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To understand whether the optimization of the operating/electrode structural parameters are temperature dependent, a 3D numerical model is developed and validated to gain insight into the impact of practical operating temperature (273.15 K–323.15 K) on vanadium redox flow battery (VRFB) performance, in which the property parameters are from published experimental data. The operating temperature is found significantly influence the optimal design of VRFBs. Increasing the inlet flow rate and state of charge (SOC), decreasing the electrode porosity and fibre diameter can all improve the battery performance with interdigitated flow channels, and the improvement increases with increasing temperature. In contrast, decreasing the fibre diameter or porosity increases the flow resistance and costs higher pump consumption, which is more pronounced at a lower temperature due to higher electrolyte viscosity. The effect of electrode thickness is also different at various temperatures. The gradient porosity electrode is applied in VRFB with interdigitated flow channels. The electrochemical performance of VRFB with gradient electrode (porosity increases from 0.8 at channel side to 0.93 at membrane side) performs similarly with the VRFB with 0.8 porosity electrode, while the pressure drop is reduced by 40% at all temperature. This model provides a deep understanding of effects of a wide range of working temperature on the optimization of operating/electrode parameters and on the VRFBs' performance. • 3D model is established for VRFB concerning the temperature effects. • Effects of operation and electrode parameters on VRFB changes with temperature. • Pressure drop increases with increased VRFB performance of traditional electrode. • Gradient electrode design reduces pump loss while maintaining battery performance. [ABSTRACT FROM AUTHOR]

Strategic petroleum reserve (SPR) and alternative fuels are both important for energy security. In this paper, a quantitative energy security model is proposed to calculate the optimized scales of SPR and alternative fuels (e.g., coal-converted methanol). The coordinated model mainly focuses on cost-benefit analysis, including the economic costs of SPR and alternative fuels, and the benefits for ensuring energy security. Demonstrating examples in China have been analyzed, and it shows that SPR and alternative fuels have coordinated effects in ensuring energy security, while alternative fuel is a supplementary method for reducing the negative effects of the raise of oil price and related economic losses. By the end of 2030, the net present value (NPV) will be considerably large with 150–200 million tons of SPR and 50–100 million tons of alternative fuels in China. Quantitative sensitivity analysis have been introduced for optimum scales and net present value (NPV) of SPR and alternative fuels, demonstrating that GDP/oil price elastic coefficient, domestic production of oil and investment of alternative fuels are key parameters for energy security. This model provides a quantitative method for the evaluations of the national energy security strategy. [ABSTRACT FROM AUTHOR]

Convection heat transfer characteristics in a single rock fracture was experimentally investigated in this work. Distilled water was used as working medium for heat transfer in manmade smooth and rough fractures of sandstone and granite samples. The influence of fracture surface roughness on heat transfer intensity was analyzed. During seepage heat transfer process, evolution of samples external surface temperatures was monitored using six resistance temperature detectors to study the local heat transfer characteristics along the flow direction. Subsequently, heat transfer correlations were proposed on the basis of the experimental results. The results indicate that the roughness of rock fracture surface improves the overall heat transfer intensity to a certain extent, whereas lithology has little influence on the heat transfer intensity. For smooth fractures, the local heat transfer intensity decreases with the increase of the distance from the inlet. For rough fractures, evolution of sample external temperatures along the flow direction exhibits strong nonlinear characteristics with multiple peaks. Nu/Pr 1/3 is close to a power function of Re under the experimental conditions in this work. With the increase of experimental temperature, the relationship gradually tends to be linear. [ABSTRACT FROM AUTHOR]

Protonic ceramic fuel cells (PCFCs) are promising electrochemical devices to achieve power-ethylene cogeneration. A model of a tubular C 2 H 6 -fed PCFC, including an internal reforming section (IRS) and an electrochemical reaction section (ERS), is constructed to investigate the effects of structural parameters on the cogeneration performance. Increasing cell length and ERS markedly enhance the ethylene yield. The highest ethylene yield of 44% is obtained in a 10 cm PCFC at 973 K. The positive effect of thickening the entire anode or IRS on yield is not as pronounced as extending the cell length or ERS. Except that the increase of IRS thickness leads to the decrease of the current density, the increase of other structural parameters causes the current density to increase first and then decrease. By decreasing the ERS ratio, the current density can be enhanced up to 14% and reaches the highest value of 2235 A m−2 at 973 K in an 8 cm PCFC with a 30% ERS ratio. This model provides an insightful understanding of the interrelationship between the structural parameters and the cogeneration performance of PCFC. This model can also serve as a valuable tool for the PCFC fuelled with other hydrocarbons. • A 2D asymmetric model for tubular C 2 H 6 -PCFC is constructed. • The effects of structural parameters on PCFC performance are quantitatively studied. • Increasing cell length by 1 cm can enhance ethylene yield by 12.5%. • Increasing ERS ratio by 10% can enhance ethylene yield by 7.7%. • Increasing IRS thickness by 100 μm can decrease current density by 6.3%. [ABSTRACT FROM AUTHOR]

Renewable energy plays a crucial role in clean energy transformation and emission mitigation. It's, therefore, necessary to understand the trend and factors affecting renewable energy distribution and disparity across countries. This paper investigates the development pattern of renewable energy worldwide. It depicted a distributional picture of the world renewable energy using a club convergence algorithm, to form 5 clubs with 78 economies based on the renewable energy generation during 2000–2018. China, the United Kingdom, and the United States are the top economies in renewable energy generation. And most of the economies are in the clubs with less renewable energy generation. With the Dagum Gini coefficient and decomposition method, it is found that the disparities of renewable energy between clubs are increasing, while the disparity within each club is decreasing. Affluence, demand for energy, technology level, industry and population structure are the factors determining the club according to the result of the ordered probit model and the fixed-effects panel regression model. Target recommendations are proposed for international policy formulations on renewable energy based on the results. • The economies were divided into Clubs by renewable energy power generation. • The difference within and between Clubs was calculated by the Dagum Gini coefficient. • Factors that affects renewable energy power generation were identified. • Target policy implications were come up with. [ABSTRACT FROM AUTHOR]

While most of previous studies on China's energy conservation took the huge country as a whole, this manuscript revealed the obvious regional disparities in energy consumption of China's 30 provinces. Based on a hybrid energy input–output model, the total energy consumption of different regions was decomposed and compared using three measurements of embodied energy in inter-regional trade: 1) only considered inter-regional energy trade; 2) considered embodied energy in flow-out of final goods and services; 3) considered embodied energy in flow-in of final goods and services. Based on the second and third measurements, the 30 regions were categorized into four groups by their energy intensity and per capita GDP (gross domestic production). Common characteristics of decomposed regional energy intensity are discussed, and policy implication for regional energy conservation is provided. For developed regions with low energy intensities, such as Shanghai, energy conservation should focus on promoting low energy-consuming life style. For under-developed regions with low energy intensities, such as Guangxi, economic development is more urgent than energy conservation. For developing and energy absorbing regions, improving energy efficiency in industries is significant. For developing and energy exporting regions, transforming primary energy into high value-added products would be beneficial for economic development and energy conservation. [ABSTRACT FROM AUTHOR]

In this paper, the feasibility of generating electricity from EGS (enhanced geothermal systems) by oilfield produced water circulating through reservoir stimulated by staged fracturing technology for horizontal wells is investigated based on the geological data of Xujiaweizi area, located in the Daqing Oilfield, northeast China. HDR (hot dry rock) resource potential assessment is carried out by using volumetric method. Reservoir stimulation is numerically simulated based on the geological data of well YS-1 and field fracturing experience in this region. Geometric dimensions and flow conductivity of the resulting fracture are imported into the hydro-thermal model to calculate the electricity generation potential of the proposed EGS power plant. An EGS design scheme is proposed based on the simulation results. The system is also evaluated from the economic and environmental aspects. The results indicate that HDR resource in Xujiaweizi area is of great potential for development. Through the staged fracturing technology for horizontal wells, electricity generation power of the proposed EGS project can roughly meet the commercial standard. For 20 years of continuous production, power generation from the proposed EGS power plant is economic feasible. Meanwhile, significant reductions in greenhouse gas emissions can be achieved. [ABSTRACT FROM AUTHOR]

We use a variant of machine learning (ML) to forecast Australia's automobile gasoline demand within an autoregressive and structural model. By comparing the outputs of various model specifications, we find that training set selection plays an important role in forecasting accuracy. More specifically, however, the performance of training sets starting within identified systematic patterns is relatively worse, and the impact on forecast errors is substantial. We explain these systematic variations in machine learning performance, and explore the intuition behind the 'black-box' with the support of economic theory. An important finding is that these time points coincide with structural changes in Australia's economy. By examining the out-of-sample forecasts, the model's external validity can be demonstrated under normal situations; however, its forecasting performance is somewhat unsatisfactory under event-driven uncertainty, which calls on future research to develop alternative models to depict the characteristics of rare and extreme events in an ex-ante manner. • It examines the role of training set selection in demand forecasting. • It relates systematic variations in forecasts to structural changes in the economy. • It explores the economic intuition behind the 'black-box'. [ABSTRACT FROM AUTHOR]

Coal will continue to dominate the energy structure for a long time, however, the severe environmental issues require that coal should be cleanly and efficiently utilized. This work proposes to carry out integrated research on the optimization model of the coal and new energy-based industrial structure at the enterprise level. To meet the low-carbon requirements, a multi-objective superstructure optimization model of the coal and new energy-based energy structure under a variety of constraints is constructed, while the carbon emissions and total profits are selected as the objectives simultaneously. Then a case study is conducted with the industrial structure of a representative energy company as the study object. Via self-developed mixed programming to achieve the optimal solution of Pareto-frontier, this study analyzed the energy industry adjustment and layout optimization under three different scenarios. The turning point with the emission reduction rate of 2 % is recommended as the optimal choice under the baseline scenario, and new energy power generation has become a new growth point of the group's profits after adjusting the investment structure. Comparisons between the coal and new energy power generation prices will seriously affect the optimization and prediction results of the low-carbon scenario. The annual profit in 2020 will decrease significantly under the epidemic situation, but the change rules of emissions and profits are basically consistent with the baseline scenario. The research methods and quantitative results could be generalized for relevant comprehensive energy companies to adjust their strategic layout and make plans. • The multi-objective superstructure optimization model and method are constructed. • Quantitative case analysis of China Energy's industrial structure is carried out. • Three scenarios are set to analyze the optimization impact of multi-factor changes. • Corresponding suggestions for industrial structure adjustment by 2025 are proposed. • The proportion of new energy power generation installed could be above 27 % in 2025. [ABSTRACT FROM AUTHOR]

Abstract: A new concept of ‘low-carbon towns’ (LCTs) has emerged in the urban planning and development of China in recent years to face the challenge of global climate change. This manuscript presents the current status, basic concepts, and town practices for the development of LCTs in China. First, we summarize the driving forces and regional activities for the development of LCTs in China; then, we introduce the town types and related programs. We propose the definition of a Chinese LCT and the main approaches to developing Chinese LCTs through a system analysis revealing what they are and how they may be developed in a Chinese context. The proposed approaches to develop Chinese LCTs include economic, social, layout, technology, and reuse approaches, each of which is introduced in the context of typical town planning and management in China. [Copyright &y& Elsevier]

Abstract: This paper analyzes the technical, economic, and environmental characteristics of different pathways for supplying hydrogen to vehicles in China. A life-cycle accounting of “well-to-tank” hydrogen delivery for 11 different infrastructure pathways reveals different relative economic costs and environmental benefits. Coal-derived methanol as a hydrogen carrier appears particularly promising for China from an economic standpoint. The analysis considers three different infrastructure models: (1) “point-to-point” distribution from well to fueling station; (2) an “idealized city model” with radial and network distribution within a city grid; and (3) a model of Beijing infrastructure growth that evolves over time. The analytical results, the infrastructure models, and the practical case of Beijing provide policy-makers with new tools for hydrogen development strategies. [Copyright &y& Elsevier]

Integrated energy systems offer substantial potential for enhancing renewable energy integration. However, due to the distinct dynamic characteristics between system components, the characterization of system flexibility in integrated energy systems remains a challenge. This further complicates their optimal design, as underestimation or overestimation of flexibility during design can result in unexpected operational performance degradation. This article aims to improve the accuracy of system flexibility characterization in the optimal design of an integrated energy system, and address the conflict between high-precision modeling requirements and the difficulty of solving high-dimensional optimization problems. Specifically, higher temporal resolution operational constraints are adopted to characterize system flexibility, and a variable temporal resolution optimization method is developed, which could effectively reduce computational burden whilst maintaining accuracy. Optimization results demonstrate a significant reduction in solving time, approximately 98.5 %, compared to directly shortening the time step. Moreover, the proposed method ensures optimal results with a reliable system configuration, preventing load loss during operation. Additionally, it significantly reduces total ramping amount and adjustment times of coal-fired units by over 56.0 % and 32.3 % respectively, while achieving a 0.9 % reduction in carbon emissions. Despite these benefits, the total annual costs of the system only experience a minimal increase of 0.6 %. • A variable temporal resolution optimal design method for integrated energy systems is developed. • The dynamic characteristics of various system components are distinguished. • The method enhances the model accuracy whilst reducing the computational complexity. • System layout obtained by the method has better reliability, safety, and lower carbon emissions. [ABSTRACT FROM AUTHOR]

Based on the finite line source (FLS) model, A heat transfer model considering both multilayer soil and multiple Borehole Heat Exchangers (BHEs) is proposed. The accuracy of the model is verified by experiments. The model is used to study the effect of thermal physical properties of multilayer geological media on the overall thermal efficiency of multiple BHEs. The dimensionless regional thermal efficiency (E) is introduced as an evaluation index of heat transfer characteristics of multiple BHEs. Under a certain geological structure, the heat transfer efficiency of multiple BHEs in homogeneous soils and multilayer soils were compared with the analytical model. The results show that the E of the multilayer multiple BHEs model is less than that of the homogeneous multiple BHEs model, with the maximum difference being 11.43% in 2,000 h. With these thermal properties and soil layer structure, the rate at which E decrease for the multilayer model is a factor of 4 higher than that for the homogeneous model. In the soil layer where the thermal interaction is the most intense, the unit Heat Transfer Rate (HTR) decreased by 25.3%. At a fixed spacing, the thermal diffusivity is the key to determining the degree of thermal interaction. Under the 4 × 4 BHEs layout, the dynamic performance loss increases by about 4% for every 1 × 10−7 m2/s increase in soil thermal diffusivity. When the multiple BHEs are in a multilayer geological media with a large difference in thermal properties (especially thermal diffusivity), a comprehensive multilayer analysis is needed to obtain the thermal efficiency of the overall multiple BHE area accurately. The multilayer multiple finite line source model can be used during the engineering design stages of a BHE field to predict the regional thermal efficiency with borehole spacing and the number of boreholes. • A multilayer finite line source model considering multiple BHEs is proposed. • The accuracy of the model is verified by experiments. • Multilayer soil with large difference has a greater impact on thermal efficiency. • Dynamic performance loss with different thermal diffusivity are analyzed. [ABSTRACT FROM AUTHOR]

Coal power plants are crucial in both the power sector and central heating sector and also emit large amount of carbon dioxide. Existing research on coal power plants transformation mainly focused on their role in the power sector, with insufficient attention paid to their heat and power cogeneration capabilities. To address this gap, this paper proposes a long-term expansion joint optimization model for power sector and central heating sector incorporating the competitive technologies in both sectors, which is used to obtain the optimal low-carbon transition pathway of power sector and central heating sector, and analyse the pathway of coal power plants. China is selected for a case study for its largest scale of existing coal power plants in the world and urgent need of decarbonization. Compared to the scenario only considering electricity generation function from coal power plants to power sector, another scenario also considering the heating production to central heating sectors brings less than 5% increase in their remaining capacity, whilst results in significant changes in their regional distribution. Proportion of heat and power cogeneration of coal power plants in the heat generation structure is expected to increase first to 80% in 2030 and decrease to 58% in 2055. • A long-term optimization model for sectors of power and central heating is built. • Impacts of considering heating sector on coal power plants paths are quantified. • Proportion of coal power plants in total heat production increases to 80% in 2030. • Electric heat pumps are developed rapidly for negative carbon emission constraint. [ABSTRACT FROM AUTHOR]

The previous neglect of shale oil multi-component characteristics and the nanpore wall properties of real shale result in an insufficient understanding of shale oil flow mechanisms in nanopores. Meanwhile, research on the flow regimes of shale oil remains lacking. In this study, molecular dynamics simulations are employed to investigate the flow of shale oil in hydroxylated quartz nanopores and rough kerogen nanopores. Simulation results show that the flow regime changed as the pressure gradient (∇ p) increased to a critical value (∇ p c). The velocity profile was parabolic when ∇ p < ∇ p c , but gradually became piston-like when ∇ p ≥ ∇ p c. Because increasing ∇ p leads the adsorbed molecules desorbing, aggregating in the pore center, and forming clusters that are not easy to shear. Increasing vertical force from pore wall causes fluid aggregation in the pore center as ∇ p increases. The ∇ p c in kerogen nanopores is larger than that in quartz nanopores due to the rough kerogen surface and sticky layers. Multi-component fluids have higher ∇ p c than single-component fluids in quartz nanopores. However, they have the same ∇ p c in kerogen nanopores due to the rough kerogen surface. This investigation can provide theoretical basis for high-efficient production of shale oil. [Display omitted] • The flow regime of multicomponent shale oil in rough nanochannels was studied by MD. • Critical pressure gradients exist for fluid flow regime transitions in nanopores. • Determined governing factors of velocity profile changing from parabola to piston. • Determined governing factors of critical pressure gradients. [ABSTRACT FROM AUTHOR]

High energy consumption remains a challenge for the amine-based post-combustion CO 2 capture in thermal power plants. Process intensification is a feasible way to reduce heat requirement effectively in a CO 2 capture process. In this work, we propose a hybrid post-combustion CO 2 capture process configuration, aiming at lower energy consumption compared to conventional ones. The proposed process configuration features a pre-concentrating membrane, an intercooler, a rich solvent split configuration, and an air stripper. Typical aqueous monoethanolamine (MEA) with 30 wt% concentration is selected as absorbent. A rigorous rate-based method with corresponding thermal dynamic and chemistry models are employed to calculate the performances of the proposed CO 2 capture process in Aspen Plus. Impacts of single process intensification configuration are analyzed separately to identify quantitative contribution of each of them to the overall performance improvement. Five different processes are presented and the reboiler duty can be reduced to a minimum in the last process due to the combination of the four configurations. Results show that a reboiler duty as low as 2.5 MJ/kg CO 2 can be achieved by parametric optimization, which is 28% lower than that of conventional processes, leading to a reduction of 1.9% points in net power efficiency penalty. [ABSTRACT FROM AUTHOR]

Wide-range and frequent operation changes have become a common phenomenon with thermal power plants in the context of fast penetration of intermittent renewable power. Performance monitoring at transient states is more important to the safety and high efficiency of power plants. Data quality is essential for conducting dynamic performance monitoring, and dynamic data reconciliation (DDR) provides great potential to enhance quality of measured data at transient states. In this paper, a moving window based approach to dynamic data reconciliation is proposed for a real coal-fired power plant using high sampling operational data. Firstly, dynamic characteristics of the system are discussed, taking account of the equipment accumulation in DDR problems. Results of case studies indicate that the data accuracy of measured mass flow parameters are enhanced effectively after DDR, and better results are obtained with the increasing time window size. Comparison with steady state data reconciliation approach is also carried out to indicate the enhanced effect of the DDR approach for the performance monitoring of a real power plant. [ABSTRACT FROM AUTHOR]

Improving energy efficiency is one of the most reliable ways toward carbon neutrality. Most previous studies have focused on how to reduce energy intensity; however, it is not enough to provide an overview of how many carbon emissions can be reduced by technical efficiency improvements underlying energy systems. To fill this gap, this study extended the common Kaya identity to systematically evaluate the carbon reduction potential from technical efficiency improvements of various technical conversion components within the energy system at a granular level. The extended Kaya identity includes technical efficiency factors of electricity efficiency, conversion efficiency, and passive efficiency. It provides a comprehensive framework to evaluate current performance, historical contributions, and future potential of technical efficiency improvements. The case of China reveals that: Currently, only around 5% of energy sources were delivered to final services. By improving technical efficiency to high levels, 59% carbon reduction can be achieved during the future energy transition, even when the economy is still growing. In the past, electricity efficiency and conversion efficiency have significantly reduced carbon emissions. Future policymakers should pay more attention to passive systems to provide more final services, such as improved room insulation, streamlined vehicle designs, and smart energy management. • Proposed an extended Kaya identity framework for the systematic evaluation. • Evaluated the role of technical efficiency improvements at the most granular level. • 59% carbon reduction by improving technical efficiency during energy transition. • Passive systems highlighted for more carbon reduction potential. • Strongly promoting technical efficiency improvements in China's carbon neutrality. [ABSTRACT FROM AUTHOR]

As a core equipment for energy conversion and clean utilization, gas turbines are utilized in many areas under various ambient conditions. Ambient conditions can vary with seasons and time of a year, even in the same location. Ambient conditions also have significant impacts on gas turbine performances at part-load. In this paper, we proposed an off-design behavior mechanism model of gas turbines, which aims at quantifying impacts of ambient conditions on gas turbine performances. Impacts of key parameters are considered, including compressor geometry, staged combustion in a combustor and turbine cooling. Moreover, an operation windows analysis is presented. In order to illustrate variation logics of NO x emissions, load regulating capacity with variations of ambient temperature, pressure and relative humidity, case studies are performed considering twelve parameters, four regions and seven ambient conditions. Results show that the ambient temperature has the most significant impacts on the gas turbine performances. The output power, gas turbine efficiency and load regulation capacity are improved at base-load as well as part-load. When the ambient temperature drops from 15 °C to −15 °C at base-load, the efficiency and the power increase by 2.1% and 13.9%, respectively, whilst the regulation range of which increases from 46.4% to 51.4%. • A gas turbine off-design behavior model is proposed considering IGV, staged combustion and cooling. • An operation windows analysis method of gas turbine performances is presented. • Impacts of ambient conditions are analyzed based on gas turbine operation windows. • Analysis of NO x emissions is carried out under different conditions. [ABSTRACT FROM AUTHOR]

Large-scale energy storage is essential for the stability of a grid, especially for those with large proportion of intermittent renewable energy sources. The efficiency of a conventional compressed air energy storage (CAES) technology is limited by compression heat loss and changing working conditions. In this manuscript, a combined air and hydro energy storage (CAHES) system is proposed, which realizes a higher exergy efficiency compared with conventional CAES systems by reducing compression heat losses and addressing issues of changing working conditions through thermal compensation from solar radiation. The configuration and two operating modes of the proposed CAHES system are firstly introduced, followed by theoretical analysis and numerical simulation under different operating modes to analyze system performances. Impacts of external and internal factors on the system performances are analyzed. The practical feasibility of the system is also investigated. Results show that the exergy efficiency of the system reaches approximately 50%, whilst the charging electricity ratio reaches over 80%. [ABSTRACT FROM AUTHOR]

Crosswind degrades the cooling performance of a natural draft dry cooling tower (NDDCT) by affecting the air flow field at the inlet and outlet and inducing complex vortices inside and outside the tower. The distribution of the vortices along the flow streams is found to be a key factor for the ventilation rate. The parameter of flow loss factor (FLF) is proposed to quantitatively identify the effect of the vortices and unbalanced flow on the ventilation rate. Approaches of the installations of windbreaks and enclosure on the cooling performance of the NDDCT are numerically studied. It is found that both approaches can individually reduce the size of the inner wall vortex, improving the flow field characteristics. However, they have different strengths in breaking up the side low pressure areas and reducing the swirling intensity of the mainstream vortices. Results show that the approaches of windbreaks and enclosure can effectively prevent the degradation of the cooling performance for the NDDCT in a wide crosswind velocity range, and their combination could nearly eliminates the negative effect of the crosswind. [ABSTRACT FROM AUTHOR]

Raw measured data from an industrial process inherently contain measurement errors. Data reconciliation together with statistical test methods can be used for gross error detection and identification. The magnitude of a gross error should satisfy a quantitative criterion for sufficient isolation from other measurements. However, research on the isolability and identification for multiple gross errors and comparison with single gross error are rarely insufficient. In this work, a mathematical method for evaluating the identification and isolability of multiple gross errors is proposed, and case studies in a real-life 1000 MW coal-fired steam turbine power plant using measured data are carried out. The isolability of multiple gross errors are firstly analyzed theoretically, then examples of the absolute minimum isolable magnitudes for multiple gross errors are presented and validated. Besides, the impact of system redundancy on gross error isolability is also investigated. Results indicate that the minimum isolable magnitude of a gross error is larger in a system with larger redundancy. [ABSTRACT FROM AUTHOR]

In the process of rapid economic development, the relationship between energy consumption and economic development is close and the coupling relationship is complex. The study proposes a method for the assessment of integrated energy consumption factors. In particular, production and consumption driving factors are expressed in relation to the growth of primary energy consumption responsibility in the energy supply chain system. Specifically, based on previous research, the study builds a LMDI decomposition model based on the primary energy consumption responsibility - embodied energy (PECREE) formula. By analyzing the impact of changes in the final commodity quantity, value-added allocation factor, energy intensity, end-use energy consumption structure and primary energy consumption responsibility conversion factor on primary energy consumption responsibility, the study systematically reveals the linkage relationship between product production and consumption on energy consumption changes, and reveals the related driving mechanism of primary energy consumption responsibility growth. We choose China's energy supply system from 2005 to 2020 as a case study, focusing on the impact of changes in economic sectors on primary energy consumption responsibility, and provide a supplementary explanation from the commodity consumption side. The results show that the change of final use quantity is the most important factor causing the increase of primary energy consumption responsibility, but the impact is decreasing year by year. The impact of energy intensity change on primary energy consumption responsibility is mainly dominated by economic sectors with high energy consumption and high energy intensity. The impact of value-added allocation factor requires systematic consideration of energy intensity of economic sectors. The increase of the proportion of electricity in the end-use energy consumption structure of the economic sector promotes the growth of its primary energy consumption responsibility. The reduction of primary energy consumption responsibility conversion factor for electricity is one of the factors that inhibits the growth of primary energy consumption responsibility. Finally, we believe that while meeting the needs of social development and production and life of the people, China is already on the road of adjustment and transformation of its industrial structure and energy structure, and will continue to make progress in the future. • This study builds a LMDI model based on primary energy consumption responsibility - embodied energy formula. • This study reveals the related driving mechanism of primary energy consumption responsibility growth. • Final use quantity is the most important factor causing primary energy consumption responsibility. • Impact of value-added allocation factor requires consideration of energy intensity of economic sectors. [ABSTRACT FROM AUTHOR]

Measurement errors inevitably exist amongst on-line measured data in steam turbine power plants. Problematic steam turbine isentropic efficiencies and turbine expansion curves are therefore obtained in the existence of measurement errors. Data reconciliation is widely used for uncertainty reduction of measurements and parameter estimation. Inequality constraints or bounds are rather necessary in some cases to adjust parameter estimates to be physically meaningful. In this work, we apply an inequality constrained nonlinear data reconciliation approach to the thermal system of a power plant, and compare its effect with equality constrained approaches. Case studies using performance test data and operational measurement data of a real-life 1000 MW steam turbine power plant are provided. The necessity and difference brought by inequality constraints are also discussed. Corrected expansion curve with reasonable enthalpy–entropy relationships and better estimates of isentropic efficiencies are obtained after implementation of inequality constraints. Results show that uncertainties of most measured parameters are reduced by 30–80 percent, and uncertainty of the calculated exhaust steam enthalpy is reduced by 22 percent. [ABSTRACT FROM AUTHOR]

Daqing City in Northern Songliao Basin (China) requires huge amounts of electric power and thermal energy for oil processing and resident support each year. We used actual geological and logging data of deep well YS-2 in Daqing oilfield to investigate electricity generation and heating potential from enhanced geothermal systems in tight rock and naturally fractured formations (3850–4500 m) using different reservoir stimulation methods. We then proposed optimized hydraulic fracturing and heat extraction strategies for each formation. Results indicate that the Yingcheng formation is suitable for the development of HDR (hot dry rock) resources in this region. Heat output in the stimulated naturally fractured formation is obviously higher than that in the tight rock formation. The development of HDR resources in the naturally fractured formation should be prioritized. In middle-low temperature (about 160 °C), tight rock formation still has great potential for heating supply, but the structure has poor capacity for electricity generation because of the low appropriate injection rate resulting from low reservoir temperature. However, when a high temperature reservoir is selected, electricity generation is feasible from tight formation by using gel-proppant hydraulic fracturing combined with horizontal well technology. [ABSTRACT FROM AUTHOR]

Prediction of building energy performance is a critical strategy for building energy management. Extant studies established city-scale prediction models only based on buildings with energy data. However, building energy data in most cities is limited, which may impair model performance. A large number of unlabeled buildings (without energy data) may reveal important energy use knowledge, but few studies have explored their capability to improve building energy prediction. Therefore, a novel semi-supervised deep learning method, namely dynamically updated multi-fold semi-supervised learning method based on deep neural networks (DUMSL-DNN) is proposed to predict building energy use intensity (EUI) by utilizing unlabeled samples. Manhattan is selected as a case study, which contains 4854 labeled samples and 34,456 unlabeled samples. Compared with the optimal DNN model, DUMSL-DNN can improve building EUI prediction with root-mean-square error (RMSE) reduced by 9.36% and mean absolute error (MAE) reduced by 9.43%. The DUMSL method is superior to typical semi-supervised learning methods with the lowest RMSE of 0.5207 and the lowest MAE of 0.3325. By the implementation of DUMSL-DNN, more areas with high EUI are identified in Manhattan. Specifically, commercial buildings and residential buildings built before 1965 have higher EUI. Measures are accordingly proposed to improve building energy efficiency. • This study explores how the unlabeled samples can enhance building EUI prediction. • A novel semi-supervised deep learning method is proposed for building EUI prediction. • Compared with DNN, DUMSL-DNN can use unlabeled samples to reduce RMSE by 9.36%. • The DUMSL method is superior to typical semi-supervised learning methods. • More areas with high EUI are identified in Manhattan for policy-making. [ABSTRACT FROM AUTHOR]

This manuscript attempted to analyze the influencing factors of coal consumption growth in China using the logarithmic mean Divisia index (LMDI) decomposition method developed based on the physical processes of coal utilization from raw coal to the end-use sectors. By mapping the energy allocation diagram of coal flows, we built a method to balance the energy allocation of coal flows and derived several technical influencing factors. These factors were used to develop an LMDI decomposition method suitable for analyzing the coal consumption growth of complex coal-use systems, such as that of China. The method is subsequently applied to analyze the influencing factors of China's coal consumption growth from 2001 to 2011. The results indicate the rapid growth of GDP (gross domestic production) per capita, which heavily relied on the expansion of heavy industry as the dominant factor driving coal consumption growth. Improvement in the energy efficiency of coal power generation and coal end-use combustion were the primary factors reducing coal consumption. [ABSTRACT FROM AUTHOR]

Power plant on-line measured operational data inevitably contain random and gross errors. Data reconciliation is a data preprocessing technique, which makes use of redundant measured data to reduce the effect of random errors, and identify gross errors together with a statistical test method. When applying the data reconciliation based gross error identification method in real-life process, it is sometimes difficult to isolate a small magnitude gross error in one measurement from another due to the influence of system constraint nature and random errors. As a result, the magnitude of a gross error should satisfy a quantitative criterion to make sure of its sufficient isolation from other measurements. In this work, we propose a mathematical method to evaluate the minimum isolable magnitude for a gross error in one measurement to be isolated from another with a required probability for data reconciliation based gross error identification. We also illustrate an application of the proposed method to the feed water regenerative heating system in a 1000 MW ultra-supercritical coal-fired power generation unit. Validation of the proposed method through simulation studies is also provided, together with the influence of system constraint nature and random error standard deviations on the gross error minimum isolable magnitudes. [ABSTRACT FROM AUTHOR]

Abstract: Coal based polygeneration, a technology that couples power generation and chemical production, is a promising solution to the challenges of fossil fuel depletion and greenhouse gas emissions. Carbon monoxide shift process is a key unit in polygeneration, which adjusts hydrogen and CO ratio according to the requirements of downstream processes. Usually steam is added to shift the gas composition extensively, which contributes considerably to the energy efficiency penalty. This paper presents a polygeneration system with a low steam demand CO shift process, based on a recently developed catalyst QDB-04. Compared with a conventional CO shift, the proposed process is characterized by a low steam to CO ratio in the feeding syngas, and the steam required for the CO shift can be significantly reduced. A model of the proposed CO shift process was developed and its performance was compared with a conventional CO shift. Key system parameters were chosen to integrate the low steam CO shift process in a methanol/power polygeneration system. Based on flowsheet simulation, an energy assessment was performed to compare the proposed polygeneration system with a conventional one. Results show that the polygeneration with the low steam CO shift process has considerable energy savings over the conventional scheme. [Copyright &y& Elsevier]

Abstract: Historically, many resource conservation campaigns failed because they paid inadequate attention to the interests of stakeholders. As a consequence, stakeholder analysis has gained increasing attention in order to avoid potential policy failures in the related fields. However, the stakeholder analysis of China’s energy conservation campaign still has been under-developed. This paper proposes a network-based modeling framework to facilitate the development of stakeholder analysis of China’s energy conservation campaign. Given the proposed framework, an illustrative case study is provided to elaborate how to integrate a set of techniques to further develop a quantitative model, as well as to demonstrate the practicability of the proposed framework. The results derived from the case study shows that the proposed framework and the model can be used as analytical tools to improve the government’s policy-making process in term of providing a systematic perspective of stakeholder interrelations. [Copyright &y& Elsevier]

Chinese policymakers are addressing climate change by altering the coal-heavy energy structure. Although coal propelled economic growth, its environmental impacts challenge sustainable development. To balance growth with environmental care, the authorities aim to decrease coal use and enhance clean coal technologies. Thus, understanding coal consumption mechanisms and influencing factors is vital. Actions include adjusting economic structures, lowering energy intensity, enhancing energy layouts, increasing coal-fired efficiency, and optimising power sources. This study used the energy allocation analysis–logarithmic mean Divisia index (EAA–LMDI) decomposition method to examine coal consumption changes from 2005 to 2010, 2010–2015, and 2015–2020. A distinctive feature of this study is that it integrated the EAA method to meticulously consider technical factors that are rarely considered by other researchers. These are the primary factors restraining coal consumption growth. This study also used Sankey diagrams to illustrate the formation mechanisms of coal consumption in China. The findings highlight the contributions of economic development, energy intensity, economic structure adjustments, end-use energy structure, coal-fired power generation efficiency, and power source adjustments to changes in coal consumption in China. The insights of this study can support policymakers in designing effective policies for achieving sustainable energy development and reducing coal consumption in China. • LMDI decomposition based on energy allocation analysis is the methodology used. • Sankey diagrams are used to describe the utilisation of coal in China. • The trends of influencing factors and their impact on coal consumption are explored. • Economic development caused a rapid increase in China's coal consumption. • The transformation of energy technology curbs the increase in China's coal consumption. [ABSTRACT FROM AUTHOR]

Small pressurized water reactors (SPWRs) have complex and variable working environments with high external perturbations that challenge the operational balance and control of the primary and secondary circuits. To improve the control performance of SPWRs, a two-level hierarchy coordinated control system for SPWRs is designed in this paper. First, the equipment model of the primary and secondary circuit systems is developed. Then, based on ideal steady-state programming (ISP) with a constant coolant average temperature and a constant steam pressure, the reactor coolant average temperature, feedwater of once-through steam generator (OTSG), steam dump and steam turbine speed control systems are established by implementing PID controller. Finally, the SPWR coordinated control system is designed according to the logical relationships among the above sub-control systems, and the system is simulated and analyzed under load rejection conditions. The results show that the SPWR coordinated control system using ISP has good operational performance, and the overshoot of the coolant average temperature and steam pressure is minor under load rejection conditions, ensuring the safe operation of SPWRs. • The equipment model of the primary and secondary circuit system of SPWR is established. • A two-level hierarchy coordinated control system for SPWR is designed • The performance of coordinated control system of SPWR is verified. [ABSTRACT FROM AUTHOR]

Demand for electricity is a key bottleneck for the development of remote areas. Grid extension to remote areas has previously been constrained due to difficult terrain for construction and vast investment. Fast development of decentralized renewable energy production technologies provides opportunity for tackling the challenges. The study aims to demonstrate the techno-economic feasibility of off-grid hybrid renewable energy system for remote rural electrification, via a case study of a village in West China by performing simulation, optimization and sensitivity analysis. Daily and seasonal characteristics of energy supply as well as demand sizes and patterns of remote rural areas are considered. Different combinations of PV panels, wind turbine and biogas generator are modeled and optimized in Hybrid Optimization Model for Electric Renewables (HOMER). The most cost competitive configuration is determined whilst ensuring a reliable power supply featuring residential, community, commercial and agricultural demand of the village. Comparison of the off-grid hybrid power system and grid extension has been carried out. Results show that a hybrid power system comprising solar, wind and biomass is a reliable and cost-effective option for sustainable remote rural electrification whilst achieving environmental benefits. [ABSTRACT FROM AUTHOR]

Low-carbon transition of energy systems is an inevitable trend to address climate change challenges. For developing regions, proper planning is essential for reducing transition costs during low-carbon transition of their energy systems, featuring a higher proportion of intermittent renewable power connected to power grids. Impact of uncertainty must be considered for more feasible planning of peak-shaving and energy storage units. In this study, a chance-constrained programming approach to optimal planning of low-carbon transition of a regional energy system is presented. This approach considers uncertainties of wind power, photovolatic (PV) power and load to ensure power supply reliability. A developing region in central China is taken as a case study. Results show that considering uncertainty, an additional 4.79% of power generation capacity needs to be installed per year on average, with a 3.02% increase in the transition cost. Finally, sensitivity analysis results are provided, showing that a rapid increase in transition costs occurs when the confidence level exceeds 99%. The results in this study provide references for decision-makers to plan the low-carbon transition of energy systems as well as weighing transition costs against energy supply stability. [Display omitted] • A chance-constrained programming energy system optimization model is established. • The uncertainties of wind power, photovoltaic power and load are considered. • The impacts of uncertainty degree on the optimal solution were quantified. • The relationship of investment cost and confidence level is given. [ABSTRACT FROM AUTHOR]

In this study, tetra- n -butyl ammonium bromide (TBAB) semi-clathrate hydrate was employed for CO 2 capture from unconventional natural gases exploited by supercritical CO 2 injection. The TBAB hydrate formation kinetics and CO 2 separation efficiency were studied under different TBAB concentrations and subcoolings using a stirred tank reactor. Optimum experimental conditions were obtained (2.8 MPa, Δ T = 6 K, 2.57 mol% TBAB), and the synergetic effect of sodium dodecyl sulfate (SDS) and TBAB on CO 2 separation from CH 4 + CO 2 was investigated under these conditions. The results indicate that gas consumption and CO 2 selectivity declined with the increase of subcooling, and the best CO 2 selectivity was obtained at 2.57 mol% TBAB. The kinetics of TBAB hydrate nucleation and growth were promoted when adding SDS into the TBAB solution, but the CO 2 separation efficiency was reduced. The CO 2 selectivity obtained at 2.57 mol% TBAB was significantly improved as compared to the THF, THF/SDS, and TBPB systems. Therefore, TBAB is a prospective promoter for hydrate-based CO 2 capture from CH 4 + CO 2. Continued efforts are required in the future to increase the gas consumption without sacrificing the CO 2 separation efficiency. • 2.57 mol% is an optimum TBAB concentration for CO 2 capture from CH 4 + CO 2. • The highest CO 2 separation factor obtained at 2.57 mol% TBAB was 36.5. • The optimum subcooling for CO 2 capture using TBAB hydrate was 6 K. • The CO 2 concentration was increased from 40 mol% to 73 mol% via one-stage hydrate-based gas separation process. [ABSTRACT FROM AUTHOR]

This manuscript analyzes the influencing factors of energy consumption growth in Guangdong Province using the logarithmic mean Divisia index I (LMDI) decomposition method developed based on the physical processes of energy utilization from the primary energy supply to end-use sectors. By introducing the input-output method for mapping the energy allocation diagrams of Guangdong Province, we derive the primary energy quantity conversion factors, which establish the connection between end-use energy consumption and primary energy consumption. These factors are used to develop an LMDI decomposition method suitable for analyzing the energy consumption growth of this region. The method is subsequently applied to analyze the factors influencing energy consumption growth in Guangdong Province from 2004 to 2014. The results indicate that the growth of GDP per capita and population are the dominant factors driving energy consumption growth, while the improvement of electricity supply efficiency is the main factor inhibiting energy consumption growth. [ABSTRACT FROM AUTHOR]

The utilization scale of biomass solid densified fuel (BSDF) in China is still far from reaching the 2020 target of the national plan. Promoting the utilization of pellet fuel from corn straw (CSPF) is an effective way to increase the utilization of BSDF considering its resource potential and convenience for distributed use. To enhance scientific support for the corresponding policy research, this manuscript presents a life cycle assessment (LCA) and economic evaluation of CSPF through a case study in Jilin Province. The results indicate that the utilization of CSPF in this case study can eliminate 90.46% of the life cycle GHG emissions by replacing coal burning. A CSPF project designed with a production capacity of 50,000 tons/year based on corn straw resources of five neighboring villages can be economically viable, but a smaller project with a capacity of 10,000 tons/year based on corn straw resources of a single village will have a poor economic outcome. Further encouraging the use of CSPF among industrial and commercial users and applying carbon trading mechanism for CSPF projects can effectively improve the economy of smaller projects to further promote the deployment of CSPF technologies. [ABSTRACT FROM AUTHOR]

Power demand in China has increased rapidly in the past decade, and it is projected to grow even further. To gain insights into how this demand growth could optimally be met, addressing regional differences such as resource distribution and power demand, is crucial. For long-term planning purposes, using a multi-regional mathematical model that divides China's power sector into regions overcomes the limitations of viewing as a single network. Reflecting how inter-regional power transmission could best be utilized is critical in understanding how flows between regions could be optimised. In this paper, a multi-regional model that reflects actual grid infrastructure with an objective function to maximize accumulated total profits gained by the power generation sector from 2013 to 2050 is proposed. A case study is provided to illustrate how inter-regional power transmission could influence the regional deployment of technologies under different policy scenarios. The results show that energy subsidies and national targets will remain important to the deployment of renewable energy in both the short and long term. In addition, potential downside implications of lower demand growth on the long-term prospects of long-distance inter-regional power transmission and options, such as more flexible electricity pricing mechanisms, to limit the effects are discussed. [ABSTRACT FROM AUTHOR]

The recovery of waste heat is important for energy saving and carbon reduction in China. Although numerous technologies for waste heat recovery in China have been analyzed, research is still insufficient to provide an overview of the waste heat potential within the entire energy system. To fill this gap, this paper applies a top-down energy efficiency analysis to develop a Societal Waste Heat Accounting Model to quantify the waste heat potential in China. By indicating the total amount, sector and temperature distribution, and the ability to perform work of waste heat for China in 2018, the results revealed that: a) waste heat occupies 42% of total primary energy inputs, and 26% of primary energy and carbon emissions can be theoretically saved by utilizing waste heat. b) the electricity generation sector is the main source of waste heat, accounting for 45% of the total, of which 88% is below 100 °C. c) the industry sector has a wide range of temperatures, mostly above 300 °C, highlighting the highest ability to perform work. Future studies can focus on the utilization of low-temperature waste heat, which is 66% of the total, for example, the Organic Ranking Cycle technology and the heat pump technology. • A Societal Waste Heat Accounting model quantified waste heat potential in China. • Waste heat potential occupies 42% of total primary energy input in 2018. • Most potential exists in the electricity generation and industry sectors. • Theoretically 26% of energy savings and carbon reductions by waste heat utilization. • The policy priority for the future is the utilization of waste heat below 100 °C. [ABSTRACT FROM AUTHOR]

Shale oil is a promising alternative unconventional energy to conventional fossil fuels. Although some studies have been conducted on total oil content, little work to date was performed on sorbed versus free oil, which is essential for estimating shale oil reserves. This study proposed a sorbed oil model insights from the contribution of oil absorption in kerogen (Abs k), oil adsorption on organic pores (Ads k), and oil adsorption on clay pores(Ads c). The model innovatively considers the effect of thermal maturation on kerogen sorption and the proportion of clay pores hosting adsorbed oil (f). A case study shows that the Abs k ranges from 250 to 80 mg/g TOC in the vitrinite reflectance range of 0.5%–0.89%, while Ads k is 16.5–115.58 mg/g TOC because organic pores are not well developed. For clay pores, the oil adsorption capacity is 1.8 mg/m2 and f is mainly controlled by the oil saturation. At the early oil window, oil sorption associated with kerogen dominated, thus free oil instead of total oil contents should be considered when selecting favorable areas. The proposed model is useful to our understanding of the shale oil occurrence mechanism and provides a new way of estimating sorbed oil contents at different maturity. [Display omitted] • A novel sorbed oil model is proposed by combining kerogen absorption, organic pore adsorption, and clay pore adsorption. • Thermal maturation has a great effect on kerogen sorption oil capacity. • Free oil instead of total oil contents should be considered in the selection of shale oil sweet spots at the early oil window. [ABSTRACT FROM AUTHOR]

Maintaining the online calculation accuracy of isentropic efficiency of a steam turbine stage is challenging due to widely existing gross errors in steam turbine measurements. They invalidate modelling results and hinder model-based monitoring and optimization. Data reconciliation is a mathematical method for gross error detection and has been applied in various industrial systems. In power plant systems, previous studies focus on gross error detection of flow rate measurements in regenerative systems based on equality constraints, which is insufficient for gross error detection of steam turbine systems. We propose a data reconciliation model adding inequality constraints to solve the problem. Statistical test is used to detect gross errors in steam turbine systems. Then an in-service 660 MW ultra-supercritical double reheat power plant is selected as a case study. Gross errors of flow rate measurements are detected and eliminated firstly. Then nonlinear inequality constraints, entropy increase of each stage, are added for further detection. Results show that the proposed model effectively detects gross errors in the steam turbine system and further improve the thermal calculation accuracy by 3.1–5.7%. It provides quantitative guidance for the calibration and maintenance of measurement instruments and facilitates performance monitoring and operation optimization in in-service power plants. • Entropy increase constraints are developed to detect gross error for steam turbines • A data reconciliation model with inequality constraints for power plants is proposed • The gross error of an in-service double reheat steam turbine is detected • Thermal calculation's accuracy is further improved by 3.1–5.7% [ABSTRACT FROM AUTHOR]

Wind and solar energy are paid more attention as clean and renewable resources. However, due to the intermittence and fluctuation of renewable energy, the problem of abandoning wind and photovoltaic power is serious in China. Hydrogen production by water electrolysis is the effective way to solve the problem of renewable energy absorption. However, the multi-energy system has several optimization objectives for the capacity configuration, which are generally conflicting. The "impossible triangle" problem in the system is difficult to solve. Furthermore, the system capacity configuration is greatly affected by factors such as operating mode and energy storage form, etc. Therefore, the three different application scenarios are proposed both in the off-grid and grid-connected system, in which the energy storage system consists of only battery, only hydrogen, both hydrogen and battery, respectively. The system operation strategy is based on that the main purpose of hydrogen energy is storage, transportation and utilization alone. The multi-objective capacity configuration optimization based on the improved NSGA-Ⅱalgorithm is proposed, which is verified to be superior to NSGA-Ⅱand MOPSO. The capacity configurations of off-grid and grid-connected multi-energy systems are compared and analyzed. The economy of grid-connected system is better than that of off-grid system. The sensitivity analysis of important parameters is carried out such as wind/solar resources, load level and equipment price. The average wind speed has the significant impact on the net present value of the system. The capacity configuration and operation strategy proposed in this paper are effectively feasible to increase the renewable energy accommodation and meet comprehensive performance requirements of multi-energy complementary system. • Improved NSGAⅡalgorithm for capacity configuration can solve "impossible triangle" problem. • Different energy storage forms are analyzed in off-grid and grid-connected systems. • Hydrogen comprehensive utilization is superior to its electrical power regulation. • Relationship between net present value and sensitive factors is analyzed. [ABSTRACT FROM AUTHOR]

In this study, a fixed bed of pulverized coal particles was employed to enhance the precombustion CO 2 capture from fuel gas (40 mol% CO 2 /H 2 ). The performance of the HAHF (hybrid adsorption-hydrate formation) process occurred in the fixed bed was evaluated at different liquid saturations and operation pressures. The experiments were carried out at 274.2 K with the pressure varying from 3.0 MPa to 6.0 MPa. 1.0 mol% THF (tetrahydrofuran) solution instead of liquid water was used to saturate the fixed bed and reduce the hydrate phase equilibrium conditions. The results indicated that gas hydrate nucleation in the fixed bed was quickly induced by gas adsorption in coal particles. The HAHF process was dominated by hydrate formation as the fixed bed saturation increased, and the CO 2 recovery and separation factor were increased. Gas consumption during the HAHF process was promoted with the increase of operation pressure, but the CO 2 recovery and separation factor decreased. In the fixed bed of coal particles saturated by 1.0 mol% THF solution the highest gas uptake obtained was 51.9 mmol of gas/mol of water, which was comparable with that obtained in the fixed bed of silica sand in the presence of 5.53 mol% THF. Therefore, compared with the hydrate based gas separation process, the hybrid adsorption-hydrate formation process proposed in this study could be a viable option for CO 2 capture from fuel gas. [ABSTRACT FROM AUTHOR]

This paper proposed a COSM (cost-optimization superstructure model) and derived the optimized oil-saving pathways for road freight transportation in China until 2030. The optimization target of the COSM was to minimize the accumulated energy and vehicle costs from 2010 to 2030 by choosing the most cost-effective fuel option for newly registered trucks each year. Based on the COSM, three scenarios were developed to evaluate the oil-saving pathway in terms of imported crude oil price, available alternative fuels and GHG emission reduction. The scenario analysis results indicate that: (1) for scenario A, the accumulated oil-saving potential was approximately about 13%, while the oil-saving potential of improving fuel consumption rate and load running rate was 17% and 16%; (2) for scenario B, the accumulated oil-saving potential increased to 82% in reference oil price and 23% in low oil price; (3) for scenario C, to reduce per ton of GHG emission, the increased cost will increase from 34 USD to 450 USD when the GHG emission target decreased from 15.4 billion tons to the turn point of 13.5 billion tons. [ABSTRACT FROM AUTHOR]

Abstract: The interconnection between a renewable power generation facility and a power grid poses challenges because of volatility and intermittent characteristics. Energy storage is one of the best solutions for this problem. This paper presents an integrated energy storage system (ESS) based on hydrogen storage, and hydrogen–oxygen combined cycle, wherein energy efficiency in the range of 49%–55% can be achieved. The proposed integrated ESS and other means of energy storage are compared. The results show that the proposed integrated system cannot be constrained by geological conditions and availability of materials, and appears to be an appropriate tool for the development of renewable power. Moreover, a case study is conducted for a special wind power plant with a nominal power of 100 MW and that generates electricity of 225 GWh/y. The integrated system is designed based on the daily wind load. Energy efficiency and preliminary economic comparison studies for the integrated system operated in two modes show that up to 50% average net efficiency of the integrated ESS can be achieved and that the integrated ESS can stabilize the intermittent wind power. Therefore, the integrated ESS can be useful to mitigate the bottleneck of renewable power development. [Copyright &y& Elsevier]

Reliable wind energy forecasting is crucial for the stable operation of power grids. This paper proposes a regional wind power probabilistic forecasting model comprising an improved kernel density estimation (IKDE), regular vine copulas, and ensemble learning. The IKDE is firstly used to generate the margin probability density function (PDF) of each wind farm and the KDE bandwidth is optimized via the golden-section search algorithm to obtain the best possible prediction. Then, several dependence structures are formulated by building different regular vine copulas based on multiple criteria, and all the dependence structures work together with marginal PDF to generate respective joint distribution functions. Finally, ensemble learning is applied to combine all the joint distribution functions and establish an ultimate distribution function. Furthermore, a novel multi-distribution mega-trend-diffusion (MD-MTD) with parametric optimization is proposed to improve the prediction when the data are insufficient. The results of comparative evaluations conducted on datasets from eight wind farms indicate that the proposed model outperforms existing models in wind power generation prediction. Specifically, the proposed model can reliably forecast power generation for an entire region for the next 24 h with only three months of historical data. In contrast, most benchmark models require a year of data. • A regional wind power probabilistic forecasting model is proposed. • Improved kernel density estimation/regular vine copulas/ensemble learning are joined. • Multi-distribution mega-trend-diffusion (MD-MTD) with optimization is also proposed. • MD-MTD improves the prediction when the data are insufficient. • The proposed model outperforms existing models in wind power generation prediction. [ABSTRACT FROM AUTHOR]

Achieving carbon neutrality would reshape energy supply systems, and proper planning could ensure transition smoothly and reduce costs. Energy infrastructure is imperative in system planning, due to long life-span and massive investment. System planning with detailed infrastructure layout could improve the feasibility of transition blueprints, whilst the layout of carbon neutral energy supply systems and the transition pathway to carbon neutrality have not been pointed out with detailed infrastructure layout. In this study, a multi-regional, multi-period and infrastructure-based planning model is applied to describe China's low carbon transition pathway towards carbon neutrality by 2060. The deployment of carbon neutral energy supply systems and the pathway to that are obtained by minimizing long-term system costs, and infrastructure layout and energy flows amongst regions are pointed out. Results show that power systems and hydrogen systems would dominate in the carbon neutral energy systems. To achieve carbon neutrality, existing transition targets need more efforts beyond 2030, and infrastructure investment would increase by 115%. Coal capacity reduction would account for most of stranded investment, and reduction of existing coal power as its life-span would be compatible with carbon neutrality. • Deployment of carbon neutral energy systems and energy flows are pointed out. • Existing targets need more efforts beyond 2030 to achieve carbon neutrality. • Infrastructure investment would increase by 115%. • Coal capacity reduction would account for most of stranded investment. • Coal power reduction as its life-span would be compatible with carbon neutrality. [ABSTRACT FROM AUTHOR]

Abstract: Coal–water slurry (CWS) preheating vaporization technology is an important new technology for the future development of Integrated Gasification Combined Cycle (IGCC) systems, providing an opportunity to improve the energy efficiency of wet feed gasification processes. This manuscript systematically analyzed the influence of integration of this technology on the energy efficiency performance of wet feed IGCC systems with or without carbon capture. We designed, simulated and compared ten cases of IGCC systems, including three wet feed IGCC systems with distinct integration modes for CWS preheating technology, one traditional wet feed IGCC and one dry feed IGCC as reference cases, all of which have one case with carbon capture and another case without carbon capture. The results indicate that, without carbon capture, the overall energy efficiencies of wet feed IGCC systems integrated with this technology are 1–5 percentage points (1%–5%) higher than that of the original wet feed IGCC system, depending on the integration mode. When carbon capture is introduced, the overall energy efficiencies of wet feed IGCC systems integrated with this technology are close to or even higher than that of the dry feed IGCC system. [Copyright &y& Elsevier]

Abstract: In this paper, we propose a simplified method and build a model accordingly for estimating the energy-saving potentials of building construction and demolition with the consideration of China''s rapid growth of building construction and its short actual lifespan of buildings. To demonstrate the practicability of the proposed method and model, we further develop an illustrative case study to estimate the energy-saving potentials from residential building sector in China. Our results show that a considerable amount of energy-saving potentials can be captured from now until 2020, 2030, or 2050 by smooth implementation of either controlling the growth in demand for the per capita residential building floor area or extending the actual lifespan of the residential buildings in China. Through this study, we fill the gap, in terms of method and model, of supporting the further improvement of China''s existing energy conservation policies. [Copyright &y& Elsevier]

Abstract: We present a map of the transformation of energy in China as a Sankey diagram. After a review of previous work, and a statement of methodology, our main work has been the identification, evaluation, and treatment of appropriate data sources. This data is used to construct the Sankey diagram, in which flows of energy are traced from energy sources through end-use conversion devices, passive systems and final services to demand drivers. The resulting diagram provides a convenient and clear snapshot of existing energy transformations in China which can usefully be compared with a similar global analysis and which emphasises the potential for improvements in energy efficiency in ‘passive systems’. More broadly, it gives a basis for examining and communicating future energy scenarios, including changes to demand, changes to the supply mix, changes in efficiency and alternative provision of existing services. [Copyright &y& Elsevier]