To explore the relevance of battery inconsistency parameters and evaluate the cells inconsistency in Lithium-ion battery module. A comprehensive evaluation method of cells inconsistency in Lithium-ion battery module is proposed. Experimental tests for 8 series battery cells have been carried out to obtain the inconsistency data including internal resistance, voltage, capacity. An inconsistency evaluation model taking internal resistance, voltage and capacity as the inputs is established by using the information entropy-grey relational analysis (GRA). The inconsistency of 8 series lithium-ion cells is comprehensively evaluated by the proposed model under the conditions of accelerated aging experiment at 25 °C and 3C rate. The results show that the proposed method can evaluate the cells inconsistency and identify cells inconsistency feature distribution.
Concerting renewable energy into hydrogen and transporting it to the end of consumption is the promising choice to achieve large-scale deep decarbonization in transportation sector. Based on this, this paper constructs a large-scale centralized renewable energy hydrogen supply chain (HSC) network model to investigate the lowest cost of three different green hydrogen supply pathways, including production, compression, storage, transportation, and utilization. The fluctuation of wind power, solar power, and hydrogen fuel demand are integrated in the model, which is optimized by dynamic programming. Different production and delivery pathways are evaluated to find the least-cost way for transport hydrogen utilization. Applying the model to China’s Western Inner Mongolia
(WIM) region, the HSC network plan in 2030 was established. The results show that the least-cost hydrogen supply is to produce hydrogen by wind power and to transport it in liquid hydrogen by truck. This study provides guidance and reference for the future planning and design of green HSC network in other countries or regions.
In the European Union, power production by means of coal has been phased out in the context of the efforts to decarbonize the economy and become carbon neutral by 2050. This trend has a big impact not only in regions where coal is produced, but also in those regions where coal-fired power plants are located. It is not always the case that coal-fired plants are located where the coal is extracted, sometimes they are located in the nearby of harbours were imported coal could arrive. In our view, both can be designated as “coal regions”. Phasing out coal has an impact on the economy of those regions, in general, and on jobs, in particular. In this paper, we analyse the various instruments designed by both the European Union and Spain to compensate the damaged experienced by coal regions. These compensations are considered to be part of the so called fair (or just) energy transition.
In Section 1 we briefly explain the former legal framework for aids to the coal sector in the European Union. In Section 2 we analyse the recently created Just Transition Fund, and in Section 3 we examine the Spanish coal sector as well as the recent 2021 Spanish Act on Climate Change and Energy Transition, in particular its provisions about the fair (or just) transition which has a particular focus in the future of those regions were coal-fired power stations were located. We explain how the Spanish policy has shifted in this area. In Section 4 we briefly summarize the foreseeable conclusions of our research.
As China pledges to achieve carbon neutral by 2060, provincial mitigation routes and plans are carried out in succession. Severe aging in demographic structure will impact future carbon emission and influence the effectiveness of low carbon policies, with shifting consumption pattern induced by age structure changes, age-different respond in low-carbon policies, shrinking labor supply. Current researches on China’s new mitigation pledges did not consider the impact of demographic changes. This study used a multi-regional CGE model with detailed household agents and found it necessary to consider the effects of aging in simulation. In extreme scenarios, there are 20% decrease in emission and 17% drop in economic output comparing with traditional scenario without taking aging into account. The implementation speed of delayed retirement faces a trade-off between economic development and emission reduction costs.
Soot formation is an important issue in the design of modern wood stoves, as soot not only deteriorates the combustion efficiency but also poses threats to human health. Although soot formation in biomass combustion has been studied previously, the investigation at wood stove level is still rare due to its complex nature. In this paper, a preliminary numerical simulation is carried out to uncover the basic trends of soot formation during wood log combustion. The soot formation model is developed based on a virtual particle multiphase flow algorithm, where the mass fraction and the particle size of the soot are both resolved. Three wood logs combusting in a confined wood stove with a parallel stacking is studied. The coupling effect of the soot formation with the heating and the combustion of the wood logs is analyzed. This work is helpful for the design and the optimization of modern wood stoves. The predicted soot mass fraction and size distribution provide important information for a better control of particulate matter emission.
With global pollution and building power consumption on the rise, energy efficiency research has never been more necessary. Accordingly, data visualization is one of the most sought after challenges in data analysis, especially in energy efficiency applications. In this paper, a novel micro-moment Gramian Angular Fields time-series transformation of energy signals and ambient conditions, abbreviated as M2GAF, is described. The proposed tool can be used by energy efficiency researchers to yield deeper understanding of building energy consumption data and its environmental conditions. Current results show sample G2GAF representations for three power consumption datasets. In summary, the proposed tool can unveil novel energy time-series analysis possibilities as well as original data visualizations that can yield deeper insights, and in turn, improved energy efficiency.
By coupling electricity and district heating (DH) networks, so-called energy hubs (EH) are generated. Those have the potential to include more renewable energy sources, depending on local conditions regarding supply and demand. This paper presents a novel approach by matching the heat demand of residential and commercial buildings with local renewable heat sources and by considering the development of the building stock with the spatial and capacitive DH potential through the aid of a geographic information system-based analysis for the Swiss Canton of Zurich. By identifying suitable DH areas, primarily supplied by non-renewable energy carriers, are assigned to renewable heat sources. This method allows to explore the possible bandwidth and key factors of the potential for future scenarios until 2050, related to developments of DH technology and policy efforts regarding buildings directives. The results show that high-temperature (HT) DH could be doubled, and that the EH potential is quantified at 3.75 TWhth/a for 2020 (five times the current value) and 3.25 TWhth/a for 2050, in the same scenario.
To meet global energy demand, photovoltaic (PV) energy technologies should be rescaled and upgraded. A facile way is to head towards underwater PVs to create stable and reliable renewable energy sources in the aquatic regime. Current work comprehends an experimental study on the behavior of solar radiation and the performance of amorphous silicon (a-Si) solar cell in diverse underwater conditions. The main focus of the study is to investigate the impact of water turbidity on insolation power and device performance at various depths. Both the irradiance power and the cell performance showed an inverse correlation with the water turbidity. The turbidity values for the lowest turbid double distilled water (DDW), low turbid lake water (LTLW), and high turbid lake water (HTLW) were measured to be 0.1 NTU, 2.5 NTU, and 6.6 NTU respectively. Also, a percentage drop in solar irradiance at a depth of 20 cm for different water types was captured.
The metal-organic framework UiO-66 is a promising water vapor adsorbent in the application of adsorption heat pumps due to its good stability and hydrophilicity. In this paper, we prepared some pure and Cr-doped UiO-66 samples by the traditional solvothermal method and microwave-assisted solvent synthesis method, respectively. And we characterized these samples by XRD、FTIR、BET, etc. The results show that the micropore volume and BET specific surface area of UiO-66 synthesized by the microwave-assisted method is much higher than those synthesized by the conventional solvothermal method. In particular, MW-1.5Cr-UiO-66 synthesized by microwave method has the highest BET specific surface area (1524m2/g) and water uptake (0.59g/g), which is 105.4% and 47.5% higher than UiO-66 synthesized by solvothermal method, respectively. This is more conducive to the application of UiO-66 in the field of adsorption heat pumps.
Transport is one of the major contributors of greenhouse gas (GHG) emissions. In Latvia 29.8 % from GHG emissions come from transport. Often the influence of it is measured only from air pollution, mainly CO2 emissions and health effects caused by them, perspective, not considering other external costs associated with it. In this paper, external costs from passenger cars are calculated for Latvia’s current situation. These costs include air pollution, climate change, noise, and well-to-tank analysis. Current situation costs were then compared to different scenarios of battery electric vehicle (BEV) mix in Latvia’s passenger car fleet. The results indicate that having a higher BEV mix in the fleet reduces external costs.