Abstract Copyrolysis, being an active area of research due to its synergistic impact in utilizing diverse fuel resources, including waste materials, like, peach stone (PS), has been the focal point for this study. PS, produced in vast quantities annually and typically intended for landscaping or insulation purposes, is being studied in combination with low‐grade bituminous coal for energy utilization focusing on thermokinetics and synergistic aspects. Coal‐peach stone (C‐PS) blends were formulated at different ratios and subjected to comprehensive characterization techniques, including ultimate analysis (CHN‐S), gross calorific value (GCV), Fourier transform infrared spectroscopy, and thermogravimetric analyzer (TGA). The ultimate analysis revealed an enhancement in carbon and hydrogen content from 45.38% to 68.08% and from 3.89% to 6.96%, respectively. Additionally, a reduction in sulfur and nitrogen content from 0.54% to 0.11% and from 1.16% to 0.42%, respectively, was observed with an increase in the ratio of PS in the C‐PS blends. The GCV of C‐PS blends ranged from 20.75 to 26.01 MJ kg−1. The pyrolysis conditions simulated in TGA are pivotal for evaluating thermokinetics and synergistic effects. The 60C:40PS blend shows a positive synergy index (SI) value of 0.0203% concerning total mass loss (MLT) indicating a favorable condition for bio‐oil generation. Coats–Redfern model‐fitting method reveals that the activation energy (Ea) of C‐PS blends increases in Section II with the addition of PS, and conversely, it decreases in Section III. The Ea for 100PS and 100C was 106.76 and 45.85 kJ mol−1 through (D3) and (F1), respectively, which was improved through the optimal blend 60C:40PS with an Ea of 94.56 and 27.58 kJ mol−1 through (D3) and (F2), respectively. The values obtained from linear regression prove that the kinetic models are effective while the thermodynamic analysis indicates that the pyrolytic behavior of C‐PS blends is characterized as endothermic, nonspontaneous, and capable of achieving thermodynamic equilibrium more rapidly.

Abstract The power electronic converters and grid‐connected filters were important components of the permanent magnet direct drive wind power generation system whose performance directly determines the quality of wind power generation. In past modeling, analysis, and control studies, capacitive and inductive components were often treated as integral‐order components. However, the inductance and capacitance components in the actual permanent magnet direct drive wind generator were fractional‐order components, and their electrical characteristics will change with the change of order, which had an important impact on the dynamic and static characteristics of the system. In this paper, the mathematical model of the fractional‐order LCL (FOLCL) filter was derived. Through simulation, it could be seen that the FOLCL filter can avoid resonance fundamentally. At the same time, the fractional‐order PI (FOPI) controller was introduced into the machine‐side current converter, and the parameters of the FOPI controller of the outer speed loop and the inner current loop were adjusted by using the time‐domain optimization method. The results showed that the efficiency of the FOPI controller was significantly better than that of the integer‐order PI controller in realizing maximum wind energy capture. It provides theoretical support and practical application value for the stable operation of the wind power generation system.

Abstract Clarifying the influencing factors of energy consumption in underground production processes of coal mine is the premise and foundation for the coal mining industry to control the energy consumption and intensity to achieve the goal of carbon peak and carbon neutrality. This paper aims to investigate and compare the differences in energy consumption and carbon emissions between a mining‐separating‐backfilling integrated coal mine (MSBICM) and a traditional coal mine and explore the effects of the main production links underground on carbon emission intensity in coal mines. Hence, taking an MSBICM in Henan province as an example, this study constructed an energy consumption and carbon emission model of the mine using system dynamics (SD) method. Based on this model, the energy consumption of the main production logistics system and auxiliary production system in MSBICM was simulated and analyzed. In addition, this study made a comparative analysis of the energy consumption of the different production links in the two types of coal mines. The results showed that: (1) the comprehensive mechanized coal mining with solid filling system and ventilation system were the subsystems with the highest and lowest energy consumption in MSBICM respectively. (2) The influence rates of raw coal mining, gangue filling, coal‐gangue separating, and material transportation on carbon emission intensity in coal mine were 1.09%, 1.34%, 1.09%, and 5.13%, respectively. (3) Under the same production and filling targets, energy consumption of underground transportation systems in MSBICM was found to be 336.66 tons of standard coal less than that in traditional coal mine. This study has helped clarify the complex relationships among the factors that influence energy consumption in coal mines and provided a reference for implementing dual control of energy consumption to promote low‐carbon mining of coal resources.

Abstract In this paper, a combined method is proposed to improve the accuracy of an electrical equivalent circuit model (EECM) and state‐of‐charge (SOC) estimation in situations where a lithium‐ion battery is frequently charged and discharged. To calculate the terminal voltage in the dynamic region, where charging and discharging are frequently repeated at 0.1 s intervals, a specific region is determined and historical weight is selected, based on the amount of charge in that region, to reflect the model parameters. The historical weights are applied to the charging and discharging parameters to improve the estimated performance of the EECM in estimating the terminal voltage of the battery. Also, the improved EECM is applied to the extended Kalman filter to improve the performance of SOC estimation. A 21,700 cylindrical lithium nickel manganese cobalt oxide‐type battery was used for verification, and the parameters required for modeling were extracted through experiments that were conducted to determine electrical characteristics. This paper compared two models not considering the history of charging or discharging characteristics with a model considering history to verify the accuracy of voltage and SOC estimation results. The result shows that the voltage and SOC estimation errors of the proposed combined method are the lowest in the three cases.

Despite the recent discoveries of considerable fossil fuel reserves, Brazil is one of the only great economic and industrial powers with very high amounts of renewable energy in its electricity matrix. Approximately 79.3% of the electric energy supply comes from renewable resources, of which hydroelectric power represents 70.6%. The two primary concerns regarding hydroelectricity are the damage caused to the environment by the construction of dams and the uncertainty of the supply in cases of long drought seasons. This article presents an analysis on the availability and energy exploitation of sugarcane straw and forest residues derived from eucalyptus for decentralized generation using a Geographic Information System–based model. The potential bioelectricity and bioethanol production from sugarcane and eucalyptus biomass in the Administrative Region of Campinas (ARC) is higher than the demand in this region. The results provide guidelines for designing alternatives to the intended Nationally Determined Contributions in Brazil within the scope of the ARC, and they can be used to provide energy empowerment, electric matrix diversification, and new policies that address the residue availability and demand.