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The fluctuation and uncertainty of the electricity load bring challenges to load forecasting. Traditional point forecasting struggles to avoid errors, and pure interval forecasting may cause the problem of too wide an interval. In this paper, we combine point forecasting and interval forecasting and propose a point-interval forecasting model for electricity load based on regular fluctuation component extraction. Firstly, the variational modal decomposition is combined with the sample entropy to decompose the original load series into a strong regular fluctuation component and a weak regular fluctuation component. Then, the gate recurrent unit neural network is used for point forecasting of the strong regular fluctuation component, and the support vector quantile regression model is used for interval forecasting of the weak regular fluctuation component, and the results are accumulated to obtain the final forecasting intervals. Finally, experiments were conducted using electricity load data from two regional electricity grids in Shaanxi Province, China. The results show that combining the idea of point interval, point forecasting, and interval forecasting for components with different fluctuation regularity can effectively reduce the forecasting interval width while having high accuracy. The proposed model has higher forecasting accuracy and smaller mean interval width at various confidence levels compared to the commonly used models. [ABSTRACT FROM AUTHOR]

Borehole cataloguing is an important task in geological drilling. Traditional manual cataloguing provides the stratification of underground boreholes based on changes in core lithology. This paper proposes a novel borehole cataloguing method using a drilling process monitoring (DPM) system. This DPM cataloguing method stratifies a borehole according to the drilling speed through the rock. A 102 m borehole was drilled and cored in Baota district, Yan'an city, Shaanxi Province, China. The rock-breaking response parameters of the drill bit displacement, drill rod rotation speed and inlet pipe and outlet pipe oil pressures were monitored throughout the drilling process, and the drilling depth-penetration rate curve during the net drilling process was obtained. The changes in drilling speed show that the DPM cataloguing can identify the depths of the layer interfaces of the borehole and describe the stratification. The interface depth values obtained by DPM have little difference from the interface depth values obtained by manual cataloguing, and the errors are between −0.04% and 4.29%. From the DPM stratification results, the engineering quality evaluation of the rock mass can be realized without coring. DPM is fast, convenient, accurate, can greatly improve the efficiency of existing catalogues, and can be applied to scientific research in any underground space. DPM is a measurement-while-drilling technology. According to DPM data, the operating state of a drilling rig and the parameter changes while drilling can be obtained in situ and in real time throughout the drilling process. [ABSTRACT FROM AUTHOR]

Mineralogical and geochemical characteristics of coals provide crucial information on their potential clean, efficient, and integrated utilization. In this paper, the mineralogical and geochemical behaviors of the No. 5 coals of the Taiyuan Formation in the Weibei Coalfield, North China, were investigated, and their geological controlling factors were subsequently discussed. The minerals in the Weibei coals mainly consist of kaolinite (8.3%), calcite (5.0%), and pyrite (3.1%), with minor proportions of tobelite (2.9%), dolomite (1.7%), quartz (1.8%), and traces of siderite (0.4%) and gypsum (0.6%). Several critical elements, including Nb (19.8 mg/kg), Ta (3.6 mg/kg), Zr (71.0 mg/kg) and Li (32.3 mg/kg), occur at concentrations higher than those averages for world hard coals, making the Weibei coals potential sources of these critical elements. Several factors, terrigenous material, seawater invasion, and hydrothermal fluids are responsible for these mineralogical and geochemical characteristics. The L-type rare earth elements and yttrium (REE-Y) enrichment in the roofs and partings, Al2O3-TiO2 and Zr/TiO2-Nb/Y plots, and negative Eu and weak negative Ce anomalies in the Weibei coals indicate a felsic-intermediate dominated sediment provenance primarily derived from the Qilian-Qinling Oldland on the South. Marine bioclastic limestone, negative Ce and positive Y anomalies in coals imply the influence of seawater on the Weibei coals. Last but not least, the cleat-infilling and/or fracture-infilling calcite, pyrite, barite, and tobelite as well as the positive Eu and Gd anomalies, H-type, and M-type REE-Y enrichment patterns suggest the influence of hydrothermal fluids, which lead to re-distribution of some critical elements from roof and parting to the underlying coal seam. [ABSTRACT FROM AUTHOR]