The work to be presented is a comparative analysis of deep decarbonization strategies for the natural gas grid. The analysis is based on California supply and demand scenarios and unit costs, but results are broadly applicable to other markets seeking deep decarbonization. To achieve deep reductions in economy-wide GHG emissions, the fuel delivered over the natural gas system must be replaced by zero or near-zero-carbon substitutes. Electrification of many end uses will reduce the need for gaseous fuel over time. However, the least-cost approach to economy-wide decarbonization will likely include continued use of decarbonized forms of methane and expansion of the use of hydrogen for a range of applications. Low-carbon gaseous fuels are well suited for current uses of natural gas, those of conventional hydrogen (predominantly refining and ammonia production) and applications served by liquid fuels. Hydrogen and methane can be decarbonized through production pathways that use renewable energy sources and feedstocks, or through carbon capture and sequestration in geological formations or solid products. The presentation will compare the long-term costs of alternative strategies for decarbonizing the gas grid, including cost of potential transition from natural gas to pure hydrogen. Preliminary results show that decarbonized hydrogen is the most cost effective energy vector to serve zero-carbon gaseous fuel demand in the deeply decarbonized future economy.
In its reports, the IPCC demands new prosperity ideas (i.e., new post-growth economic models (change of lifestyle, institutional innovations and networks of neighbourhood help
)) to solve the climate crisis [2, 3]. Therefore a Keynes sector covering non-market economic activity is modelled in an intertemporal dynamic multinational Computable General Equilibrium model (CGE model) . The CGE model consists of four countries (A, B, C, D) with three economic sectors (Food-Energy-Water (FEW)-sector, public and private service,
industry) each and country D has a derived Keynes sector representing the ideas of the post growth approach .
We discuss the economic effects of our CGE model in a scenario where the countries’ growth rates differ: Country A follows a zero-growth pathway, B and C grow by moderate rates, and country D is on a de-growth scenario. Using the CGE model, we discuss the implementation of a Keynes sector in an open economy with trade relations to the other three countries. This model approach reveals the possible socio-economic consequences and alterations of various growth models for the FEW Nexus sector, as well as the other economic sectors of the four countries.
This research firstly proposed a in situ hydrogen generation to convert glucose to sorbitol via Mg scarification. This process features the utilization of Mg powder as the hydrogen activator, water as the hydrogen source, commercial Ru/C as the catalyst, allowing the hydrogenation to occur under mild reaction conditions without the external supply of hydrogen. Efficient production of hydrogen inside the reaction solvent results in a glucose conversion rate of 96% as well as the sorbitol selectivity of 92% over Ru/C at 110 °C for 2 h. The hydrogenation behavior of this system is examined under the gradient Mg dosage, Ru/C loading, and reaction temperature. A wide application scope has been verified, which containing fructose, mannose, galactose, xylose, and cellobiose. Furthermore, the Ru/C applied in this process can be reutilized successfully without sacrificing its high catalytic activity and sorbitol selectivity. This hydrogenation system makes significant advances by removing the dependence on the external supply of high-pressure hydrogen. This is the first study of a self-propelling, highly active process to highly selective hydrogenation of sugars to polyol under mild conditions, thus providing an economical, safe, and sustainable alternative to conventional hydrogenation methods.
We describe a roadmap, based on a series of workshops and studies, to use base-load nuclear reactors to replace fossil fuels in a low-carbon world that integrates nuclear, wind, solar, hydro-electricity and biomass energy sources. Nuclear reactors with large-scale heat storage enable variable electricity to the grid with nuclear plants that both buy and sell electricity. The low-cost heat storage and assured generating capacity enables efficient use of largescale wind and solar. Nuclear hydrogen production facilities at the scale of global oil refineries produce hydrogen to replace natural gas as a heat source. Nuclear heat and hydrogen convert plant biomass into drop-in hydrocarbon biofuels to replace gasoline, diesel, jet fuel and hydrocarbon feed stocks for the chemical industry. The external heat and hydrogen greatly increases the quantities of biofuels that can be produced per unit of feedstock. The system can produce variable quantities of biofuels and sequestered carbon dioxide that enables negative carbon dioxide emissions and increases revenue if there is a market for removing carbon dioxide from the atmosphere.
Heat, cooling, and ventilation units are major energy consumers for commercial buildings, consuming as much as 50% of a building’s total annual power usage. Management of an air handling system’s energy is a key factor of reducing the energy costs and carbon dioxide (CO2) emissions that are associated with the demand when ventilating and conditioning the air in a building. One issue is that buildings are frequently over ventilated as a full assessment of the air handling unit (AHU) data is not evaluated by building operators. There are multiple variables that account for energy consumption of the AHU which need to be monitored by building operators. In order to assess the demand, it is required that the CO2 levels of the occupied zones be measured, and the outdoor air ventilation rate be adjusted based on real-time CO2. The concept of an energy management system and its characteristics are defined in respect to use with an AHU system. The prototype system used for the research is demonstrated and key data analyzed using real-time data collection. The goal of the research is to assess the number of CO2 sensors needed to accurately measure the demand-based needs for ventilation and provide review of the data required to monitor the AHU energy. Findings indicate that no more than one CO2 sensor would be required for a large lecture hall.
An energy components analysis for stop-to-stop drive segments is provided. In particular, the components of rolling resistance, air drag, and kinetic energy are examined for conventional and optimal segments. It is shown that in energy-optimal driving, the maximum kinetic energy is reached early in the drive segment and then it is converted into work to overcome air drag and rolling resistance; in a sense, it is recovering kinetic energy. In conventional profiles, the maximum speed is attained late in the profile and thus cannot be used to cover much of the air drag and rolling resistance energy cost. The role of the initial acceleration is shown to play a key role, especially for short segments. These results are illustrated through several simulation examples.
Building-integrated photovoltaic (BIPV) technology plays an important role on the path to carbon neutral society. The CdTe-based vacuum PV glazing is proposed to improve the thermal performance of the PV glazing. Therefore, the goals of renewable energy production and energy-efficient building can be achieved at the same time. To fully understand the dynamic heat transfer process and thermal behaviour, this study conducted a comprehensive numerical evaluation based on a mathematic heat transfer model for the CdTe-based vacuum PV glazing. It was found the average dynamic solar heat gain coefficient (SHGC) of the CdTe-based vacuum PV glazing is 0.147 and will increase with the increment of incident solar radiation. The dynamic overall heat transfer coefficient (U-value) varies from 0.451 to 0.467 W/m2K under summer conditions which are higher than which under winter conditions. The solar radiation dominates the total heat transfer compared with the temperature difference in the daytime. The solar radiation and ambient temperature have a negative effect on the PV efficiency and a distinctly positive effect on the outside surface temperature. However, the inside surface temperature is much more stable. A sensitivity analysis was also conducted to investigate the thermal response of the vacuum PV glazing with different design parameters and various environmental conditions. The emissivity of low-e coating is the most effective design parameter. The results indicate that the vacuum PV glazing can perform an excellent thermal insulation performance and contribute to the optimization of the design parameters in future studies.
Investigating the effect of China’s clean coal technology policy on air quality is of great significance for promoting energy transformation and formulating follow-up policies. Utilizing 31 provincial cities data in Chinese mainland from 2013 to 2020, the spatial variation characteristic and change rate of air quality index (AQI) are discussed in this study. Amongst, the AQI in 2020 is predicted by deep learning approaches, to eliminate the uncertainty that COVID-19 bring about. The association analysis between AQI and socio-economic factors is also conducted, to clarify the internal mechanism of clean coal technology policy. The results show that 1) The AQI can be better predicted by the tailored Convolutional Neural Network-Long Short Term Memory (CNN-LSTM) network; 2) the air pollution in China shows an integration trend, embodying heavy and slight pollution in Northern and Southern China, respectively; 3) the clean coal technology policy has an average reduction effect of 18.82% on AQI. And there is a 2-year time lag before the policy takes any strong positive effects; 4) the clean coal technology policy mainly improved air quality through the way of emission reduction and de-industrialization. Practicable policy suggestions are put forward to supporting emission reduction, promoting energy transformation in China and applicable to other developing countries with scarce energy resources and severe air pollution.
Air conditioning systems consume a large amount of energy with the rising living standard of human beings. Indirect evaporative cooler, which is increasingly recognized as a promising alternative to partially substitute conventional air-conditioning devices, has been studied extensively to improve the cooling efficiency and save energy in buildings.
Using porous media in the indirect evaporative heat exchangers is a critical approach for performance enhancement. This paper established a two-dimensional plate-type counterflow indirect evaporative cooler model with porous media on the secondary air channel surface. On the one hand, the porous structure was incorporated in the model to alter the boundary layer and flow status. On the other hand, the water retention ability of porous media that potentially improves the surface wettability has been proven to enable the intermittent operation of the water pump. The influence of various porous parameters, i.e. porosity and pore diameter, on the time-independent dynamic variation of the outlet primary air temperature have been quantitatively analyzed. This study provided a theoretical foundation for the studies of the porous plate-type indirect evaporative cooling technology.
The objective of this paper is to proof that intermittent renewable supply sources can be integrated to develop a reliable baseload plant, which can generate electricity at a competitive cost to the conventional generation. A methodology has been developed to optimize the design of a hybride plant, which is based on several technologies including; solar PV, wind, hydrogen generation/fuel cells, and batteries to serve as a renewable energy baseload plant. The methodology includes site selection to ensure maximum integration among the intermittent supply sources as well as optimized sizing of both generation and storage technologies. The objective function is for the least Levelized Cost of Energy (LCoE). The system reliability is judged using the Loss of Power Supply Probability (LoPSP) criterion. A MATLAB algorithm has been developed for the initial sizing of the system components, which searches for the optimum solution within the applicability domain. This is followed by HOMER software-based optimization technique for the plant operation. A case study for baseload hybrid plant of a capacity 200 MW is presented. The location of the plant is screened among several sites in Egypt to achieve the best optimum combination of both solar and wind generation considering; resource intensity, site conditions and constraints, as well as integration between solar PV and wind outputs. According to the selected site and according to the developed optimization methodology, the system has a combination of renewable generation/storage capacities of; 87.5% wind and 12.5% solar PV, and storage of 75% fuel cell and 25% battery. This injects energy to the grid with an energy mix of 89 % from direct renewable power sources (solar PV & wind), 8 % from the fuel cell, and 3 % from the battery. This energy mix ensures a steady output baseload of 200 MW throughout the year with zero LoPSP, at a LCoE of 8.61 ¢/kWh. Relaxing the LoPSP constraint to 2.5% resulted in 26.83% reduction in the LCoE to 6.8 ¢/kWh. According to this study, renewable energy generation can be used toward achieving 100% baseload power systems at competitive energy cost to the conventional generation.