Herein, the flame structure of a “hybrid fuel” as a mixture of combustible gas and solids in powder form was studied experimentally. A circular burner was used, and a rich premixed flame was achieved. The results showed that the powder underwent high-temperature pyrolysis in the region sandwiched by the inner and outer flames to gasify quickly. The gasification efficiency was estimated experimentally to prove that a sufficient amount of powder could be burned out in this system.
This study investigates numerically the sunrise and sunset transient temperature model that is developed for modeling sunlightâ€™s temperature in designing latent heat thermal energy storage system (LHTESS), to close carbon cycles. It was used as a model for the threedimensional conjugate phase change material (PCM) melting procedure in the thermal storage of a 500K-rated concentrated solar power (CSP) plant using computational fluid dynamics (CFD) code. Air is the heat transfer fluid (HTF). Two transient solar temperature models and an isothermal model were studied and compared. The reduction in the expected storage time and increased energy storage greatly improved the system’s efficiency. The numerical model results were substantiated by experimental evidence from the open literature.
The simulation of TEM images is computationally difficult. However, in the limit of completely amorphous materials, it can be simplified to the mass-thickness contrast only, neglecting any diffraction. Our method allows fast creation of TEM images of char models and allows to find an optimal viewing angle. The intention of our char models is to investigate the stacking and bending of graphitic carbon systems. To count the planes of a stack and determine the plane length and curvature one needs specific angles to create the TEM image. A good angle gives a high contrast between carbon layers. In this paper, we show TEM simulations of four different carbon structures.
The interaction between H2 and electricity systems increases system energy flexibility and renewable penetration with mitigation on the grid power pressure, where the hydrogen-fuel-cell vehicle is the key component during the interaction process. However, the low energy efficiency of the electricity-H2-electricity conversion will cause massive energy loss, thus leading to an increase in operational costs and equivalent CO2 emission (ECE). This study aims to develop systems with different degrees of synergistic collaboration between battery and hydrogen energy systems by applying three hierarchical control strategies, to investigate the impact of the hydrogen-based building-vehicle network on the operational costs of the whole community and HV owners, and ECE of the whole energy network. In addition, the system also considers a variety of renewable sources, low-grade heat recovery from electricity-to-H2 and H2-to-electricity conversions, the degradation of fuel cell (FC), and multi-stage grid electricity price. Results indicate that compared to the reference case without V2B/B2V, the annual total operational costs of Case 1 (V2B/B2V interaction with first charging/discharging priority given to electric battery) and Case 2 (V2B/B2V interaction first charging/discharging priority given to FCEVs) increase by 2.35% and 17.43%, but the operational costs of HV owners are reduced by 6.76% and 36.19%, respectively. Research results can provide frontier guidelines on development of synergistic battery-hydrogen network for renewable sharing and energy use in buildings and fuel cell electric vehicles.
Energy communities are considered a key element in the transition towards more sustainable energy systems. Indeed, the final consumers are encouraged to form communities to share the locally produced renewable electricity. In such a prospective, this work proposes a novel Mixed Integer Linear Programming formulation for the design optimization of energy communities: given a set of buildings/prosumers of a district, the model allows optimizing the number of energy communities and the selection of prosumers/buildings to be included in each community with the objective of maximizing the economic or energy benefit for the whole district. The proposed model is applied to a case study of a district with 40 prosumers and results are critically analyzed.
CO2 storage in deep saline aquifers is a promising technique for carbon neutrality. Accelerating the dissolution rate of dissolution trapping is key to improving storage efficiency and providing long-term storage security. In this study, density-driven convection processes were conducted using magnetic resonance imaging (MRI) with two analog fluid pairs as equivalents of the CO2-brine fluid system. Superhydrophilic SiO2 NPs with different mass fractions (0 wt%, 0.1 wt%, and 1 wt%) were added to the dense fluid to investigate the optimum mixing ratio. The basic fluid interface instability is identified. The addition of nanoparticles shortens the onset time of instability and increases the finger numbers in each axial section. It shows that dense fluid with NPs leads to more stable interface behavior. Furthermore, experimental results confirm that a reduction in surface tension between NPs and CO2 would enhance fluid miscibility and mass transfer during convection. This study can expand the perspective on accelerated dissolution rates and CCS security in the substance.
The reversible thermochemical reaction between magnesium hydroxide and magnesium oxide is recommended for storing heat energy in the middle temperature range of 300-500 oC. However, the low hydration rate of magnesium oxide limits the heat storage performance for practical applications. In this study, the nano-porous carbon supported composite was prepared by calcination method for improving the heat storage performance. The hydration and dehydration experiments were carried out. The results show that the overall heat storage density of composite can be improved to 1053 kJ/kg, which is 1.4 times that of pure material. Compared with other experimental results, the heat storage density of the composite has been improved by more than 30%.
In Chile, the government presented the National Green Hydrogen Strategy, which will allow the export of this renewable fuel created with zero-emission energy, a positive contribution to carbon neutrality. This study addressed the possibility of integrating a green hydrogen value chain in the port sector. The study focused on generating electricity from photovoltaic solar energy to produce enough hydrogen in electrifiers to power a fuel cell that generated electricity and residual heat. Two scenarios were calculated for hydrogen generation depending on the solar energy available to cover an electrical and thermal demand in ports 1 MWhe and 0.1 MWht, respectively. For this purpose, the Calliope tool was utilized for energy system sizing. Furthermore, it was determined that the cost of 1 kgH2 is 4.1 times higher than that of 1 liter of diesel to obtain the same 1 MWhe. Similarly, the Levelized Cost of Energy was calculated for two operating conditions.
In order to avoid catastrophic climate change, the world is currently involved in an ambitious energy transition. In this great transition, fossil-based fuels are to be replaced with intermittent renewable energy. Science will provide the â€œknow-whyâ€ but the ultimate success will be dependent on combining this with the engineers â€œknow-howâ€. This paper aims to bring light to what capabilities the engineer discipline has with regards to subsea engineering with a focus on subsea structures so that the scientific community can make use of it when researching new subsea storage concepts. Novel ideas for design of subsea hydropneumatics energy storage concepts adapted from the oil and gas industry including a justification for them has been reviewed and presented in the paper. Although publications around subsea hydropneumatics energy storage solutions exists there are few, if any, related to design considerations.
The purpose of this study is to conduct data mining research on building time series energy consumption data set. Research done so far mainly focused on cluster analysis. In this research, python language is used as the carrier, K-shape algorithm is adopted to perform cluster analysis on the time series energy consumption data from the perspective of time series. By analyzing the characteristics of its time series changes, the corresponding energy consumption patterns are obtained, and then corresponding energy saving measures are proposed to complete the construction of the entire method system. The final results show that the energy consumption curve obtained by clustering algorithm can effectively reflect the operation characteristics of the building. At the same time, based on the principle of peak cutting and valley filling, the energy consumption curve can be adjusted according to the characteristics of different modes, so that the building can effectively achieve the effect of energy saving.