• Energy Research

Abstract The purpose of this paper is to investigate the influence of blending methods on the co-gasification of petroleum coke and lignite with CO 2 using a thermogravimetric system at 0.1 MPa. The weight loss curves, XRD analysis, SEM images, BET specific surface area, were investigated. It was observed that petroleum coke shows a low reactivity because of the graphitic carbon structure, low catalyst content and small specific surface area. Blending with lignite can get a high reactivity. The co-gasification reactivity was significantly influenced by blending methods. Wet grinding is much effective than dry grinding. Long grinding time made lignite show greater BET specific area. And the sample in long grinding time has more association chances between petroleum coke and AAEM species. The co-gasification reactivity increases linearly with a rise of BET specific area.

Microalgae are recognized as a third generation feedstock for biofuel production due to their rapid growth rates and lignin-free characteristics. In this study, a lipid extracted microalgal biomass residues was used as the raw material to produce isoprene, α-pinene and β-pinene with an engineered E. coli strain. We adopted an optimal sulfuric acid hydrolysis method (1:7 ratio of solid to acid solution, 32% (w/v) concentration of sulfuric acid solution at 90 °C for 90 min) to efficiently convert holocellulose into glucose efficiently (6.37 g/L). Futhermore, we explored a novel detoxification strategy (phosphoric acid/calcium hydroxide) to remove inhibitors and notably acetic acid, furfural and 5-hydroxymethylfurfural (5-HMF) were reduced by 5.32%, different number given later 99.19% and 98.22%, respectively. Finally, the fermentation concentrations of isoprene (223.23 mg/L), α-pinene (382.21 μg/L) and β-pinene (17.4 mg/L) were achieved using the detoxified hydrolysate as the carbon source, equivalent to approximately 86.02%, 90.16% and 88.32% of those produced by the engineered E. coli strain fermented on pure glucose, respectively.

AbstractWe have measured the effect of degradation on the I-V characteristics in APFO3:PCBM solar cells. The solar cell devices were subject to ambient air under simulated solar illumination. We found that the degradation resulted in a lowering of the fill factor and short circuit current while the open circuit voltage remained unchanged. In order to gain insight into what has caused the degraded I-V characteristics we have studied the active layer film using various techniques. We found clear spectral changes both in absorption and in photoinduced absorption spectroscopy correlated with increased carrier lifetimes and lowered mobility when comparing the degraded film with a pristine one. The results show a significant degradation of the active layer causing a lower fill-factor and short circuit current.

Abstract Three-dimensional (3D) metal halide perovskite solar cells (PSCs) have a power conversion efficiency that is now comparable with conventional silicon solar cells. For PSC applications to succeed in the market, long-term reliability under open-air conditions is essential. Recent experiments have shown that two-dimensional (2D) perovskites seem to exhibit good stability due to the presence of hydrophobic organic spacers, but 2D PSCs are incapable of generating and transporting a large amount of charge due to their extended optical bandgaps. Mixed dimensional perovskites with dimension lies between 2D and 3D recently became a promising candidate to sustain long-term stability and high performances concurrently to address this obstacle. The current research article presents the finding of simulation-based studies performed on novel device architecture consisting of ITO/Nb-Ti2O3/3D Perovskite/2D Perovskite/Spiro-OMeTAD/Au. Using optical simulation features of SCAPS, absorption of light is computed in the proposed device. The computational results show that the thickness of the 2D perovskite layer badly affects the solar cell parameters. A thin 2D perovskite behaves as a capped coating that avoids the deterioration of 3D perovskite in open-air environments. The effect of a multivalent defect in the 3D perovskite layer is mathematically modelled, and their impact on overall performance parameters are analyzed. The findings are compared to the same configuration results, except where the absorber layer’s multivalent defect has been substituted by a neutral defect of the same defect density of about (1011 cm−3). Results show that the multivalent defect leads to an underestimation of the efficiency by 4.2%.

Abstract This study investigates the possibility of using and developing hydrokinetic power to supply reliable, affordable and sustainable electricity to rural, remote and isolated loads in rural South Africa where reasonable water resource is available. Simulations are performed using the Hybrid Optimization Model for Electric Renewable (HOMER) and the results are compared to those from other supply options such as standalone Photovoltaic system (PV), wind, diesel generator (DG) and grid extension. Finally the paper points out some major challenges that are facing the development of this technology in South Africa.

The shipping industry faces a large challenge as it needs to significantly lower the amounts of Green House Gas emissions. Traditionally, reducing the fuel consumption for ships has been achieved during the design stage and, after building a ship, through optimisation of ship operations. In recent years, ship efficiency improvements using Machine Learning (ML) methods are quickly progressing, facilitated by available data from remote sensing, experiments and high-fidelity simulations. The data have been successfully applied to extract intricate empirical rules that can reduce emissions thereby helping achieve green shipping. This article presents an overview of applying ML techniques to enhance ships’ sustainability. The work covers the ML fundamentals and applications in relevant areas: ship design, operational performance, and voyage planning. Suitable ML approaches are analysed and compared on a scenario basis, with their space for improvements also discussed. Meanwhile, a reminder is given that ML has many inherent uncertainties and hence should be used with caution.

KOF Working Papers, 327

Abstract Day-ahead forecasts of direct normal irradiance (DNI) from the Integrated Forecasting System (IFS), the global model of the European Centre for Medium-Range Weather Forecasts (ECMWF), are used to simulate a concentrating solar power (CSP) plant through the System Advisor Model (SAM) to assess the potential value of the IFS in the electricity market. Although DNI forecasting from the IFS still demands advances towards cloud and aerosol representation, present results show substantial improvements with the new operational radiative scheme ecRad (cycle 43R3). A relative difference of approximately 0.12% for the total annual energy availability is found between forecasts and local measurements, while approximately 10.6% is obtained for the previous version. Results of electric energy injection to the grid from a simulated linear focus parabolic-trough system shows correlations coefficients of approximately 0.87 between hourly values of electric energy based on forecasted and measured DNI, while 0.92 are obtained for the daily values. In the context of control strategy, four operational strategies are given for different weather scenarios to handle the energy management of a CSP plant, including the effect of thermal energy storage capacity. Charge and discharge operational strategies are applied accordingly to the predicted energy availability.