Green Energy and Resources最新文献

Optimizing process conditions in anaerobic digestion could enhance the utilization of organic matter for renewable energy generation. Thus, initial upset substrates with elevated volatile fatty acids were investigated under agitation and non-agitation conditions for optimal bioreactor performance. There were two continuous agitation scenarios for the liquid-state (40 and 100 rpm) with a non-agitated scenario. Similarly, a non-agitated and 40 rpm scenario for the solid-state. The result indicated that the non-agitated liquid-state reactor had the highest methane yield (193 L/kgVS) and lowest retention (51 days) despite delayed microbial adaptation. Of the prominent microbes, the relative abundance of Firmicutes and Archaea_unclassified negatively correlated with VFA at 100 rpm. Contrarily at 40 rpm, Firmicutes correlated positively with VFA, an indication that Firmicutes could withstand acid production at agitation speed ≤40 rpm suggesting that agitation associated with VFA might reduce microbial diversity in an initial upset liquid-state bioreactor. Thus, upset influent could be utilized for energy generation with a non-agitated liquid-state bioreactor.

Nickel (10∼50 mol%) doped calcium ferrite nanoparticles (NPs) are synthesized by the solution combustion method using lemon juice extract as a reducing agent, followed by calcination at 500°C. The calcined samples are characterized with different techniques. The Bragg reflections of Nickel doping confirm the formation of a single orthorhombic calcium ferrite phase. The crystallite size is estimated using both Scherrer's and the W-H plot method. The surface morphology consists of irregular size and shaped agglomerated NPs along with pores and voids. A blueshift and a broad absorption spectrum is observed with an increase in the direct energy band gap. The direct energy band gap estimated from Wood and Tauc's relationship was found to be 2.91∼2.97 eV with an increase in dopant concentration. The magnetic analysis provided values for saturation magnetization (M_s), remanence (M_r), and coercivity (H_c), while dielectric studies demonstrated a dielectric constant of 2.81, 2.14, and 1.67 with increasing dopant concentration. The variation of dielectric properties of the sample as a function of frequency in the range 0.1∼20 MHz has been studied at room temperature. The dielectric properties of CaFe₂O₄: Ni (1∼9 mol%) NPs clearly indicate that there is a more pronounced dispersion at lower frequencies, gradually reaching saturation as the frequency increases. The dielectric loss was found to decrease from 4.62, 3.22, and 2.32 with an increase in Ni²⁺ substitution (10, 30, and 50 mol%) respectively. These results indicate the suitability of these samples for applications in memory devices and high-frequency applications.

When selecting biomass feedstock for sustainable heat and electricity generation, higher heating value (HHV) is an important consideration. Meanwhile, the laboratory procedures of using an adiabatic oxygen bomb calorimeter to determine the HHV are strenuous, costly, and time-consuming. As a result, researchers have turned to artificial intelligence techniques such as artificial neural networks (ANN) to predict HHV using data from proximate analysis. Notwithstanding, this approach has been hampered by different case-specific techniques and methodologies given the heterogeneous nature of biomass materials and intricate ANN structures. This study, therefore, examined and compared the efficacy of six training algorithms comprising thirteen distinct training functions of feedforward backpropagation neural networks to predict the HHV of a variety of biomass materials as a function of the proximate analysis. In creating the networks, the neurons of the hidden layer were iterated from 1 to 20 leading to 260 investigated scenarios. Compared to other training algorithms, the Bayesian Regularization and Levenberg-Marquardt with 15 and 12 hidden neurons respectively, demonstrated superior prediction performances based on the Nash-Sutcliff's efficiencies of 0.9044 and 0.8877, and mean squared errors of 0.002271 and 0.00267. It is envisaged that this study will create an insightful paradigm for a rapid selection of best-performing ANN algorithms for biomass HHV prediction.

To promote the formation of CO₂ hydrate for cold energy storage, the influence of gas-inducing agitation at varying operating speeds were studied experimentally. A comparison was made with normal stirring (without gas inducing) from the perspectives of deviation from equilibrium condition, subcooling, agglomeration, and hydrate production. The test results revealed that gas-inducing agitation contributed to a closer shift of the hydrate formation profiles towards equilibrium conditions when compared to normal stirring. However, this advantage became less pronounced as the stirring speed increased. Notably, a substantial improvement in subcooling phenomena was observed when transitioning from 250 rpm normal stirring to 500 rpm, decreasing the induction time to 19.3%. Comparing normal stirring, the incorporation of a gas-inducing stirrer further reduced the induction time by 68.6% at 400 rpm. Nevertheless, further increasing agitation speed for both sets did not yield apparent improvement in the subcooling phenomenon. In contrast to normal stirring, gas-inducing agitation effectively prevented hydrate agglomeration at a lower speed and led to increased hydrate production at the same rotation speed. An ascending trend in hydrate production was achieved as agitation accelerated from a low speed to a specific speed, e.g., 400 rpm for gas-inducing stirring and 500 rpm for normal stirring. However, further elevating the stirring speed did not stimulate greater hydrate production. The findings of this study indicated the existence of double-sided effects in using gas-inducing stirring for hydrate promotion and a crucial speed range (e.g., 400∼450 rpm in this study) essential for the efficient implementation of gas-inducing technology. Operating at this prescribed speed range was recommended to improve the energy Return on Investment, maintaining high hydrate production, and enhancing the controllability of cold storage systems. This study provides practical insights for applying gas-inducing technology in gas hydrate reactors, contributing to the development of green cold energy storage.

Energy storage is a crucial solution for the intermittency and instability of renewable energy. Carnot batteries, a novel electrical energy storage technology, promise to address the challenges of renewable electrical energy storage worldwide. Rankine-based Carnot batteries, which are geographically unconstrained and effectively store energy at low temperatures, have attracted considerable attention in recent years. In this study, a mathematical model was developed, and a multi-objective optimization with power-to-power-efficiency, exergy efficiency, and levelized cost of storage was performed. Moreover, the investment cost and exergy loss of the optimized system components were investigated in detail and analyzed. The results showed that the optimal power-to-power-efficiency, exergy efficiency, and levelized cost of the storage system can be achieved at 60.3%, 33%, and 0.373 $/kWh based on single-objective optimization, and the operating parameters of the proposed system are different. Therefore, there is a strong trade-off relationship between the three objective functions mentioned above. Under the same weighting for the two approaches, they are 25.8%, 23%, and 0.437 $/kWh, and 39.3%, 29.1%, and 0.549 $/kWh, respectively. Furthermore, this study observed that the exergy destruction in the charge mode was nearly 95 kW larger than that in the discharge mode, and the exergy destruction of the throttle valve was the largest at 95.83 kW, accounting for 28.32%. The expander was the component with the highest cost (35.84% of the total cost) in the proposed system, followed by the compressor.

Developing countries face challenges in maintaining a reliable power supply due to factors such as ageing infrastructure and rapid urbanization. Relying on backup diesel generators during outages is not only ecologically hazardous but also economically inefficient. Integrating multiple renewable sources with conventional energy systems is crucial to meeting growing energy demands and reducing carbon emissions. This study assesses dispatch strategies for optimal operation in hybrid renewable energy systems (HRES) connected to an unreliable national grid (GRD). An enhanced combined dispatch (ECD) strategy is introduced for effective energy distribution, considering load demands, energy resource availability, and grid unreliability. Compared to load following (LF) and cycle charging (CC) strategies, the ECD strategy proves superior, resulting in an optimized HRES configuration with a 248 kW solar PV array, a 2 kW wind turbine (WDT), a 22 kW biogas generator (BGG), a 92 kW diesel generator (DiG), and a 658 kWh battery storage (BSS). Achieving a low Levelized Cost of Energy (LCOE) at 0.148 USD per kilowatt-hour and a Net Present Cost (NPC) of 1.99 million USD. Adopting the ECD strategy also exhibits substantial reductions in CO₂, CO, SO₂, and NO_x emissions when compared to CC and LF. ECD achieves approximately 25% lower CO₂ emissions, 34% lower CO emissions, and a 40% reduction in SO₂ and NO_x emissions. These findings highlight the ECD strategy's potential for effective, economically viable, and environmentally conscious energy solutions, particularly relevant in developing nations like Nigeria, where Hybrid Renewable Energy Systems could play a crucial role in the energy sector.

Increasingly stringent emission standards have led shippers and port operators to consider alternative energy sources which can reduce emissions while minimizing capital investment. It is essential to understand whether there is a certain economic investment gap for alternative energy. The present work mainly focuses on the simulation study of ships using ammonia and hydrogen fuels arriving at Guangzhou Port to investigate the emission advantages and cost-benefit analysis of ammonia and hydrogen as alternative fuels. By collecting actual data and fuel consumption emissions of ships arriving at Guangzhou Port, the present study calculated the pollutant emissions and cost of ammonia and hydrogen fuels substitution. As expected, it is shown that with the increase of NH₃ in fuel, mixed fuels will effectively reduce CO and CO₂ emissions. Compared to conventional fuel, the injection of NH₃ increases the NO_x emission. However, the cost savings of ammonia fuel for CO₂, SO_x and PM₁₀ reduction are higher than that for NO_x. In terms of pollutants, ammonia is less expensive than conventional fuels when applied to the Guangzhou Port. However, the cost of fuel supply is still higher than conventional energy as ammonia has not yet formed a complete fuel supply and storage system for ships. On the other hand, hydrogen is quite expensive to store and transport, resulting in higher overall costs than ammonia and conventional fuels, even if no pollutants are produced. At present, conventional fuels still have advantage in terms of cost. With the promotion of ammonia fuel technology and application, the cost of supply will be reduced. It is predicted that by 2035 ammonia will not only have emission reduction benefits, but also will have a lower overall economic cost than conventional fuels. Hydrogen energy will need longer development and technological breakthroughs due to the limitation of storage conditions.

In recent years, ion-selective capacitive deionization (CDI) technology has been used to selectively separate ions from multi-ion composition solutions. Innovative ion-selective electrode materials have been widely used in the fields of recovery of high-value ions and removal of toxic and harmful ions. Developments of electrode materials and their structure-chemical activity relationships were reviewed and analyzed. Moreover, anticipatory observations and challenges regarding the future of ion-selective CDI devices are discussed. Ultimately, this comprehensive review aims to provide meaningful insights and directions in the exploration for ideal ion-selective electrode materials, propelling further advancements in CDI systems.

Photo-thermal catalytic CO₂ hydrogenation to value-added products is considered a viable strategy for CO₂ conversion, whereas the unsatisfactory selectivity and conversion efficiency hinder its practical applications. Herein, Pt nanoparticles supported on LaCoO₃ with different loadings were prepared for photo-thermal catalytic CO₂ hydrogenation. Transmission Electron Microscope (TEM) images revealed that the Pt nanoparticles (about 2∼4 nm) were evenly dispersed on the surface of rhomboid-phased LaCoO₃ supports. X-ray photoelectron spectroscopy (XPS) studies showed that in the composited catalysts, electron transfer from LaCoO₃ to Pt occurred, suggesting a strong interaction between Pt and LaCoO₃. In result, 0.6 Pt/LaCoO₃ showed a remarkable CH₄ production rate of 119.8 mmol g_cat⁻¹ h⁻¹ with 87% selectivity at 250°C under visible light irradiation. Additionally, the in situ diffuse reflectance infrared Fourier transformations spectroscopy (DRIFTS) indicated that formate is the main intermediate species in the photo-thermal catalytic CO₂ hydrogenation process and illumination could promote the conversion of intermediate species without changing the reaction pathway, thus increasing the yield of CH₄. Given that the catalyst preparation approaches could be easily scaled up and the conversion efficiency of CO₂ is satisfactory, it is confident that this research will offer valuable guidance for the future industrialization of CO₂ conversion.