The efficient use of solar energy to produce hydrogen by thermochemical and photochemical reactions is quite challenging and promising. Solar thermochemical processes can make use of full spectrum sunlight but ignore the energy quality differences between spectrums, while photochemical processes can convert light into chemical energy but use part of the solar spectrum. To explore the possibility of combining solar light and heat, an experimental study of photo-thermochemical methanol steam reforming reaction is conducted in a fixed bed reactor. Photochemical and thermochemical reactions are carried out simultaneously on Cu/ZnO/Al2O3 catalyst. Compared to thermochemical reactions (TRs), the photo-thermochemical reaction (PTR) shows an increased conversion rate, especially at low temperature. At 188℃, the PTR improves the yield of hydrogen by 32.9%. According to the characterization results, the photo-generated electrons contribute to the enhancement of the PTR. The mechanism for the increased conversion rate is further discussed from the thermodynamics perspective. These findings provide a reference for future integrated use of light and heat at mid-and-low temperatures.
Access to affordable and clean energy is one of the basic requirements for sustainable growth. Bangladesh, as one of the developing nations, currently faces rapid growth in the electricity sector. However, limited potential of indigenous natural resources might jeopardize energy security in long-term. Adoption of modern clean energy sources like nuclear power, renewable energy generation technologies have their own economic and technical limitations.
In this study, we analyzed all available and potential energy sources for electricity generation considering techno-economic limitations and applied linear programming to obtain the best electricity generation mix that would ensure low cost and limited emission simultaneously. The whole country is geographically divided in to nine regions to obtain a high spatial resolution of current installed capacities and future potential for expansion. Moreover, hourly demand for all different nodes is projected so that high temporal resolution can be achieved. This dynamic optimal power generation mix model provides optimized generation and capacity mix from 2025 to 2050 at five years intervals with hourly dispatch schedule. Different economic growth scenarios for electricity demand projection and policy scenarios including carbon-emission limits and adaptation of new technologies have been considered for sensitivity analysis. This analysis provides a clear pathway for low-cost optimum electricity sector expansion by incorporation of modern technologies like nuclear power and renewables with storage capacity.
The COVID-19 pandemic has negatively affected people living in vulnerable conditions around the world—especially rural communities with lack of access to basic services. Rural electrification can play a fundamental role in pandemic recovery by facilitating the provision of basic services and improving quality of life for poor rural communities. This study aims analyze this potential through understanding the correlation of multidimensional variables with electricity consumption. The dominant approach to rural electrification has been a for-profit model, which has hindered electricity access for the most vulnerable populations of the global South. Using multiple linear regression tools, this study confirms that a renewable energy generation model that considers social, economic and environmental factors, in addition to technical factors, is pivotal to increasing electricity consumption, and consequently facilitate greater energy access in developing countries.
One of the cleanest burning fossil fuels is natural gas and is recognized as a strong candidate for energy resources as compared to oil and gas. Natural gas hydrates are commonly found in Shallow and deep waters where suitable pressure and temperature condition combine to make it stable. Gas Hydrates are the potential source of methane which needs to be extracted from the seabed but exploitation of it is much far from being economically viable and safe. Various methods for the exploitation of methane gas are depressurization, thermal stimulation, chemical inhibitor injection and replacement methods. These methods are being widely studied by using experimental approach and numerical methods. Numerous Fields tests carried out by different nations to produce the methane gas from natural gas hydrate reservoir and observed that it’s a complex process. This paper gives comparative study on the effect of exploitation methods on methane gas recovery from natural gas hydrate deposit. Combination of different methods for the production of methane gas from natural gas hydrate is briefly reviewed. Possible methods for the extraction of natural gas in each method and challenges/limitations are discussed in detail. Combination of thermal stimulation and depressurization method is observed to be more efficient than the individual methods in terms of recovery of methane gas from gas hydrates.
Technology advancements and increasing energy demands has introduced the world to the major problem of climate change. The emission of greenhouse gases in the atmosphere due to combustion of fossil fuels has adversely affected biodiversity and ecosystem. For the remedial of this global issue, extensive studies come up with the hybrid approach of utilizing CO2 Capture Technology for sequestrating CO2 in hydrates. This paper aims to provide review of the current CO2 capture techniques and the work done to study the CO2 sequestration in porous medium using CCS technology. For the sequestration of CO2, CO2-CH4 exchange technique is mainly focused. The water saturation and clay minerals showed inhibitive nature on CO2 storage efficiency in natural hydrate bearing sediments. In addition, the gas chromatography provides evidence for the greater CO2 storage capability in hydrates. Further, this technique showed the wider aspect of CCS technology for generating energy and reducing excess CO2 from the atmosphere.
With the growth of the transport sector and its emissions, the European Union (EU) has obliged member states to increase the share of renewable energy sources. To understand which policies need to be pursued to achieve the objectives set by the EU, a system dynamics model was developed and applied to the case study of Latvia. The model considers the potential of the production and use of renewable fuels, the impact of policies on the development of renewable energies, and factors influencing population choice of transport mode.
The melting and solidification of phase change material (PCM) in a horizontal eccentric shell-and-tube latent heat storage (LHS) unit were numerically studied to design a high-efficiency LHS configuration. Firstly, the melting and solidification in a concentric configuration were studied to reveal the influence of natural convection. The results show that, because of natural convection, the solid PCM above the tube has a high melting rate during the melting process and the liquid PCM under the tube has a high solidification rate during the solidification process. Then the eccentric tube configuration was used to take the best advantage of natural convection. The results show that the eccentric tube with the tube moving to the downside can efficiently enhance the PCM melting rate. The best melting performance can be obtained when the eccentricity (ε) is -0.6, where the PCM melting time reduces about 29.8% compared with the concentric tube. However, the downward movement of the tube seriously weakens the PCM solidification rate and causes total performance deterioration of the entire melting and solidification cycle. For the whole melting and solidification cycle without rotation, the minimum total time is obtained at ε= 0.1 which is only 1.3% less than the total time at ε= 0. A new LHS unit with a rotation configuration was proposed to enhance PCM melting and solidification rates simultaneously. The validation results show the optimum heat transfer performance for the whole melting and solidification cycle can be obtained when ε = -0.2, where the total melting and solidification time reduces by 11.1% compared with concentric configuration.
In the study of in-plane signal acquisition and measurement of polymer electrolyte membrane fuel cells, it is difficult to ensure the accuracy of direct signal measurement because the voltage drop of the shunt resistor that needs to be used is small and easily disturbed and generates transmission loss. This paper develops a distributed signal integrated amplification sensor (DSIAS) using PCB segment measurement technology, which amplifies the segment voltage drop signal instantaneously before transmission and acquisition. It avoids the loss and interference of small signals in the transmission process. In addition, a unique collector structure is designed to meet the matching installation between the endplate and the PCB sensor, thus enabling online amplified measurement of planar information without affecting the internal system of the fuel cell. This signal amplification sensor has been initially measured and applied planar segment impedance. Under standard operating conditions, measurements were taken to obtain the impedance information of the in-plane segments. The electrochemical impedance spectra of the cell single and each segment were plotted separately using the FFT algorithm of MATLAB software. These works can be applied to understand and explore the internal mechanisms of fuel cells in more depth.
This paper dedicates to investigate the feasible and sustainable combustion fuel design which can be used to mitigate the environmental challenges posed by using conventional combustion fuel such as natural gas (CH4) and propane (C3H8) in the industrial metal reheating processes. Three possible solutions were evaluated by using CFD method in Ansys Fluent: oxy-H2, air-H2 and airNH3/H2. It has been found that oxy-H2 combustion can simultaneously satisfy the requirement of both flame temperature and NOx reduction. However, the use of oxy-H2 solution might lead to high costs and a large amount of waste heat. The air-H2 solution possesses the advantage of low cost and sufficient heat, but the NOx emission is higher than that of propane combustion due to higher flame temperature. For the air-NH3/H2 solution, feasible combination schemes taking into consideration flame temperature, combustion efficiency and NOx emissions were determined and ready to be analysed in terms of scale formation.
An ecological driving strategy considered battery State-of-Health is proposed based on Deep reinforcement learning. Not only does this strategy try to minimize fuel consumption while maintaining the safe car-following sate, it also seeks to lower the battery aging speed. In order to optimize the car-following and energy management performance, reward functions are developed by combing driving features of car-following, engine and battery characteristics. The agent maximizes the accumulated reward by interacting with the simulation environment to explore the action space. While controlling the SHEV to maintain a safe car-following distance, the proposed method reduces the effective Ah-throughput by 15 -57.6% and only increases the fuel consumption within 5% compared with the case of achieving the best fuel economy. In addition, this method is proven to achieve similar results in different driving cycles.