A mathematical model was developed in this study for predicting the dynamic heat transfer from geothermal reservoirs to natural gas hydrate (NGH) reservoirs for reducing the cost of natural gas production from gas hydrate deposits. The derived analytical solution was validated by numerical simulation. The expression of the mathematical model shows that, for a given geothermal-gas-hydrate system, the heat transfer is proportional to the mass flow rate of heat-transferring work fluid. A field-case study with the mathematical model indicates that the NGH reservoir temperature should rise quickly at any heat-affected point, but it should propagate slowly in the radial direction. It may take more than two years to dissociate NGH within 20 m of the heat dissipator wellbore due to thermal stimulation. The slow process of heat conduction suggests that the heat dissipator wellbores should be perforated to cause heat convection into the gas hydrate reservoirs to expedite gas production from the gas hydrate reservoirs.
The building envelope (walls, floor, windows,roof) is a very important element of the design as it can have a effect on the energy performance of the building, that is comfortable all year round can be achieved with reasonable levels of insulation, reduced thermal bridging, summertime shading features, and ventilation. Depending on the properties of the thermal zone where we are, it is therefore possible to integrate PCM and optimize their parameters in order to favorably diphase the energy consumption peaks and energy consumption and, by the same token, significantly reducing the use of the HC system. Consequently, the integration of this PCM in the envelopes of new buildings or in renovation would contribute to reduce the energy bill in the building sector in Morocco. So the (PCM) represents a sustainable alternative to reduce energy consumption for this a thermal dynamic simulation was realized with TRNSYS 204. Since PCM involves large latent heat at small temperature phase changes, PCM is used for temperature stabilization and for storing heat with large energy densities and capacity the storage in combination with rather small temperature changes. The simulation was carried out for the climate zone of Morocco (Casablanca Nouasseur). The results of the simulation showed that the use of phase change materials inbrick walls reduced overheating in the summer period, decreasing the ambient temperature of the indoor air by 3 °C.
CO2 reforming of CH4 by solar energy is a promising solution to the problems of energy shortage and global warming, by converting two greenhouse gases into fuel. Reticulated porous foam supports are promising candidates for solar-driven carbon dioxide reforming of methane (CRM) reactions due to their favorable thermal conductivity, superior mechanical strength, and high gas permeability. Here, the axial and radial parameters of the porous foam are co-optimized to enhance the solar absorption and CRM reaction. The optimal Ni foam catalyst parameters are obtained by combining the physical model simulation with the genetic algorithm. The light-fuel efficiency of optimized homogeneous porous is up to 46.47%. The optimization structures of the graded pore size show disparate light absorption strategies in the radial direction for better adaptation to Gaussian-distributed concentrated solar energy, and light-to-fuel efficiencies are up to 55.0% and 52.2% respectively. This work analyzes the effects of graded porous foam support on solar energy absorption and chemical reactions, which opens new routes to the design of efficient porous foam catalysts for better adaptation to Gaussian-distributed light-driven CRM reactions.
High temperature process industries reject up to 60 % of their thermal energy as waste heat that is difficult to recover due to high up-front costs and the complexity of installing conventional heat-recovery systems. Market resea rch suggests tha t certa in industries a re willing to a dopt Thermophotovoltaic (TPV) systems into their process as the technology becomes reliable and commercially viable. A Demonstration Model (DM) with 2 x GaSb cells was used to tria l the technology in a la boratory and industria l context. The DM was exposed to a range of temperatures from 500 °C to 900 °C using an electric oven. The DM was tested in the cooldown grate of a cement factory where it produced 1.65 kW/m2 at 1083 °C.
In recent decades, the transition from fossil fuels to the use of renewable energy sources has profoundly changed the world’s energy landscape. This in turn has given rise to the concept of energy transition based on the principle of the “three-D’s”, Decarbonization, Decentralization and Digitalization. The emergence of the concept of community energy suggests a “fourth-D”, denoting democratization as a pillar underlying the concept of community energy. This concept is where energy is produced by and for the community, placing the citizen and community at the center as key actors in the entire energy value chain (generation, distribution, consumption, and associated services). This work aims to discuss the social innovation model suitable for the implementation of energy democratization, which leads to the successful penetration of the concept of community energy in developing countries, especially Mozambique, which is a use case study explored in this paper. We explain how this social innovation model can promote socio-economic empowerment, sustainable industrial and human development, and energy inclusion that contributes to environmental balance and social stability in rural communities in Mozambique. The global energy landscape is not uniform in terms of access to energy sources and this debate in developing countries is still relevant and significant, as a considerable number of citizens do not have accessibility to electricity and are still seeking access to it for the first time (energy inclusion). But beyond the social innovation through energy inclusion, we also discuss new innovative modular ways of implementing Distributed Energy Resource (DER) based on typical Photovoltaic (PV) panels and energy storage (batteries). A modular approach for the implementation of smart grids can promote a more cost-effective organic growth, distributing resources more evenly and avoiding oversizing or undersizing of rural electrification systems. Such modularization would also allow new partners or new equipment sets to be added to the infrastructure smoothly. Finally, we suggest the introduction of an AI-based algorithm capable of adapting the smart grid management to new infrastructure modifications (addition of new prosumers or consumers). The algorithm proposed would be able to help control the quality and cost of power for all participants, reduce operation and maintenance costs of the systems, and balance generation and consumption. With that, the suggested modular implementation in conjunction with AI-based smart grid management will provide smart grids that can reduce costs of investment and fair consumption and generation balance that, with time, can promote local sustainable industrial and human development in a virtuous circle to boost social transformation.
Due to the harsh and changeable drilling environment and complex energy flow conditions, it is difficult to obtain an accurate and reliable energy consumption (prediction model. To make up for the above shortcomings, taking into account the advantages of accurate and convenie nt power system measurement, an EC prediction model driven by a combination of mechanism and data is proposed. Based on the deviation b etween actual EC results and theoretical mechanism model calculation results, the least square suppo rt vector machine (LSSVM) data compensation model is established. And the whale optimization algorithm based on von Neumann topology is used to optimize the parameters of the LSSVM model. The experimental results show that the prediction error of the proposed method is 1.69%. Compared with the prediction results of the mechanism model and the data data-driven model, the average prediction error of the proposed method is reduced by 0.27% and 2.9%.
The heavy-duty diesel engines have created effective method to reduce nitrogen oxide (NOx) pollutions with selective catalytic reduction (SCR) system. This study deals with problems in the urea evaporation and decomposition process, the ammonia gas distribution in SCR system and ammonia pattern at inlet of catalyst. The test system used two types of urea injectors, an L-type and an I-type. The ammonia gas value was sampled at the catalyst inlet using a gas sensor. The results elucidate the saturation phenomena, ammonia distribution phenomena, and ammonia value from the two types of urea injectors. The study of effect urea injector was shown at the catalyst inlet by the different chemical mechanisms governing of ammonia concentration distribution in the SCR system.
Biochar draws attention because of its potential for carbon sequestration and long-term sustainability in agriculture by improving soil health and crop yield. In the present research, the carbon sequestration potential of biochar derived from sugarcane residues has been assessed. It was estimated that about 38.8 MT sugarcane top & leaf (STL) and 96.3 MT sugarcane bagasse (SB) are produced in India annually. Out of which, about 47 % STL and 37 % SB remain unused. Surplus STL & SB has an estimated 17.6±0.4 MT biochar potential, sequestrating 18.8±0.4 MT CO2e carbon in the soil. STL & SB-derived biochar application at 10 T/ha could sequestrate 51.9±1 and 47±2.2 MT CO2e carbon due to enhanced crop yield and reduced soil organic carbon mineralization. Also, biochar application at 10 T/ha could reduce about 0.08 MT NPK fertilizer consumption and 0.22±0.13 MT N2O emissions from sugarcane cultivation, having 0.28±0.17 and 65±38 MT CO2e reduced carbon footprint, respectively. Overall, sugarcane residues – biochar system for carbon sequestration could reduce 220.3±45.1 MT CO2e carbon footprint, about 9.5±2 % of total GHG emission from India at the 2019 level. Mapping sugarcane-producing states revealed that Karnataka, Maharashtra, and Uttar Pradesh shared about 75.5 % of surplus STL & SB potential. Andhra Pradesh, Bihar, Gujarat, Haryana, and Tamil Nadu have a 16.5 % combined share in surplus STL & SB potential. The current study’s findings would contribute to creating a sustainable and environmentally friendly system for managing sugarcane residue and increasing the nation’s sugarcane production.
This paper identifies and describes a new but a rapidly growing area of economic and climate governance: International Green Economy Collaborations (IGECs). Examples such as the US-EU Carbon-Based Sectoral Arrangement on Steel and Aluminum Trade illustrate the twin drivers of the emergence of IGECs: green growth imperatives and geo-economics. We argue IGECs are related but distinct from either Green Industrial Policy or Deep Trade Agreements. IGECs are particularly well suited to support green transition by addressing cross-border market failures between partner countries and by facilitating deep cooperation on embedded emissions accounting rules. Their role in bifurcation of the global economy, and its implications for the net zero transition remain to be seen.
Combating Climate Change requires temporally and spatially-resolved atmospheric and solar data planetwide. The Glitter Belt HALE architecture of reflective vehicles serves both as meteorology platforms and as a scalable, reversible option to reduce insolation. The 30.5km altitude and 12-hour night glide requirements, rendezvous and swarm operation for high-precision distributed antenna applications all pose unique challenges, but are shown feasible with the present approach. Conceptual design, small scale design-build-fly tests, and dynamic flight simulation are used to remove uncertainties and derive system properties. Scale-up to reduce atmospheric heat retention is viable in concert with GHG reduction and efficiency improvement measures. Given international will, Global Warming can be controlled in verified, safe and reversible manner that uniquely satisfies all guidance from the National Academies.