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Compared with the traditional "dynamic‐static" load rockburst induced by working face mining, a new typical disaster with concealment characteristics has appeared in deep thick coal seam roadways, namely, static creep rockburst, the occurrence mechanism of which remains unclear. Through the method of combining theory with practice, this paper elucidated the mechanical mechanism of static creep rockburst of deep thick coal seam roadways, along with the CT inversion of its rockburst risk. Next, by establishing the creep model and three‐dimensional creep formula under static conditions, it was observed that the main conditions for the unstable creep of deep thick coal seam roadway were high stress and thick coal seam. In addition, by analyzing the unstable creep failure process of surrounding rock in static roadways, it was found that the weakening of surrounding rock strength and stress relief were the reasons for starting rockburst and reducing impedance. The mechanical conditions of creep rockburst caused by stress superposition in weak areas of the roadway under static conditions were proposed, and the criterion of rockburst possibility was given. Finally, according to the characteristics of spontaneity and time delay of such a rockburst disaster, the static creep rockburst evaluation of thick coal seam roadway before mining was achieved by CT inversion, and the research conclusions were thoroughly verified. [ABSTRACT FROM AUTHOR]

This paper presents a model predictive control (MPC) and its application on a three‐phase four‐leg inverter in an islanded mini‐grid to compensate for unbalanced load conditions while minimizing the neutral‐to‐ground voltage (NGV). The proposed approach uses the novel discrete‐time model of the four‐leg inverter and LC filter to predict the control variables. These predictions are evaluated by using a multiobjective cost function. The proposed method is based on the minimization of the cost function to select the best vector state of the power converter to be applied in the next sampling instance. The cost function in this study has two objectives: the adequately tracked low voltage reference and minimization of the NGV, simultaneously. The stability analysis is also defined to investigate the stable dynamics of the proposed MPC. The effectiveness of the suggested method is verified through simulations considering the single/three‐phase and balanced/unbalanced loads. The distinguished results of the proposed work indicate that the proposed MPC algorithm provides high power quality under unbalanced and nonlinear load conditions with high stability. The robustness of the proposed controller is also studied with both inductive and capacitive filter parameter variations. [ABSTRACT FROM AUTHOR]

In this paper, a three‐dimensional simulation model of the engine cylinder is established using commercial simulation software AVL‐Fire, and the accuracy of the model is verified with experimental results. The effects of diesel/biodiesel/n‐butanol blends on diesel engine performance, and combustion and emissions characteristics were investigated by performing simulation operations on the model. The combustion process in the cylinder was simulated for 0%, 5%, 10%, 15%, and 20% of n‐butanol in the fuel mixture. The results showed that at 75% load, the brake thermal efficiency of D95N5, D90N10, D85N15, and D80N20 engines increased by 0.84%, 1.68%, 2.48%, and 3.19%, respectively, and soot emissions decreased by 2.76%, 5.52%, 8.25%, and 10.96%, respectively, compared with D100. However, the brake power of the engine was reduced, the brake ratio fuel consumption increased, and NOx emission increased. In addition, at all loads, soot and CO emissions decrease as the percentage of n‐butanol in the fuel mixture increases. [ABSTRACT FROM AUTHOR]

The emission of greenhouse gases from fossil fuels is the main environmental impact of energy resources. Moving toward the use of renewable energy resources is the only solution to tackle these problems. In this paper, a configuration of the hybrid biomass and geothermal energy resource is examined for cooling and electricity generation. In this study, water as a geothermal working fluid is heated up due to combustion of syngas produced in a digester and produce power in a steam turbine. So, the remaining heat of this geofluid runs an absorption chiller for cooling production. The results reveal that the energy and exergy efficiencies of this proposed cycle are 30.8% and 15.5%, respectively. Moreover, the economic analysis of this cycle concludes that the payback period is 2.8 years and the simple payback period for this configuration is 2.6 years. Moreover, the highest exergy destruction rate of 52.4% belongs to the absorption refrigeration cycle. Whereas the lowest exergy destruction of the steam line is the lowest value of 17.4%. [ABSTRACT FROM AUTHOR]

This paper studies the width of narrow coal pillars, mining‐induced failure characteristics, and surrounding rock control effect of gob‐side entry driving (GED) adjacent to 2‐1208 filling working face with an approximately 900 m depth. Laboratory experiments, numerical simulations, loosening circle tests, and engineering practices are conducted. The mechanical properties of the filling body, the distribution and evolution law of the second invariant deviatoric stress (J2), and the variation in the plastic zone of the surrounding rock in GED are studied. The conditions of various coal pillar widths and the gob backfilled or not of the adjacent working face are also considered. The results of roadway driving along the filling working face in the deep coal mine are that: (1) The evolution law of J2 and the plastic zone features of the surrounding rock in GED have changed significantly. Thus, it is unreasonable to still adopt the customary theory of narrow coal pillar determination and roadway support design method of GED adjacent to nonfilling working face. (2) The plastic zone of GED has typically asymmetric distribution characteristics during driving and retreating, which is mainly concentrated at the upper corner of the virgin coal rib. And the elastic zone changes slightly by the influence of mining‐induced pressure on the working face, indicating that support in this area is easier. (3) During the stable period of roadway driving, there includes a "ring‐shaped" J2 depression zone at the upper corner of the coal pillar rib. While the peak zone distribution of J2 in the virgin coal rib of GED is approximately "crescent‐shaped," and the peak zone is inclined to the upper corner of the virgin coal rib, which implies that this area is a crucial control region. (4) During the retreating period of panel 2‐1210, the direction of the maximum principal stress of GED gradually deflects from the direction of the gob to that perpendicular to the roof and floor, which represents that the key support area of GED has changed. Therefore, the advanced support of GED needs to be reinforced by single hydraulic props. The width of the coal pillar was determined to be 5 m, and a targeted truss anchor cable support method with bidirectional resistance function is proposed for the roof and both ribs, which realized the stability control of GED during deep filling mining. [ABSTRACT FROM AUTHOR]

In this paper, a Random‐XFEM technology was employed to simulate hydraulic fracture interaction with the natural void in a random field of Young's modulus. The random distribution of Young's modulus is characterized by random field theory, while the stress and pressure fields fracturing were solved by the extended finite element method. And a Random‐XFEM iteration algorithm was proposed to solve the hydraulic fracture propagation problem. Then the proposed model was verified against the KGD model and numerical study. A series of numerical examples were presented to analyze the interaction mechanism of hydraulic fracture and void in a random field. The numerical results show that the random field of Young's modulus has a great impact on the hydraulic fracture propagation path. Under the random distribution of Young's modulus, the hydraulic fracture would deviate from the direction of maximum horizontal principal stress. And the random field parameters (Young's modulus mean and point variance) have different effects on the hydraulic fracture propagation path. Also, the interaction patterns of hydraulic fracture and void are greatly affected by random fields. [ABSTRACT FROM AUTHOR]

The coaxial magnetic gear is a new type of noncontact transmission mechanism, which avoids the inherent defects of the mechanical gearbox due to gear meshing transmission. To study a coaxial magnetic gear (CMG) with high torque density and low torque ripple to replace the mechanical gear in the semidirect drive wind turbine, a novel umbrella shaping inner rotor CMG (US‐CMG) with an auxiliary modulation ring is proposed in this paper. The novel structure adopts a CMG with a dual modulated ring to increase the electromagnetic torque. In addition, the magnetic block of the poled inner rotor is divided into three pieces magnetized by Halbach arrays, and the middle piece is umbrella‐shaped to reduce torque ripple. Based on the topology of the US‐CMG and the principle of the magnetic field modulation, the operation mechanism of the US‐CMG is analyzed. A contrastive analysis among the US‐CMG, Halbach magnetized dual‐modulator CMG (HM‐CMG), and surface‐mounted CMG (SM‐CMG) is established to identify the performance of the US‐CMG. Compared with the SM‐CMG, the results show that the electromagnetic torque of the US‐CMG has increased by 65.46%, and the torque ripple of the US‐CMG is 57.6% of that of the SM‐CMG. [ABSTRACT FROM AUTHOR]

Off‐grid renewable energy systems are a solution for power generation in areas where access to the grid is not possible or cost‐effective; in particular, low population rural areas located far away from grid lines or in rugged terrains. Furthermore, over‐reliance on fossil fuels for supplying global energy demand has led to the depletion of nonrenewable resources and environmental issues. This paper presents a feasibility assessment of an off‐grid hybrid renewable energy system for a remote rural area in Kohgiluye and Boyer‐Ahmad Province in Iran. Regarding the available energy resources in the region, a photovoltaic (PV)‐biomass energy system is considered. HOMER Pro software is utilized to find the optimized sizing of the PV‐biomass system to fulfill this load demand. The objective function in this optimization is the system's total net present cost. Due to the rapid fluctuation of economic factors in the country, several rates of inflation and discount rate are considered to investigate their influence on the costs of the system. The optimization result for the current inflation rate of 40% and the discount rate of 18% in the country proposes a hybrid energy system consisting of a 3 kW biogas‐fueled generator, 4.74 kW PV, 10 kWh battery, and 2.07 kW converter to meet the 2.64 kW peak load and 14.53 kWh/day consumption of the community. The total net present cost and cost of energy are $93,057 and 0.0933 $/kWh, respectively. Finally, the environmental assessment of the proposed hybrid system shows an annual CO2 emission of 2.95 kg, which means 99.9% CO2 emissions mitigation compared to a conventional coal‐based electrical plant. [ABSTRACT FROM AUTHOR]

Achieving carbon neutrality targets requires substantial financial support. Effective utilization of renewable energy is an essential means of promoting energy‐saving and emission reduction to realize a green and circular economy. This paper combines carbon trading mechanisms with the operational mode of Chinese micro‐grid enterprises. This method uses the real options theory to construct an investment decision model for photovoltaic (PV) micro‐grid enterprises. The study aims to analyze the impact of carbon trading revenue on a numerical simulation of PV micro‐grid enterprise investment decisions. The findings demonstrate that when projected growth rates, volatility standard deviations, and risk‐free interest rates rise in the carbon trading market, the carbon price threshold rises, causing businesses to seek out investment opportunities with higher future carbon prices. The increase of micro‐grid generation technology acceptance probability, the availability of resources to meet generation investment requirements, and the generation project cycle will decrease the carbon price threshold and accelerate enterprise investment. Studying the influence of carbon trading prices on micro‐grid investment has specific guidance and practical significance for future government subsidy policies and the investment strategies of grid enterprises. [ABSTRACT FROM AUTHOR]

In this paper, to analyze the oxygen corrosion of the casing string under the nitrogen blanket condition of the salt cavern underground gas storage and to predict the casing's service life, an indoor corrosion weight‐loss experiment was used to study the effects of oxygen concentration, temperature, and pressure on the gas and liquid phase of N80 steel pipe corrosion laws. The corrosion products were examined using scanning electron microscopy, X‐ray fluorescence spectroscopy, and X‐ray diffraction analyses. Finally, the corrosion life of the casing was predicted based on the uniform corrosion rate and casing strength check. The results indicated the following: (1) under the experimental conditions, the gas–liquid two‐phase corrosion rate gradually decreased with the increase in nitrogen concentration, while when the concentration was 78%–95%, the liquid‐phase corrosion was serious, and in the liquid nitrogen environment (nitrogen concentration is 99.9%), the liquid‐phase corrosion rate was lower than the oilfield corrosion control index (0.076 mm/a); (2) the temperature and pressure had no significant effect on the casing corrosion; (3) with the increase in nitrogen concentration, the service life of the inner and outer pipes under different working conditions gradually increased, with the minimum service life equaling 28 years when the concentration was 99.99%; (4) nitrogen concentrations of 99.99%, 95%, 90%, and 78% can meet the column strength of the 3‐year cavity‐building cycle, while under the 5‐year cavity‐building cycle, it is recommended that the lower limit of the purity is 90%. Overall, the research results will provide a strong information basis for the construction of salt cavern gas storage cavities. [ABSTRACT FROM AUTHOR]

Due to rapid socioeconomic growth and current environmental concerns, reducing global greenhouse gas emissions is a key step toward sustainable development. In recent years, some researchers have begun to adopt new grid management technologies such as virtual power plants (VPP) that allow them to improve energy management and cost and reduce gas emissions. The integration of distributed energy resources (DER), such as solar photovoltaic and wind power, combined with micro‐turbines and energy storage systems and with the support of VPP intelligence, will contribute immensely to improving micro‐grids (MGs) energy performance and reducing gas emissions. In this paper, an expert multi‐objective feasibility enhanced particle swarm optimization algorithm is adopted for the optimal scheduling of energy management system to reduce the total operating cost and net emission simultaneously. The proposed algorithm is tested on an Algerian reel building‐MG integrated VPP with DERs and combined cooling, heat, and power generation. Finally, different cases are simulated for a 24‐h time and discussed to demonstrate the validity of the proposed VPP energy system and the effectiveness of the adopted algorithm to reduce gas emissions and the total operating cost. [ABSTRACT FROM AUTHOR]

In this paper, a novel organic flash Rankine cycle (OFRC) system for low‐temperature heat recovery is analyzed and optimized using the 3E (energy, exergy, and economic) analysis method and particle swarm optimization algorithm, respectively. Five environmentally friendly organic fluids and three typical heat source conditions are simultaneously discussed during the parametric analysis and optimization process, to obtain a comprehensive understanding of the thermo‐economic characteristics of this novel system. The main analysis results show that the biggest exergy loss of the OFRC system is caused by the condenser, followed by the evaporator. About 70% of the specific power cost is caused by the capital investment of the system, and more than 60% of the capital investment is spent on purchasing the high‐pressure and low‐pressure expanders. Under the same operating conditions, the working fluids with high critical temperatures can achieve higher cycle thermal efficiency and lower specific power costs than those with low critical temperatures. The optimization results show that the OFRC system is able to achieve a better thermodynamic performance than the organic Rankine cycle (ORC) and organic flash cycle (OFC) systems, and when the heat source's inlet temperature is set to 100°C, 120°C, and 140°C, R245fa, R290, and R152a are, respectively, recommended as the best working fluid for the OFRC system. Besides this, it is found that the OFC system has the worst thermo‐economic performance, and the ORC system can achieve the lowest specific power cost. A new finding is that, for all three systems, the higher the critical temperature of the working fluid, the lower the specific power cost of the system. [ABSTRACT FROM AUTHOR]

This paper proposes an improved version of Barnacles mating optimizer (BMO) for solving the optimal allocation problem of distribution generator (DGs) in radial distribution systems (RDSs). BMO is a recent bioinspired optimization algorithm that mimics the intelligence behavior of Barnacles' mating. However, like with any metaheuristic optimization approach, it may face issues such as local optima trapping and low convergence rate. Hence, an improved BMO is adopted based on the quasi oppositional (QOBMO) and the chaos maps theories (CQOBMO). The two improvement methods are applied to increase the convergence performance of the conventional BMO. To prove the efficiency of the improved QOBMO and CQOBMO algorithms, 23 benchmark functions are used, and the accomplished results are compared with the conventional BMO. Then, the improved algorithm is applied to minimize the total power and energy losses in the distribution systems considering the uncertainty of DG power generation and time‐varying load demand. The uncertainty of DG is represented using photovoltaic‐based DG (PVDG). The improved method is employed to find the optimal power scheduling of PVDG and battery energy storage (BES) during 24 h. Two standard IEEE RDS (IEEE 33‐bus and IEEE 69‐bus) are used to simulate the case studies. Finally, the obtained results show that significant loss reductions (LRs) are achieved using the improved BMO where LRs reach 65.26%, and 68.86% in IEEE 33‐bus and 69‐bus, respectively, in the case of PVDG integration. However, using PVDG and BES the energy loss reductions reach 64% and 67.80% in IEEE 33‐bus and 69‐bus, respectively, which prove the efficiency of the improved BMO algorithm in finding the optimal solutions obtained so far. [ABSTRACT FROM AUTHOR]

The aim of this paper is to analyze local autoignition induced by secondary flame acceleration. The secondary flame acceleration process and the local autoignition formation mechanism at the condition of the secondary flame acceleration propagation were investigated by utilizing an improved designed constant volume combustion bomb (CVCB) with two perforated plates. Primary flame and secondary flame propagation were recorded via high‐speed schlieren photography. The results showed that there were three distinct stages in the process of flame propagation through two perforated plates, which were the primary jet flame stage, secondary jet flame stage, and flame‐shock interaction stage. The morphologies of the flame were analyzed by high‐speed Schlieren images, flame velocities, and pressure oscillation including primary jet propagation, secondary flame formation and acceleration, and location autoignition. Results show the effect of initial pressure on flame propagation, flame velocity, and pressure oscillation. Acceleration of secondary flame and local autoignition phenomenon was more precisely demonstrated as unburnt gases were compressed by flame waves (different velocities) with initial pressure increasing. Based on the morphology of flame, three different types of flame combustion modes were captured at different initial pressure involving turbulent flame, deflagration, and quasi‐detonation. The present work might provide a new insight for combustion science in a confined space, such as autoignition due to compression effect of secondary jet flame and primary flame interaction. It also provides the theory guidance and research direction towards further studies on propane storage vessel deflagration. [ABSTRACT FROM AUTHOR]

Trombe walls figure among many passive devices used in the Mediterranean climate to minimize heating demands in residential buildings. The thickness of this massive wall is a critical parameter that influences the effectiveness of the system. Insufficient wall thickness conducts to an important interior temperature fluctuation, and huge wall thickness will increase costs and thermal resistance. In this paper, the optimum thickness of four different construction materials (concrete, stone, adobe, and brick), which can be used in the Trombe wall, was determined using an energetic and economic analysis. The energetic results with TRNSYS software show that the best materials, which can contribute to a reduction by 50% in heating loads of a single room, are stone and concrete. For the economic analysis, the life cycle cost and the payback period were calculated for each construction material. The results show that the optimum thickness for stone and concrete are, respectively, 34 and 32 cm with a payback period of 2.85 and 2.65 years. [ABSTRACT FROM AUTHOR]

Solar photovoltaic (PV) power is emerging as one of the most viable renewable energy sources. The recent enhancements in the integration of renewable energy sources into the power grid create a dire need for reliable solar power forecasting techniques. In this paper, a new long‐term solar PV power forecasting approach using long short‐term memory (LSTM) model with Nadam optimizer is presented. The LSTM model performs better with the time‐series data as it persists information of more time steps. The experimental models are realized on a 250.25 kW installed capacity solar PV power system located at MANIT Bhopal, Madhya Pradesh, India. The proposed model is compared with two time‐series models and eight neural network models using LSTM with different optimizers. The obtained results using LSTM with Nadam optimizer present a significant improvement in the forecasting accuracy of 30.56% over autoregressive integrated moving average, 47.48% over seasonal autoregressive integrated moving average, and 1.35%, 1.43%, 3.51%, 4.88%, 11.84%, 50.69%, and 58.29% over models using RMSprop, Adam, Adamax, SGD, Adagrad, Adadelta, and Ftrl optimizer, respectively. The experimental results prove that the proposed methodology is more conclusive for solar PV power forecasting and can be employed for enhanced system planning and management. [ABSTRACT FROM AUTHOR]

Building a complex fracture network in a deep shale gas reservoir during multicluster hydraulic fracturing is challenging. On the one hand, hydraulic fractures tend to propagate along shale bedding planes, thus leading to a limited hydraulic fracture height; on the other hand, under the effect of high in situ stress and weak plane of fractures, multihydraulic fractures can hardly initiate and propagate uniformly. All of these will jeopardize the performance of hydraulic fracturing. This paper considers the influence of natural fracture network, shale beddings, fracturing‐fluid leakage, and high in situ stresses, and builds a numerical model to simulate multifracture propagations along vertical direction during hydraulic fracturing in deep shale reservoirs. The model is developed based on the theory of solid–fluid coupling and finite element method with pore pressure cohesive element technique are used to simulate multicluster fracture initiation and propagation. Moreover, the model is verified by published experiment data, and a good agreement between model and experiment results is observed. The influences of pump rate and fracturing‐fluid viscosity on fracture geometry are discussed, and the flow dynamics around each perforation cluster under different perforation parameters are also studied. Finally, suggestions to improve overall outcome of multicluster hydraulic fracturing are also provided. [ABSTRACT FROM AUTHOR]

Microwave heating (MW) and freeze fracturing (FF) have been widely used for enhancing the permeability of coal reservoirs. In this paper, the effects of combined MW–FF treatments on coals are experimentally investigated through nuclear magnetic resonance. T2 distributions and fractal dimensions of coals under MW, FF, and the combined MW–FF treatments are compared and analyzed. The results show that the T2 area, porosity, and fractal dimensions of coals increase to varying degrees after MW, FF, and MW–FF treatment. The T2 spectrum peaks increase from 2 to 3 and macrofractures can be observed after the coal was treated with the combined MW–FF treatments. However, these phenomena are not observed under MW or FF treatment. The combined MW–FF treatments can effectively fracture coals with less microwave energy and less liquid nitrogen freezing cycle owing to its intensive thermal shock fracturing. Therefore, the combined MW–FF treatment is favorable for fracturing the coals and hence favorable for the CBM production. [ABSTRACT FROM AUTHOR]

The integrated energy system is an important prerequisite for the sustainable transformation to the low‐carbon power system. Therefore, this paper aims to provide readers with insights into the existing research about the planning and operation models of integrated energy systems. First, the general structure of integrated energy systems is elaborated, and the new issues faced by the low‐carbon planning and operation for the integrated energy systems are represented. Next, the technical framework and the general model are proposed. Furthermore, the typical models and solution technologies of the low‐carbon planning and operation are summarized based on specific models operating in multiple scenarios. Finally, based on the characteristics and framework of the integrated energy system, the future research direction is given, which is expected to guide the sustainable development and low‐carbon transformation of energy systems. [ABSTRACT FROM AUTHOR]

In this paper, a grey prediction model group is employed to quantitatively study the impact of COVID‐19 on natural gas consumption in Chongqing, China. First, a grey prediction model group suitable for the prediction of Chongqing's natural gas consumption is introduced, which consists of GM(1,1), TWGM(1,1), and the newly‐developed ODGM(1,1). Then, the model group is constructed to predict Chongqing's natural gas consumption in 2020. Finally, compare the predicted results of the model group with the actual consumption and quantitatively analyze the impact of the epidemic on natural gas in Chongqing. It is found that the impact of the epidemic on the consumption of natural gas in the first quarter of the year is very small, but relatively bigger in the second and third quarters. The study is of positive significance to maintain the supply and demand balance of natural gas consumption in Chongqing in the background of COVID‐19; and it enriches and develops the theoretical system of grey prediction models. [ABSTRACT FROM AUTHOR]

This study has attempted to compare two thermodynamic cascade cycles, which in this paper are presented as Systems A and B. System A was consisted of a steam Rankine cycle (SRC) as a top cycle and an organic Rankine cycle (ORC) as a bottom cycle. System B was consisted of the same SRC as the top cycle and a Kalina cycle as the bottom cycle. The comparison of both systems has been made by changing a number of parameters. The chosen parameters for this comparison were bottom cycle mass flow rate, aperture area of the collector, top cycle condensing pressure, and bottom cycle turbine inlet and outlet pressures. Also, a short economic evaluation has been made between two proposed cascade cycles (Systems A and B). The result indicated that the Kalina cycle shows superiority over the ORC as the bottom cycle in a solar‐driven SRC. Furthermore, it was determined that the most effective parameters on the overall efficiency of the systems are the condensing pressure of the top cycle and the outlet pressure of the bottom cycle turbine. Also, among the chosen parameters, the outlet pressure of the bottom cycle turbine had the highest effect on the efficiency of the bottom cycles. Considering the economic aspect, the results showed that the levelized costs of energy for both systems are quite equal at 0.011 ($/kWh). [ABSTRACT FROM AUTHOR]

Parameter extraction of photovoltaic (PV) models based on measured current–voltage data plays an important role in the control, simulation, and optimization of PV systems. Despite the fact that various parameter extraction strategies have been dedicated to solving this problem, they may have certain drawbacks. In this paper, an effective hybrid optimization method based on adaptive rat swarm optimization (ARSO) and pattern search (PS) is presented for effectively and consistently extracting PV parameters. The proposed method employs the global search ability of ARSO and the local search ability of PS. The performance of the new algorithm is investigated using a set of benchmark test functions, and the results are compared with those of the standard RSO and some other methods from the literature. The extraction of parameters from several PV models, such as single‐diode, double‐diode, and PV modules, confirms the performance of the suggested method. Simulation results show that the proposed method surpasses other state‐of‐the‐art procedures in terms of accuracy, reliability, and convergence speed. [ABSTRACT FROM AUTHOR]

In order to seek the optimal growth of China's economy under the premise of natural gas supply safety and air pollution emission constraints, this paper builds a multiobjective optimal allocation model of China's natural gas. The model takes 2012 as the base period, and the simulation period is from 2013 to 2025. Four types of policy combinations are set as variables to be introduced into the model. Lingo is used to simulate the policy combinations under considerations by the model to select the optimal scenario. The dynamic scenario simulation results are as follows: (a) Comparing the simulated data with actual data from 2013 to 2018, we find that the relative error between the simulated results and the actual results is less than 3%, indicating that the constructed multiobjective optimization configuration model is reliable and effective. (b) By 2025, China's natural gas production will be 333.4 billion cubic meters, and its consumption will be 217.1 billion cubic meters. The output will gradually exceed the demand; the proportion of natural gas consumption in the total energy consumption will increase from 5.4% to 7.8%. The proportion has increased significantly; the total GDP is 139 trillion yuan, with an average annual growth rate of 7.5%, and the contribution of the tertiary industry to GDP accounts for 55.8%; (c) China's SO2 emissions from 19.54 million tons in 2013 will be reduced to 12.64 million tons in 2025, China's NOx emissions plummeted from 21.92 million tons in 2013 to 12.59 million tons, and the emission intensity of atmospheric pollutants dropped from 34.0 tons/100 million yuan in 2013 to 9.1 tons/100 million yuan in 2025. [ABSTRACT FROM AUTHOR]

The carbon trading market has become a powerful weapon in alleviating carbon emissions in China, and the carbon price is at the core of its operation. Hence, the carbon trading market serves as an indispensable component in forecasting the carbon price accurately in advance. This paper innovatively explores an ensemble‐driven long short‐term memory network (LSTM) model based on complementary ensemble empirical mode decomposition (CEEMD) for carbon price forecasting, applying it to all eight carbon trading pilots in China. The CEEMD was initially implemented for mode transformation in order to decompose the original complicated mode into a set of simple modes. Then, the partial autocorrelation function selected time‐lagged features as inputs for each mode. Subsequently, the LSTM was used to model the mapping between time‐lagged factors as well as each mode's target values, constructing multiple LSTM models for ensemble learning. Finally, the inverse CEEMD computation was introduced to integrate the anticipated results of the multi‐mode into the final results. Its practical application simultaneously embraced all eight carbon pilots in China, covering their corresponding carbon price data over a considerably long period. The obtained results illustrated that the proposed model driven by ensemble learning possessed sufficient accuracy in carbon price forecasting in China compared with the single LSTM model as well as other conventional artificial neural network models. Furthermore, according to the scope of its application, the innovative model exhibited strong stability and universality. [ABSTRACT FROM AUTHOR]

Most of the crude oil produced in China is highly viscous and easy to condense, and the pipeline transportation method is mostly heated. At present, frequency conversion technology is gradually applied to oil pump units. In order to find the best pipeline operation scheme, this paper is based on MATLAB programming software and established a corresponding mathematical model of oil pipeline energy consumption. This model innovatively takes the rotational speed of the variable frequency pump as one of the model optimization variables, calculating the pressure change and temperature change between stations of the pipeline, predicting the energy consumption of the pipeline and can guide the optimized operation of the pipeline, which has a high popularization and application value. An example of Qingtie Fourth‐line crude oil pipeline shows that among the genetic algorithm, particle swarm optimization, and simulated annealing algorithms for solving the optimization model, the particle swarm optimization algorithm has fast convergence speed, short optimization time, obtains the most optimal scheme, and can reduce energy consumption by 7.84%, which proves the practicability and creativity of the optimization model. [ABSTRACT FROM AUTHOR]

There is a growing interest in adaptive facade technologies to counter overheating problems and well‐being concerns in smart and high‐performance buildings. However, traditional literature review studies do not necessarily provide deep insights into the future trends of adaptive facade technologies. To address these limitations, this paper proposes a novel conceptual framework and technological classification for adaptive facades in the future. Our research methodology includes a literature review expert interviews and content analysis. In‐depth interviews with 27 international adaptive facade experts were conducted with a focus on the European context. The results categorize the adaptive facade technologies under four promising families and present a conceptual framework that identifies human‐centered design, smart building operating systems, service‐driven solutions, circularity, and materials as the main drivers of the facade technological advancements. Overall, this methodology yields new and rich qualitative knowledge related to adaptive facades; however, it has certain limitations, such as being time‐consuming. The research provides insights on future delivery processes and the future structural trends of adaptive facades. The new categorization and framework articulate the multifunctionality and performance requirements of facade technologies including smartness, automation, comfort, and well‐being. [ABSTRACT FROM AUTHOR]

Obtaining the most Stimulated Reservoir Volume (SRV) by forming a complex fracture network is the prerequisite for shale gas hydraulic fracturing. In this paper, a coupled DFN–DEM model is presented based on a realistic discrete fracture network from fracturing treatment, to simulate the complex interactions between a created hydraulic fracture and a natural fracture system in shale. The sensitivity analysis of numerical simulation was performed to investigate the effects of hydraulic fracture length, multi‐fracture spacing, and internal friction angle on the stimulation reservoir area. The simulation results revealed that regardless of the DFN distribution and the length of hydraulic fracture, shear failure always tracked on the existing natural fracture plane. The amount and depth of the natural fracture shear into formation increased as the hydraulic fracture grew in length. Moreover, the actual dynamic morphology of fracture network was the radial or dendritic. A drastic change of permeability along the distance from injection may stimulate the fracture networks especially near the wellbore. For the multi‐fracture, the opening of the second fracture was able to stabilize the sheared fractures at the tip of the initial fracture. The shear failure area around the second fracture tended to increase with the growth of the length of the second fracture. Fracture network connectivity in the system is better for the optimal fracture spacing, and then fluid penetration during injection will influence the permeability evolution during stimulation. The stimulation reservoir area of the fracture network and the natural fracture friction angle had a quadratic relationship. Finally, the results by the data from field measurement in Sichuan, China verified that the proposed coupled DFN–DEM model had an accuracy up to 91.7%. The research results provide a reference for predicting the development of fracture network far away for multistage fracturing treatment. [ABSTRACT FROM AUTHOR]

Supercritical carbon dioxide fracturing is an environmentally friendly anhydrous method. To study the propagation process during supercritical carbon dioxide fracturing, a full three‐dimensional model, coupled rock deformation, fluid transport, heat conduction, dynamic changes of carbon dioxide physical parameters, to investigate the process of fracture propagation during supercritical carbon dioxide fracturing, is established by the three‐dimensional boundary element method, the finite volume method, and finite difference method. And to solve the multiple physics coupling problems, a fully implicit solution and Newton‐Raphson iteration method are used. On the basis of this model established in this paper, the influential factors of supercritical carbon dioxide fracturing are analyzed. The results show that both of the reservoir temperature and the original in situ stress are important for carbon dioxide fracturing; The higher the reservoir temperature and the lower the initial in situ stress is, the longer and wider the fracture will be. The temperature of carbon dioxide at bottom is of no significance to the fracture length, fracture width, and the bottom hole pressure. A growing injection rate will lead to the increase of the fracture length and fracture width. This study would provide a reference for the fluid phase control of supercritical carbon dioxide fracturing technology. [ABSTRACT FROM AUTHOR]

Solar energy is a clean energy resource, so the large-scale deployment of photovoltaic ( PV) power generation is of great significance for achieving carbon emission reductions in the electric power industry. This paper proposes models and methods for evaluation of the low-carbon benefits of grid-connected PV power generation projects. The carbon emission (or emission reduction) characteristics and the economic benefits of PV generation are analyzed using the following four metrics: generation capacity revenue, PV cost, loss efficiency improvement, and reserve capacity cost. The corresponding low-carbon benefit models and economic benefit models are then established. By combining the low-carbon and economic characteristics of photovoltaic power generation, a model is proposed for evaluating the low-carbon comprehensive benefits ( LCBs) of photovoltaic power generation and the concept of a carbon emission payback period ( CPP) is put forward. Examples with typical operating data from real-world applications are used to verify the validity of the models and methods proposed in this paper. The analysis results show that photovoltaic power generation has great potential in terms of low-carbon comprehensive benefits compared with conventional power generation. [ABSTRACT FROM AUTHOR]

The vertically‐jointed coal seam, especially after water drainage, is easy to lead to large‐area coal wall spalling (CWS). To alleviate the problem, a strut subjected to equivalent central‐concentrated force was proposed for elaborating critical conditions for coal instability based on CWS characteristics, determining the main control factors. The sensitivity analysis of factors driving CWS revealed that the coal between 3.3 and 4.56 m was the most vulnerable. A microblasting technique was proposed for controlling CWS by increasing the friction coefficient at the weakened‐primary coal interface, improving the coal stress, and reducing the equivalent mining height. The paper presented the application of universal distinct element code models to simulate the CWS mechanism with different joint mechanical parameters and microblasting heights. The reduction of spalling intensity indicates that the microblasting weakening of the upper part coal could improve the overall stability of the coal. LS‐DYNA is employed for simulating the fractures development between blasting holes, and the rationality of optimized blasting parameters is revealed. The fracture characteristics of the observation hole in field demonstrated that the hole was effectively fractured by microblasting. The spalling parameters including depth, width and frequency were obviously reduced, which showed the rationality in microexplosion controlling spalling. [ABSTRACT FROM AUTHOR]

This paper explores artificial intelligent training schemes based on multilayer perceptron, considering back propagation and genetic algorithm (GA). The hybrid scheme is compared with the traditional support vector machine approach in the literature to analyze both fault and normal scenarios of a centrifugal pump. A comparative analysis of the performance of the variables was carried out using both schemes. The study used features extracted for three decomposition levels based on wavelet packet transform. In order to investigate the effectiveness of the extracted features, two mother wavelets were investigated. The salient part of this work is the optimization of the hidden layers numbers using GA. Furthermore, this optimization process was extended to the multilayer perceptron neurons. The evaluation of the model system performance used for the study shows better response of the extracted features, and hidden layers variables including the selected neurons. Moreover, the applied training algorithm used in the work was able to enhance the classifications obtained considering the hybrid artificial intelligent scheme been proposed. This work has achieved a number of contributions like GA‐based selection of hidden layers and neuron, applied in neural network of centrifugal pump condition classification. Furthermore, a hybrid training method combining GA and back propagation (BP) algorithms has been applied for condition classification of a centrifugal pump. The obtained results have shown the good ability of the proposed methods and algorithms. [ABSTRACT FROM AUTHOR]

Converting CO2, a major component of greenhouse gas in the atmosphere, into value‐added fine chemicals is beneficial from environmental and economic aspects. Except for various methods for CO2 reduction such as thermal catalysis, photocatalysis, electrocatalysis and biological reduction, hydrothermal reduction of CO2 to organics is becoming a novel and promising strategy. The hydrogen formed in situ from high‐temperature water could avoid the serious issues of hydrogen storage and transportation. This paper summarizes the recent advances on CO2 conversion to formic acid with metal‐ and biomass‐based compounds under hydrothermal conditions mainly focusing on the role of high‐temperature water, autocatalysis mechanism of metal reductants, and interfacial catalysis mechanism of metal/metal oxides. The effects of several experimental variables including temperature, reaction time and pH of the solution on formic acid yield are systematically illustrated as well. Finally, future efforts for fundamental researches and industrial applications of hydrothermal CO2 reduction are discussed. [ABSTRACT FROM AUTHOR]

Recently, phase change materials (PCMs) are acquiring much attention for the overall enhancement of photovoltaic (PV) systems' performance, because of their extraordinary property in temperature management. Many researchers have been incorporating PCMs in PV systems. However, the tested materials are principally organic PCMs. In this review, a comprehensive literature of PV systems with utilization of inorganic PCMs is introduced. Salt hydrates are the focus materials. They, in general, have comparative properties as organic PCMs and are better from safety and environmental standpoints. The characterization, properties, and applications of the salt hydrates in PV‐PCM research are discussed in this paper. Indeed, even most research shows promising outcomes, there is still need in data collection for more detailed and accurate system performance evaluation. Therefore, the real‐life application of this type of PV‐PCM system is still a long way from clear due to the discovered challenges. Finally, the possibilities of future research on PV‐PCM systems are highlighted, innovative technologies are to be discovered and addressed to defeat the current issues including system reliability and economic attainability. [ABSTRACT FROM AUTHOR]

Shale gas plays a crucial role in the national energy supply. However, fast pressure drop, production decline, and water resources pollution caused by well interference and fracture hits become more severe in multi‐layer mining shale gas fields. Such as, it is urgent to evaluate the interference of multi‐stage fracturing horizontal wells (MFHWs) between the upper and lower gas layers in Chinese Jiaoshiba shale gas field. Therefore, we put forward a comprehensive method to analyze the MFHW interference in this paper. The method contains bottom‐hole pressure response analysis (BHPRA) during neighboring well fracturing, BHPRA of well interference test, and production dynamic analysis. Our study indicates that longitudinal pressure interference exists between the Jiaoshiba upper and lower gas layers upon the apparent interference pressure response in a multi‐well test. However, MFHW interferences occur in the corresponding fracturing stages with shorter distance, and the interference strength is related to both well distance and fracturing scales. The Jiaoshiba upper gas layers can be developed to increase the gas production performance, but it is necessary to maintain a reasonable well spacing to avoid severe interference during the development. [ABSTRACT FROM AUTHOR]

Many calculation methods have been developed to forecast carbon emissions (CE). These methods can be classified into two categories: time series prediction and variables regression. However, time series prediction cannot fully use all CE‐related information and variables regression can only predict CE by knowing other variables in advance. To solve these problems, KLS is proposed in this paper which is a fusion of Kalman filter (KF), long short‐term memory (LSTM), and support vector machine (SVM). LSTM is used to predict CE as a time series, and 10 of 14 variables are selected by ridge regression (RR) to regress CE by SVM. Finally, KF is used to integrate the results of LSTM and SVM based on their variances. Overall, statistical filtering and deep learning algorithms are used in this paper, which achieved the fusion of time series prediction and variables regression. To confirm the effectiveness of KLS, we trained KLS model by CE from 1965 to 2005 and tested the model by the data from 2006 to 2014. The results showed KLS was more accurate than other four existing methods. Finally, we predicted the CE of China in next decade. [ABSTRACT FROM AUTHOR]

Liquid holdup is one of the most critical factors for the formation of pipe effusion, which is closely related to the efficiency of pipe transportation. Nowadays, liquid holdup is mainly estimated according to empirical or semiempirical correlation. Besides, little has been done concerning the accurate prediction of liquid holdup. Therefore, to obtain more precise forecast, this paper proposed a prediction method concerning liquid holdup in horizontal pipe with BP neural network algorithm. Meanwhile, a sensitivity analysis on the key factors impacting liquid holdup was conducted by the combination of the forecast calculation and orthogonal experiment design. The results showed that compared with the empirical calculation (the smallest standard deviation 8.65%), the BP neural network prediction model had achieved more accurate estimation (the average relative error is 7.38%). In addition, the sensitivity analysis indicated that the main indexes including pipe diameter, gas‐ and liquid‐phase superficial velocities, and temperature have significant influence on the liquid holdup. Pipe diameter, liquid‐phase superficial velocity, temperature, and viscosity are positively correlated with the liquid holdup, while pressure and gas‐phase superficial velocity are negatively correlated with it. [ABSTRACT FROM AUTHOR]

Traffic and vehicle simulations are often developed individually. However, vehicle performance is heavily affected by traffic conditions. Cosimulations of traffic and vehicle under real‐road situations can reflect the semi‐real‐world performance of vehicles, with traffic conditions being taken into considerations. This paper proposed an approach to combine the traffic and vehicle simulations that are realized by simulation of urban mobility (SUMO) and GT‐Suite software, respectively. In this paper, the sensitivities of the road grade and vehicle speed to the fuel economy and exhaust emissions were investigated; vehicle fuel consumption and regular exhaust emissions on a real‐road were analyzed; the effect of the traffic accident and congestions on fuel consumption and exhaust emissions were quantified. The results indicated that nitrogen oxides (NOx) and soot emission were consistent with fuel consumption rate, which was dominated by vehicle acceleration whose effect was aggravated by road grade. The fuel penalties caused by accident were in the range of 0.015‐0.023 kg depending on the severity of the accidents. The fuel consumption increased from 1.199 to 1.312 kg and 1.559 kg for 900 and 1800 vehicles/h traffic flow cases compared with 180 vehicles/h traffic flow. [ABSTRACT FROM AUTHOR]

The transportation and capture of particulate suspension in a rough fracture are widely encountered in hydrocarbon exploitation. According to a full review of the literature, traditional studies mainly focus on the placement and settlement of coarse particles such as proppants and lost circulation materials. Furthermore, a fracture is often considered to be equivalent to smooth parallel plates, whereas actual fractures are roughly walled with microconvex and are affected by normal stresses. The particulate suspension transport mechanism in a fracture under different normal stresses is still unclear. This paper proposes an approach to evaluate the permeability impairment caused by size‐exclusion of solid particles in a fracture under different normal stresses. The morphology of fracture flow space under different normal stresses is obtained by using optical scanning and FEM. Furthermore, the unresolved CFD‐DEM method is used to study the mechanism of the capture and migration of the particulate suspension in a fracture. The simulation results are in agreement with the experimental results. Furthermore, the effects of the particle size, particle concentration, injected particle volume, fracture occurrence, and applied pressure on particle invasion are discussed. [ABSTRACT FROM AUTHOR]

Nuclear magnetic resonance (NMR) T2 cutoff value is an important parameter for pore structure evaluation. It is complicated and uneconomical to obtain T2 cutoff value by an experimental method; therefore, it is necessary to explore a prediction method of T2 cutoff value. In this paper, 10 samples of tight gas reservoirs in the eastern Ordos Basin were selected, and then saturation and centrifugal experiments of nuclear magnetic resonance were carried out. On this basis, multifractal theory was introduced to calculate the multifractal characteristics of the NMR T2 spectrum of each sample, and the relationship between multifractal parameters and T2 value was analyzed. The influencing factors of the T2 cutoff value were clarified, and the prediction model of the T2 cutoff value was constructed accordingly. The results show that the T2 spectra of sandstones in the study area can be divided into three types: single steeple peak, double steeple peak, and irregular double peak. The pore diameter of the three types is 1 nm ~ 3×104 nm, 1 nm ~ 104 nm and 1 nm ~ 4×103 nm, respectively. The T2 cutoff value ranges from 9.72 to 35.16 ms. The correlation analysis suggests that the symmetrical fractal dimension difference and symmetrical multifractal dimension ratio (Dmin−Dmax, Dmin/Dmax) shows a positive linear correlation with the T2 cutoff value. The value of T2 cutoff gradually decreases with the increase of the flow zone indicator (FZI). Therefore, three parameters, including symmetrical fractal dimension difference, symmetrical multifractal number ratio, and FZI are optimized, and the prediction model for the NMR T2 cutoff value of sandstone samples in the study area is proposed. The introduction of porosity‐related parameters compensates for the shortcomings of previous T2 cutoff value prediction models. At the same time, the prediction model is proven to be accurate and reliable by testing the measured data of the samples near the study area. The results of this paper can be used for further study of the NMR T2 cutoff value prediction of tight sandstone reservoirs in different areas. [ABSTRACT FROM AUTHOR]

A new three‐dimensional fluid‐solid coupling fracture propagation model of synchronous fracturing was established to study the dynamic propagation process of simultaneous hydraulic fracturing. In this paper, we used an improved three‐dimensional boundary element method and a finite difference method, respectively, for calculating the deformation of the reservoir rock and the flow of the fracturing fluid during the fracturing process. The interaction between hydraulic fractures and nature fractures was also considered. Sensitivity analysis showed that during synchronous fracturing, the fractures between the wells attracted each other and injected with more fluid due to interference between the fractures. Affected by natural fractures, the trajectory of hydraulic fractures was more tortuous. Besides, the width and height of hydraulic fractures captured by natural fractures were reduced. In order to reduce the difference in length between individual fractures, smaller well spacing and larger cluster spacing should be used. [ABSTRACT FROM AUTHOR]

Grammatical Swarm is a search and optimization algorithm that belongs to the more general Grammatical Evolution family, which works with a set of solutions called individuals or particles. It uses the Particle Swarm Optimization algorithm as the search engine in the evolution of solutions. In this paper, we present a Grammatical Swarm algorithm for total energy demand estimation in a country from macroeconomic variables. Each particle in the Grammatical Swarm encodes a different model for energy demand estimation, which will be decoded by a predefined grammar. The parameters of the model are also optimized by the proposed algorithm, in such a way that the model is adjusted to a training set of real energy demand data, selecting the more appropriate variables to appear in the model. We analyze the performance of the Grammatical Swarm evolution in two real problems of one‐year ahead energy demand estimation in Spain and France. The proposal is compared with previous approaches with competitive results. [ABSTRACT FROM AUTHOR]

During the multiseam mining process, the overlying strata were damaged due to different mining disturbances, where a large number of fractures were produced which were the main seepage paths of gas and water, easy to cause gas or water inrush accidents. Thus, it is necessary to explore the development characteristics of the fractured zone in the overlying strata from multiseam mining. In this paper, laboratory triaxial compression tests were firstly conducted on the rock specimens subjected to different mining disturbances. In these tests, the specimen was loaded to different stress before a regular test to simulate the different damage effects on the rock strata caused by different mining disturbances. And the corresponding values of m and s could be obtained through a calculation based on the test results. Subsequently, the numerical simulation was conducted to simulate the field situation, in which the m and s values were used in the numerical model combined with the Hoek‐Brown–modified criterion, and the results show that the overburden failure height was increased with the mining disturbances from 48 to 120 m, and then, the effects of mining height and interval thickness on the development height of fracture zone were studied by numerical simulation. Finally, the leakage of roof drilling at different stages was tested and calculated in the field. The results showed that the loss of leakage drilling can directly reflect the development degree of roof cracks, and the detection results were close to the development height of the numerical simulation fracture zone. It is verified that the simulation method used in this paper is feasible and can be used as a reference for similar research. [ABSTRACT FROM AUTHOR]

Regulation of DC‐bus voltages is important for the stable operation of different applications, like microgrids and electric vehicles, and it is usually performed by charging/discharging (C/D) batteries. Such C/D system is formed by a power converter and a control system, and it is aimed at guaranteeing the system stability and extending the battery life. To extend the battery life, it is important to reduce the battery current ripples, which is usually performed with interleaved converters and nonlinear controllers; however, most of those controllers do not provide the design procedure nor guarantee the system stability. This paper proposes a nonlinear control strategy to regulate the voltage in a DC‐bus by C/D a battery through a two‐branch interleaved Boost converter. The proposed control strategy is formed by two sliding mode controllers (SMCs), where the first one regulates the DC‐bus voltage by acting on the first converter branch and the second SMC controls the current in the second branch. The reference of the second SMC is generated from the delayed current of the first branch, in order to coordinate the controllers and to reduce the ripples in the battery current. The paper includes a procedure to design the two SMCs as well as simulation and experimental results to validate the proposed solution and to illustrate its performance. The results prove the system stability and its dynamic performance according to the design. [ABSTRACT FROM AUTHOR]

Over the past years, wind energy has been considered as a promising solution for clean and sustainable energy development, but wind curtailment remains a challenge to wind power development. On this basis, utilization of non‐grid‐connected wind power becomes crucial and necessary as it can mitigate wind curtailment and improve energy efficiency. This paper proposes the collaboration strategy and optimization model of wind farm‐hybrid energy storage system (WF‐HESS) for non‐grid‐connected wind power based on battery and superconducting magnetic energy storage (SMES) whose combination can effectively cope with fluctuation and intermittence of wind input. The optimization problem is simultaneously investigated by the minimization of total cost, wind curtailment magnitude, and loss of power supply probability (LPSP). The multi‐objective particle swarm optimization (MOPSO) is introduced to find available solutions, and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied to determine the optimal one. Results are obtained for a case study, and the effectiveness and the feasibility of proposed model are verified by a comparative analysis and a sensitivity analysis. Results analysis and discussion show that the WF‐HESS model and the application of HESS have important influence on promoting utilization of non‐grid‐connected wind power and mitigating wind curtailment. [ABSTRACT FROM AUTHOR]

Taking full advantage of geological conditions is beneficial to reduce the development cost and enhance the exploit of geothermal energy in the Gonghe Basin. In this paper, a thermal‐hydraulic coupled model is put forward to study the heat extraction for Gonghe Basin based on local thermal nonequilibrium theory considering the natural fault. An excellent heat recovery system and reasonable combination of parameters are the premise of sustainable geothermal development. Two doublet systems are introduced to investigate the efficiency of the fault/fracture‐controlled EGS model. A comparative analysis is performed from the aspect of production temperature, heat extraction ratio, flow impedance, injection pressure, thermal power, and electric power. Key parameters (injection rate, injection temperature, production pressure, number of fractures, vertical interval between the two storages, and the storage permeability) are discussed. The results show that the fault‐fracture–controlled doublet model is more suitable for EGS to heat transfer than the common doublet model. The doublet model at a depth of 3300‐3800 m has a temperature gradient of 0.04°C/m. For fault‐fracture–controlled EGS model, the optimal values are 50 kg/s, 15 MPa, 60°C, 310 m, 4 × 10−14 m2, and two for injection rate, production pressure and injection temperature, vertical interval, storage permeability, and fracture number, respectively. The best well pattern layout method for the Gonghe Basin is one injection well and two production wells. The production temperature varies from 196.8°C to 192.7°C when the heat extraction ratio is 0.13 at the end of the operation. Thus, the fault‐fracture–controlled EGS model can provide a mining method and advance the development of geothermal energy for the Gonghe Basin in the future. [ABSTRACT FROM AUTHOR]

As China's power market becomes more orderly, electricity retailing companies are influenced by multiple factors restricting their healthy, stable, and sustainable development. This paper explores these issues through four dimensions, the external basic environment, operating credit risk, financial credit risk, and transaction credit risk, and determines the credit risk evaluation index system, which includes 22 factors relevant to electricity retailing companies. To achieve this, this paper utilizes the characteristics of the intuitionistic fuzzy set theory and, in an uncertain environment, the proposed credit risk assessment model based on the intuitionistic fuzzy analytic hierarchy process (IFAHP). In order to improve the identification degree of the credit risk evaluation of electricity retailing companies, a penalty factor is introduced into the model, and the variable weight mechanism of dynamic adjustment hesitancy is proposed. Finally, we select five electricity retailing companies and use different evaluation methods to conduct a comprehensive credit risk evaluation, so as to improve the credit risk level of electricity retailing companies. [ABSTRACT FROM AUTHOR]

Ice accretion on wind turbine blades is one of the major faults affecting the operational safety and power generation efficiency of wind turbines. Current icing detection methods are based on either meteorological observing system or extra condition monitoring system. Compared with current methods, icing detection using the intrinsic supervisory control and data acquisition (SCADA) data of wind turbines has plenty of potential advantages, such as low cost, high stability, and early icing detection ability. However, there have not been deep investigations in this field at present. In this paper, a novel intelligent wind turbine blade icing detection method based on the wind turbine SCADA data is proposed. This method consists of three processes: SCADA data preprocessing, automatic feature extraction, and ensemble icing detection model construction. Specifically, deep autoencoders network is employed to learn multilevel fault features from the complex SCADA data adaptively. And the ensemble technique is utilized to make full use of all the extracted features from different hidden layers of the deep autoencoders network to build the ensemble icing detection model. The effectiveness of the proposed method is validated using the data collected from actual wind farms. The experimental results reveal that the proposed method is able to not only adaptively extract valuable fault features from the complex SCADA data, but also obtains higher detection accuracy and generalization capability compared with conventional machine learning models and individual deep learning model. [ABSTRACT FROM AUTHOR]

Vehicles are subject to a variety of road unevenness and random road excitations that potentially cause the vehicle to undergo a significant amount of energy dissipation, while compromising energy efficiency. This paper focuses on designing a novel piezoelectric energy harvester and aims to assess the energy harvesting potential, from the vehicle suspension, under random and pulse road excitations. To describe the energy harvesting process, a dual‐mass suspension system vibration model of a light electric logistics vehicle, equipped with a piezoelectric energy harvester, is developed. Various parameters, such as driving speed, ratio of the moment arms of the lever, and piezoelectric material cross‐sectional area, are included in the model, for basic harvesting energy. The root mean square (RMS) value of harvested power, in the case of random road, is up to 18.83 W, while the maximum respective value, in the case of pulse road, is 102.24 W and is obtained at 30 km/h. The harvested electricity is very valuable and useful, as it can be used to power automotive electrical equipment. The results of this paper provide an important reference frame for future research, related to energy harvesting from vehicle suspension. [ABSTRACT FROM AUTHOR]

Due to the complex geostress and mining conditions in the coal seam with depth of 800 m, stability of surrounding rock for gob‐side entry retaining is very difficult to achieve. In this paper, we firstly propose an innovative bolt‐grouting controlled roof‐cutting for gob‐side entry retaining (BCR‐GER) approach for deep coal mines. Secondly, a mechanical model of "surrounding rock‐supporting body" for BCR‐GER is constructed, which consists of coal wall, roadside props, and gangues in gob (the whole supporting body). Thirdly, the key parameters (ie, cutting height, cutting angle, grouting cable length, and row of roadside props) are designed. Finally, field practice was applied at the No. 31120 haulage roadway of the Suncun coal mine in China, and in situ investigations were conducted for verification. Field measurement results show that maximum convergences of roof‐to‐floor and side‐to‐side were 264 mm and 113 mm, respectively. What is more, the maximum support resistance of roadside props was reduced by approximately 58%. The deformation and failure of surrounding rock were effectively controlled, and the pressure on roadside props was greatly reduced. This research fully considers the bearing properties of gangues in gob, eliminates the secondary disasters caused by borehole blasting, and provides guidance and reference for deep surrounding rock control of the same or similar gob‐side entry. [ABSTRACT FROM AUTHOR]

Exhaust emissions from diesel engine powered vehicles are considerably high during cold start and warm‐up, because of the poor catalyst performance due to the insufficient catalyst temperature. The controlled heat injection allowed by electrically heated catalysts can effectively reduce the catalyst light‐off time with relatively moderate fuel penalty. This paper compares the exhaust temperature and emissions of a case study diesel vehicle in cold and warm start conditions, and proposes two electrically heated catalyst control strategies, which are evaluated in terms of emission reduction and energy consumption with different target temperature settings. In addition, a new performance indicator, that is, the specific emission reduction, is used to evaluate the after‐treatment system and associated thermal management. For the worldwide harmonized light vehicle test cycle, the results without electrically heated catalyst show that from both cold and warm start conditions a large amount of operating points of the engine is located in the region of partial catalyst light off. Moreover, emissions, especially in terms of carbon monoxide and hydrocarbon, significantly decrease with the electrically heated catalyst implementation, for example, by at least 50% from cold start; however, they still tend to be rather substantial when the fuel is re‐injected after the engine cutoff phases. The exhaust temperature is lower than the target values in the sections of the driving cycle in which the electrically heated catalyst power is saturated according to the maximum level allowed by the device. The carbon dioxide penalty brought by the electrically heated catalyst ranges from 3.93% to 6.65% and from 6.49% to 9.35% for warm and cold start conditions, respectively. [ABSTRACT FROM AUTHOR]