Journal of Energy Engineering

Wind speed power characteristics are essential in evaluating the state of the wind turbine. The supervisory control and data acquisition (SCADA) data are massively collected and could be important resources for condition monitoring and anomaly detection of wind turbines if properly utilized. A systematic early-stage anomaly detection framework is built in this work consisting of three phases: (1) an improved data cleaning algorithm based on kernel density estimation (KDE) is presented to remove outliers of SCADA data where the constraint of the Gaussian distribution assumption is eliminated for describing the real distribution of power outputs in each wind speed interval; (2) deep neural networks (DNNs) are used to establish a multivariate power curve (MPC) model where the dependencies of multidimensional variables on power output are considered and selected by Pearson correlation analysis; and (3) the sequential probability ratio test (SPRT) is adopted to estimate the distribution of power residuals and used for anomaly detection and early warning. The case studies verified the efficacy of the proposed framework where 91 faults from 38 wind turbines in two wind farms are successfully detected in the early stage.

The increasing integration of electricity and heating networks escalates the operation risk of an integrated energy system (IES). The vulnerable components in IES, which play an important role of aggravating the spread of IES failures, is one of the most important parts of risk control for IES operation. To ensure the operation security and stability of IES, an operation optimization method considering the vulnerability prevention for an electricity–heat IES is proposed in this paper. The method contains two main stages: vulnerability identification and optimal operation. First, the IES cascading failure space-time graph (CFSTG) is formed by simulating the cascading failure development stages in IES, which can effectively measure the impact of vulnerable branches on the cascading failure depth and breadth. Then, the vulnerable branches of IES are initially identified based on indices of node degree calculated according to CFSTG. In order to further screen and correct the initial identification results, a prevention–correction hybrid control strategy is proposed. On this basis, a day-ahead optimal operation bilevel model is established. Overall IES operating cost and static security are taken into account in the outer layer of the model to optimize electricity and heat output of each energy hub. After obtaining a multiobjective optimal energy flow distribution of IES, the inner layer of the model is developed to optimize the output of each unit in the energy hubs. Finally, an IES test system is utilized as an example to verify the effectiveness of the proposal method.

The performance of Lithium-ion batteries (LIBs) is seriously affected by temperature rise and mechanical degradation during the charge or discharge. In this work, a fully coupled thermomechanical model with the total heat generation rate is developed to analyze the mechanism of the temperature rise and stress distribution. Then numerical simulations are performed to show the evolution of temperature and stress for 18650 LIBs. The comparisons of the surface temperature evolution between the present model and experimental results, and the temperature variation with radius between the present model and the pure thermal model are made, respectively. Finally, the influences of some design parameters upon the Li-ions concentration and the stress are discussed. The numerical results show that the present model is more validated against the pure thermal model, and the temperature and stress will be reduced if the positive electrode particle radius, the volume fraction of the positive active material and the initial electrolyte salt concentration are decreased, or the positive electrode thickness is increased which will provide some guides for the design of LIBs.

In the present investigation, a modified Savonius hydrokinetic turbine of 0.245 m turbine diameter ($D$), 0.1 overlap ratio, 0.2 shape factor, and 0.002 m blade thickness ($t$) has been investigated numerically to study the influence of extension ratio on the performance of the turbine. The effect of vane end extension on the performance of the Savonius hydrokinetic turbine is investigated by numerical simulations. Two-dimensional transient simulations are done with a pressure-based solver by keeping the diameter of the turbine constant. The study is carried out in a finite-volume solver by using unsteady Reynolds Navier-Stokes equations with a $k\text{-}\omega$ shear stress transport turbulence model. The coefficient of torque is considered for the 12th revolution of the turbine for different extension ratios of 0, 0.041, 0.082, 0.122, 0.163, and 0.204. The maximum instantaneous coefficient of torque ($C_t$) is obtained for vane orientations of 100° to 130° and 280° to 310°. The maximum coefficient of power ($C_p$) of the turbine is 0.2441 for an extension ratio of 0.041, which is 15.5% higher than that of the turbine with a zero-extension ratio.

The flow regime of gas migration and production in a low-permeability coal seam includes desorption, diffusion, low-velocity nonlinear seepage, and linear seepage. However, the current field test methods of coal seam permeability in China are all based on linear seepage theory, leaving out the low-velocity nonlinear seepage with gas threshold pressure gradient. Therefore, a field test method for gas threshold pressure gradient and permeability is established in this paper. First, the two upward cross seam boreholes (the piezometric borehole and gas extraction borehole) are constructed in the untapped area of the floor drainage roadway with the low-permeability coal seam. After sealing the holes, the pressure measurement and gas extraction are carried out, respectively. Then, a radial flow mathematical model considering the gas threshold pressure gradient was constructed, and the model was solved by the COMSOL Multiphysics software. Finally, the gas threshold pressure gradient and permeability of the coal seam were obtained by fitting the simulated data of gas pressure and flow to the measured data in the field. The method was applied to the test of gas threshold pressure gradient and permeability before and after the hydraulic punching. Field test results show that this method can more accurately characterize the permeability in the gas extraction process of low-permeability coal seam than the traditional method.

Abstract

The evaluation method for determining the pore production range during ${\mathrm{CO}}_2$ displacement in shale cores is established based on ${\mathrm{CO}}_2$ displacement experiments, core analysis using online nuclear magnetic resonance (NMR), and pore size analysis using high-pressure mercury injection. By transforming the abscissa of the NMR $T_2$ spectrum into pore-throat radius using the conversion formula between relaxation time and pore radius, the production behavior of crude oil in pores of different scales during ${\mathrm{CO}}_2$ displacement is analyzed. The target shale oil reservoir, located in eastern China, consists of two sets of salt beds. Crude oil is predominantly found in mesopores and smaller macropores. While water injection can saturate the salt and enhance seepage, the reactive areas of water imbibition are still smaller compared to those of ${\mathrm{CO}}_2$ injection. It is observed that the displacement efficiency of ${\mathrm{CO}}_2$ injection exhibits a negative correlation with the clay mineral content, with the swept pores mainly consisting of mesopores and small macropores. The proportion of crude oil produced from pores with diameters less than 0.1 μm during ${\mathrm{CO}}_2$ displacement is significantly higher than that during water displacement. The displacement effect of ${\mathrm{CO}}_2$ in mesopores and smaller macropores improves with increasing injection pressure. Above the miscible pressure condition, the oil displacement efficiency of ${\mathrm{CO}}_2$ is 11% higher than that of water displacement, indicating that ${\mathrm{CO}}_2$ displacement is more suitable for this shale oil reservoir.

Practical Applications

Exploiting oil from shale formations through water injection is challenging due to the presence of micrometer or nanoscale pores. However, in the target reservoir, which is a typical saline deposition, both water injection and gas injection, such as supercritical ${\mathrm{CO}}_2$ injection, are suitable for enhancing oil recovery. When compared to water injection, supercritical ${\mathrm{CO}}_2$ injection offers advantages such as higher injection capacity, wider swept volume, and better displacement effect. It is particularly effective in producing oil from pores smaller than 0.1 μm. Furthermore, increasing the ${\mathrm{CO}}_2$ injection pressure improves the displacement efficiency. In this type of shale oil reservoir, the average oil displacement efficiency of ${\mathrm{CO}}_2$ displacement is nearly 11% higher than that of water displacement. This method not only provides energy for the reservoir and enhances shale oil recovery but also contributes to carbon storage, making it an advanced approach for shale oil reservoir development.

A fracture network as the main channel of seepage and heat transfer has been a key focus in an enhanced geothermal system. The fractures in the geothermal reservoir usually have a strong multiscale nature in length, but the impacts of each scale fracture on geothermal reservoir productivity have not been studied so far. This paper investigates these impacts based on a discrete fracture matrix model. Firstly, the fractures are divided into four scales of micro-scale, small-scale, medium-scale, and large-scale in the dimension of a representative volume element (RVE). Secondly, governing equations are carefully formulated for matrix deformation, matrix percolation, fracture percolation, matrix heat transfer, and fracture heat transfer, thus a thermal-hydraulic-mechanical (THM) coupling model is established. Thirdly, the distribution of pore pressure and temperature, the fluid flow in fractures, and the deformation of multiscale fractured reservoirs are numerically simulated and those numerical results are comprehensively evaluated by three indicators. Finally, the impacts of each scale fracture on geothermal reservoir productivity are explored. The productivity of reservoirs with single-scale and full-scale fractures is compared. It is found that three pressure zones are formed along the mining direction in the fractured geothermal reservoir: high-pressure zone, medium-pressure zone, and low-pressure zone. Both pressure and temperature influence the reservoir deformation with a trend of first decreasing and then increasing. The impact of large-scale fractures on the steady power and cumulative heat recovery exceeds 90%. Excessive heat production from single medium-scale and large-scale fractured reservoirs induces a local thermal breakthrough prematurely. In contrast, the synergistic action of multiscale fractures can prolong thermal breakthrough time and maintain the reservoir at a higher steady power.

Gas flooding is a key technique for increasing coalbed methane (CBM) production of declining wells in coal mining areas. Nitrogen is clean, pollution-free, low-cost, and relatively safe compared with carbon dioxide. In this study, nitrogen drive experiments were conducted under different conditions using a coal–gas–liquid relative permeability device and gas chromatography. The effects of the temperature, intermittent time, nitrogen purity, and displacement pressure on the output characteristics were investigated, and then, field tests were conducted. The results show that with increasing displacement time, the produced gas volume and flow rate are dominated by methane at the beginning and then quickly transform into nitrogen. The volumes of both methane and nitrogen are positively correlated with the displacement time via a power function. Additionally, increasing the nitrogen temperature, intermittent time, nitrogen purity, and injection pressure can effectively increase methane production. In the field test conducted in the Fanzhuang block in the Qinshui Basin, China, the methane production of 10 monitoring wells was $\mathrm{11,700}{\mathrm{m}}^3/\mathrm{day}$, which was $\mathrm{2,700}{\mathrm{m}}^3/\mathrm{day}$ higher than that before nitrogen injection. This paper provides an optimized scheme for the stimulation of CBM via nitrogen displacement in coal mining areas, which has a good application prospect.

Abstract

As continental shale oil is explored and developed on a larger scale, its high starting pressure gradient in the shale matrix poses challenges for flow. This paper investigates the effect of imbibition development and the mechanism of oil mobilization under high temperature and high pressure using self-developed dynamic huff-n-puff imbibition equipment based on micropore and percolation characteristics. Using six different injection fluids—slickwater, imbibition agent CY-IMNF-1, sand-carrying agent, guanidine gel breaking fluid, imbibition agent #G-1, and ${\mathrm{CO}}_2$—this study involved an experimental investigation of high-temperature and high-pressure huff-n-puff imbibition at a pressure of 30 MPa and a temperature of 110°C. The effect of injection fluids on imbibition development recovery is analyzed, and the contribution of different scale pores to the oil recovery of continental shale is quantified. It was found that slickwater huff-n-puff resulted in the highest imbibition oil recovery, followed by imbibition agent CY-IMNF-1. Shale oil production in nanopores and micropores was mainly achieved through slickwater huff-n-puff, and the pore and throat size limit for oil mobilization was found to be 4–7 nm. Based on a synergy perspective, optimizing the hybrid system of slickwater and ${\mathrm{CO}}_2$ is suggested. This study provides technical support for developing similar continental shale reservoirs with high-temperature and high-pressure huff-n-puff imbibition.

Practical Applications

Based on a self-made experimental device and two-dimensional (2D) nuclear magnetic resonance testing, the quantitative evaluation method of sensitivity of different shale pores to external fluids is established. The results show that the oil recovery rate of imbibition using sliding water is the highest, the oil in nanopores and micropores is mainly produced through huff-n-puff by slickwater, and the limit radius of oil mobility in pores and throats was found to be 4–7 nm. The research findings have important implications for huff-n-puff experiments and the formulation design of shale fracturing fluid systems.

Accurate power load forecasting could provide a scientific basis for the rapid response and stable operation of a modern power system. To take advantage of the meteorological big data to improve short-term forecasting accuracy, while considering the nonlinear and spatiotemporal correlation characteristics of the power load data, this paper proposes a short-term power load forecasting method based on meteorological data dimensionality reduction and a hybrid deep neural network. First, the elastic network is used to reduce the dimensions of high-dimensional meteorological big data, eliminate irrelevant meteorological factors, and improve the quality of input data. Then, taking the dimension-reduced meteorological data and historical load data as input, a load forecasting model based on a novel deep neural network is established. This model uses a convolution neural network (CNN) and a bi-directional long short-term memory (BiLSTM) neural network to extract the spatial and temporal correlation features of power load related data, and combines the attention mechanism to enhance the learning weight of the load series in important periods, and adopts residual connection (RC) to optimize the network training speed and alleviate the overfitting problem. Finally, taking the open data set of the New York Independent System Operating Agency (NYISO) as an example, single-step and multi-step advance prediction experiments are carried out to verify the advantages of the proposed method.

The diesel fuel/natural gas compression ignition engine is an essential approach to achieving low-carbon goals. The injection parameters of the diesel assume a critical role in the combustion process of mixture formation and ignition of methane. The micro-orifice diesel fuel nozzle was developed based on the spray mixture theory of diesel injection in a modified engine. The combustion and emissions of injection strategy of rail pressure, multiple injections and injection timing, and different rate of substitution (Rs) under two loads are discussed and compared with the original nozzle in the compression ignition engine. The results show that the combustion center of the micro-orifice nozzle moves forward with increasing Rs. In contrast, the original nozzle presents an opposite trend. The combustion and emissions of the two nozzles are almost identical at high Rs. The atomization improvement of reduced orifice size does not significantly affect the performance and emissions with a single injection strategy. The thermal efficiency of the micro-orifice nozzle reached 43.2% at high Rs, and the total hydrocarbons (THC) was reduced by 85% compared to the original nozzle, which is a main reason for the increased efficiency at high load. The effect of improved atomization by higher pressure in multiple injections is weaker than the effect of the insufficient wet wall caused by excessive penetration. The micro-orifice nozzle with early injection and low pressure of 70 MPa can improve the atomization and shorten the diesel spray penetration, reducing unburned THC emissions and achieving higher thermal efficiency. The closer the pre-injection timing is to top dead center (TDC), the earlier the combustion starts and the higher the maximum heat release rate (HRR). The definition of the combustion delay in a traditional diesel engine is not easy to clearly describe the fuel and oxygen mixing process in the cylinder during diesel pre-injection and natural gas (NG) premixing. The shape of the HRR of the micro-orifice nozzle at different main injection timing has always maintained a similar shape of single-peak HRR, which only shifts back and forth with changes of the main injection timing. The micro-orifice nozzle with pre-injection strategy forms a homogeneous mixture in the cylinder. At the same time, the main injection of diesel is only used to stabilize the ignition. The THC emissions and thermal efficiency are not sensitive to the main injection timing. They are maintained at an ideal level, freeing the diesel engine efficiency from the limitation of the diesel injection timing. Hence, the micro-orifice nozzle combined with the two-injection strategies achieves ideal premixed combustion.