM) for cooling applications in office rooms. A recently renovated room in the Technical University of Denmark was used to have realistic boundary conditions. Using TRNSYS 17, the performance of the PCM panels during the cooling season in passive operation, discharge by air, and discharge by water circulation were investigated. A set of simulations were performed during a representative week in the cooling period. The room was simulated with no climatic systems, PCM without active discharge, ventilation during occupied hours only, and PCM with ventilation during occupied hours. Afterwards, two discharge methods were investigated, night ventilation at different flow rates and water circulation in pipes embedded in the panels. A parametric analysis was performed to identify the influence of operation factors in the thermal environment of the room. The parameters studied were the water flow rate, supply water temperature and circulation schedule as well as the conductivity of the PCM. After selecting different operating conditions of the water discharge, simulations were performed from May to October to observe the performance of the selected operation conditions. The results show that the PCM is more effective to provide adequate indoor thermal conditions if it is discharged actively by means of water. The parameters that affect the thermal indoor environment the most are the water circulation schedule, the water supply temperature, and the PCM thermal conductivity. The water flow rate did not have a significant influence. The study shows the importance of selecting an appropriate operation and control strategy for the PCM system. The process used in the study can be potentially used as a procedure for the design of similar climatic systems to determine if active discharge of the PCM is needed and if yes, which discharge method is needed.