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Abstract Predicting and optimizing radiative thermal properties have been acknowledged as an efficient way to improve thermal insulation performance of fibrous materials with high porosity. Based on experimental investigation of infrared spectral of ultrafine fibrous insulations with diameters of 520–650 nm, a method of calculating radiative thermal properties was presented by combining Rosseland equation, Mie scattering theory, Beer’s law and Subtractive Kramers–Kronig (SKK) relation. To ensure the calculation correct the uniqueness analysis was performed for Poly(vinylidene fluoride) (PVDF) fibers, which indicated the valid fiber diameter was less than 1.06 μm. The calculated thermal radiative conductivities by using the method agreed well with the measured data. The effect of fiber diameter on the thermal properties of the fibrous insulations was also investigated to minimize the radiative thermal conductivity. The results indicated that the minimized radiative thermal conductivities by regulating fiber diameters could be approximately 25% smaller than those for experimental fiber diameters. The method of predicting and minimizing radiative thermal conductivities of fibrous insulations demonstrated in this paper could be of great advantage to thermal engineering applications aiming to reducing heat loss and saving energy.

In this paper, a numerical method coupling moment method with circuit theory is used to analyze the influence of the grounding material's property on the performance of grounding grids. It can be seen that for a large grounding grid, when the soil resistivity is small, the influence of both resistivity and permeability of grounding material on the performance of grounding grids is great. If the frequency is not very high, the grounding material's resistivity can affect the performance of the grounding grid obviously. If the frequency is very low or very high, the effect of the grounding material's permeability on the performance of the grounding grid is small, while the effect is obvious at other frequency.

As a relatively mature technology, biomass molded fuel (BMF) is widely used in distributed and centralized heating in China and has received considerable government attention. Although many BFM incentive policies have been developed, decreased domestic traditional fuel prices in China have caused BMF to lose its economic viability and new policy recommendations are needed to stimulate this industry. The present study built a regionalized net present value (NPV) model based on real production process simulation to test the impacts of each policy factor. The calculations showed that BMF production costs vary remarkably between regions, with the cost of agricultural briquette fuel (ABF) ranging from 86 US dollar per metric ton (USD/t) to 110 (USD/t), while that of woody pellet fuel (WPF) varies from 122 USD/t to 154 USD/t. The largest part of BMF’s cost composition is feedstock, which accounts for up 50%–60% of the total; accordingly a feedstock subsidy is the most effective policy factor, but in consideration of policy implementation, it would be better to use a production subsidy. For ABF, the optimal product subsidy varies from 26 USD/t to 57 USD/t among different regions of China, while for WPF, the range is 36 USD/t to 75 USD/t. Based on the data, a regional BMF development strategy is also proposed in this study.

This study aims to explore the application of fractional order chaotic system (FOCS), based on the T-S fuzzy model, in the design of secure communication (SC) and this SC system’s role in the construction of efficiency evaluation system for dispatching operation of energy saving and power generation under a low carbon economy (LCE). First, the definition of fractional order differential equations and the stability theory of FOCS are discussed. T-S fuzzy control is introduced to analyse the stability of FOCS. Then, based on the adaptive synchronisation theory, the combined FOCS is designed for SC, and the performance of the system constructed here is analysed in a MATLAB environment. Next, an evaluation index system of the dispatching operation effect of energy saving and power generation under LCE is constructed. The confidential communication system constructed here is used to transmit the index data. The particle swarm optimisation (PSO) algorithm is then used to optimise the back propagation neural network (BPNN) model. The BPNN algorithm based on PSO (PSO-BPNN) is obtained, and the evaluation model is constructed. After training this model, it is applied to the evaluation of the dispatching operation effect for energy saving and power generation in 10 provinces in China. The simulation results show that the FOCS based on the T-S fuzzy model can acquire the criterion of system stability. Furthermore, the constructed SC system can effectively undertake the secure transmission of square and sine waves. The performance of the PSO-BPNN model seems to be better than other algorithms. After analysing the data on energy saving and power generation from 10 provinces in China using this model, the comprehensive evaluation value of province 5 is found to be the highest and good (0.802), while that of province 4 is the lowest and general (0.600). Summarising, the FOCS based on T-S fuzzy model constructed here is applied to the design of SC. This can improve the confidentiality of data transmission and reduce the transmission error. Moreover, the BPNN evaluation model based on PSO can effectively achieve the evaluation of the dispatching operation effect of energy saving and power generation under LCE.

Abstract The kinetics of CO 2 absorption in unloaded aqueous ammonia solution were measured using a string of discs contactor with the aqueous ammonia concentrations ranging 0.9–5.4 kmol/m 3 and temperatures ranging 298.3–321.9 K. The reaction rates strongly increase with the concentration and less strongly with temperature. Both the termolecular and zwitterion models were applied in this study as amine solutions. The parameters for both of the models were interpreted. The kinetic rate constants for CO 2 absorption in aqueous ammonia were compared with those for other amines and were found to be around 1/10 that for monoethanolamine. The fitting results for the termolecular mechanism seem more robust than those for the zwitterion mechanism from a statistical perspective.

Reservoir classification and evaluation are critical during the oil and gas exploration and production, and traditional production forecasting often require complex methods such as reservoir modeling, which is time-consuming and will delay the E&P process. With the rapid development of artificial intelligence technology, the production forecasting method based on machine learning has become a new hot spot for research. Since the characteristics of various reservoirs are different, it is difficult for conventional machine learning models to meet the required accuracy due to a large number of unknowns. In this paper, we proposed an improved hierarchical XGBoost (h-XGBoost) modeling method, which can effectively extract the features of different reservoirs and build a hierarchical data model. The study is conducted on tight conglomerates reservoir at the Mahu area in Xinjiang, and the results verify the effectiveness of the method.

The greatest sustainability challenge facing humanity today is the greenhouse gas emissions and the global climate change with fossil fuels led by coal, natural gas and oil contributing 61.3% of global electricity generation in the year 2020. The cumulative effect of the Stockholm, Rio, and Johannesburg conferences identified sustainable energy development (SED) as a very important factor in the sustainable global development. This study reviews energy transition strategies and proposes a roadmap for sustainable energy transition for sustainable electricity generation and supply in line with commitments of the Paris Agreement aimed at reducing greenhouse gas emissions and limiting the rise in global average temperature to 1.5°C above the preindustrial level. The sustainable transition strategies typically consist of three major technological changes namely, energy savings on the demand side, generation efficiency at production level and fossil fuel substitution by various renewable energy sources and low carbon nuclear. For the transition remain technically and economically feasible and beneficial, policy initiatives are necessary to steer the global electricity transition towards a sustainable energy and electricity system. Large-scale renewable energy adoption should include measures to improve efficiency of existing nonrenewable sources which still have an important cost reduction and stabilization role. A resilient grid with advanced energy storage for storage and absorption of variable renewables should also be part of the transition strategies. From this study, it was noted that whereas sustainable development has social, economic, and environmental pillars, energy sustainability is best analysed by five-dimensional approach consisting of environmental, economic, social, technical, and institutional/political sustainability to determine resource sustainability. The energy transition requires new technology for maximum use of the abundant but intermittent renewable sources a sustainable mix with limited nonrenewable sources optimized to minimize cost and environmental impact but maintained quality, stability, and flexibility of an electricity supply system. Technologies needed for the transition are those that use conventional mitigation, negative emissions technologies which capture and sequester carbon emissions and finally technologies which alter the global atmospheric radiative energy budget to stabilize and reduce global average temperature. A sustainable electricity system needs facilitating technology, policy, strategies and infrastructure like smart grids, and models with an appropriate mix of both renewable and low carbon energy sources.

Abstract Compared with other traditional energy sources, renewable energy, which results the less pollution and has numerous resources, is a significant factor in addressing the current issues of the serious environmental pollution and the resource depletion. Large-scale renewable energy integrated to the grid could bring change in both morphological structure and operation modes of energy transmission. Therefore, it is necessary to research the evolution mechanism of the future transmission network with a high proportion of the renewable energy. In this paper, an evolution framework of power system with high proportion of renewable energy is proposed. Firstly, a network equivalence and simplification based on power transfer distribution factors (PTDFs) is proposed, which can effectively simplify the decision-making process of evolution of large-scale power system. Then, an annual production simulation (8760 h) which takes into account renewable energy and load fluctuations is used to find out the bottleneck of the power grid. Based on the above methods, evolution strategy of power system with high proportion of renewable energy is studied for finding out optimal expansion strategy. A real power system of Zhejiang province is used as a test system. Test results demonstrate the feasibility of the proposed evolution framework.

To unlock the potential of flexible resources, a multi-time-scale economic scheduling strategy for the virtual power plant (VPP) to participate in the wholesale energy and reserve market considering large quantity of deferrable loads (DLs) aggregation and disaggregation is proposed in this paper. For the VPP multi-time-scale scheduling including day-ahead bidding and real-time operation, the following models are proposed, namely, DLs aggregation model based on clustering approach, economic scheduling model considering DLs aggregation, and DLs disaggregation model satisfying consumers’ requirements, respectively. The proposed strategy can realize the efficient management of massive DLs to reduce the energy management complexity and increase the overall economics with high computation efficiency, which indicate its promising application in the VPP economic scheduling.