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AbstractElectricity theft is a primary concern for utility providers, as it leads to substantial financial losses. To address the issue, a novel extreme gradient boosting (XGBoost)‐based model utilizing the consumers’ electricity consumption patterns for analysis is proposed for electricity theft detection (ETD). To remove the imbalance in the real‐world electricity consumption dataset and ensure an even distribution of theft and non‐theft data instances, six different artificially created theft attacks were used. Moreover, the utilization of the XGBoost algorithm for classification, especially to identify malicious instances of electricity theft, yielded commendable accuracy rates and a minimal occurrence of false positives. The proposed model identifies electricity theft specific to the regions, utilizing electricity consumption parameters, and other variables as input features. The authors’ model outperformed existing benchmarks like k‐neural networks, light gradient boost, random forest, support vector machine, decision tree, and AdaBoost. The simulation results using the false attacks for balancing the dataset have improved the proposed model's performance, achieving a precision, recall, and F1‐score of 96%, 95%, and 95%, respectively. The results of the detection rate and the false positive rate (FPR) of the proposed XGBoost‐based detection model have achieved 96% and 3%, respectively.

The effects of the nitrogen source and buffers used in butanol production with Clostridium beijerinckii TISTR 1461 from sweet sorghum stem juice (SSJ) containing 60 g/L of total sugar were first studied in this paper. Among the various nitrogen sources (dried spent yeast, urea, ammonium acetate, ammonium sulfate), urea was found to be the most suitable for butanol production. SSJ supplemented with urea (0.64 g/L) and cocktail buffers (KH2PO4, 0.5 g/L; K2HPO4, 0.5 g/L; ammonium acetate, 2.2 g/L) gave the highest butanol concentration (PB, 10.13 g/L). Then, the capability of immobilized C. beijerinckii TISTR 1461 cells for butanol fermentation was investigated. Two residual waste materials were examined as immobilized cell carriers. Bamboo chopstick pieces were more appropriate as carriers for cell immobilization than cigarette filter tips. The PB value of the immobilized cells on the bamboo chopstick pieces was ~13% higher than that on the cigarette filter tips. Using the response surface methodology (RSM), 1.9 cm bamboo chopstick pieces with a carrier loading of 1:32 (w/v) were the optimum conditions for cell immobilization for butanol production. Under these conditions, the PB value was 11.62 g/L. To improve the butanol production efficiency, a gas stripping system (GS) was connected to the fermenter. It was found that the PB (14.02 g/L) and butanol productivity (QB, 0.29 g/L·h) values improved by ~21% compared to butanol fermentation using no gas stripping.

The use of distributed energy systems (DES) can utilize local resources to achieve flexible and efficient energy production and supply. However, this aspect of pollutant emission reduction has not been sufficiently investigated in current related studies. On this basis, this study establishes a DES system that integrates a ground-source heat pump, a gas turbine, a photovoltaic device and an energy storage device. An Improved Zebra Optimization Algorithm (IZOA) is proposed for optimizing the capacity of DES devices and the energy supply ratio of the ground-source heat pump. Using the economic cost saving rate (ECSR), pollutant emission reduction rate (PERR) and energy saving rate (ESR) as the optimization objectives, the study builds a DES configuration optimization model. By analyzing the arithmetic example of a large hotel building, the study verifies the effectiveness of the IZOA algorithm in solving the DES configuration optimization problem. This study provides useful research ideas in promoting the development of distributed energy systems, environmental protection and energy conservation.

This study focuses on the investigation and comparison of combustion characteristic parameters and combustion performance indices between fast-growing trees and agricultural residues as biomass sources. The investigation is conducted through direct combustion in an air environment using a thermogravimetric analyzer (TGA). Additionally, partial least squares regression (PLSR)-based models were developed to assess combustion performance indices via near-infrared spectroscopy (NIRS), serving as a non-destructive alternative method. The results obtained through the TGA reveal that, specifically, fast-growing trees display higher average ignition temperature (227 °C) and burnout temperature (521 °C) in comparison to agricultural residues, which exhibit the values of 218 °C and 515 °C, respectively. Therefore, fast-growing trees are comparatively difficult to ignite, but sustain combustion over extended periods, yielding higher temperatures. However, despite fast-growing trees having a high ignition index (Di) and burnout index (Df), the comprehensive combustion performance (Si) and flammability index (Ci) of agricultural residue are higher, indicating the latter possess enhanced thermal and combustion reactivity, coupled with improved combustion stability. Five distinct PLSR-based models were developed using 115 biomass samples for both chip and ground forms, spanning the wavenumber range of 3595–12,489 cm−1. The optimal model was selected by evaluating the coefficients of determination in the prediction set (R2P), root mean square error of prediction (RMSEP), and RPD values. The results suggest that the proposed model for Df, obtained through GA-PLSR using the first derivative (D1), and Si, achieved through full-PLSR with MSC, both in ground biomass, is usable for most applications, including research. The model yielded, respectively, an R2P, RMSEP, and RPD, which are 0.8426, 0.4968 wt.% min⁻4, and 2.5; and 0.8808, 0.1566 wt.%2 min⁻2 °C⁻3, and 3.1. The remaining models (Di in chip and ground, Df, and Si in chip, and Ci in chip and ground biomass) are primarily applicable only for rough screening purposes. However, including more representative samples and exploring a more suitable machine learning algorithm are essential for updating the model to achieve a better nondestructive assessment of biomass combustion behavior.

In this paper, we investigate downlink cooperative multiple-input single-output wireless sensor networks with the nonorthogonal multiple access technique and simultaneous wireless information and power transfer over Nakagami-m fading. Specifically, the considered network includes a multiantenna sink node, an energy-limited relay cluster, a high-priority sensor node (SN) cluster, and a low-priority SN cluster. Prior to transmission, a transmit antenna, a relay, a high-priority SN, and a low-priority SN are selected. In this paper, we propose three antenna-relay-destination selection schemes, i.e., sink node-high-priority, sink node-relay, and sink node-low-priority. In each proposed scheme, we consider two relaying strategies, i.e., decode-and-forward and amplify-and-forward, and then, we derive the corresponding closed-form expressions of outage probability at the selected SNs. In addition, we introduce two algorithms: 1) the powersplitting ratio optimization algorithm and 2) the best antenna-relay-destination selection determination algorithm. Finally, we utilize the Monte Carlo simulations to verify our analytical results.

This paper introduces the pole ratio adjustment technique to improve the torque characteristics of the doubly salient permanent magnetic machine (DSPM). The electrical characteristics of the machine, namely the magnetic field distribution, flux linkage, back-electromotive force (EMF), and cogging torque, were obtained under open-circuit conditions. The electromagnetic torque and ripple torque were examined under the loaded condition. The simulations, based on the 2D-finite element method, show that the optimal pole ratio for the DSPM structure is with 18 stator teeth and 15 rotor poles. This optimal structure achieves a larger phase back-EMF than the conventional structure, as well as had a better magnetic flux path with a reasonable cogging torque. The on-load test also confirmes that the proposed optimal structure can produce a significantly higher electromagnetic torque than the conventional machine while maintaining a satisfactory torque ripple. Furthermore, an experimental prototype of the DSPM structure having 18/15 stator/rotor poles was fabricated and tested to verify the simulations. The experimental results were in good agreement with the simulations. The design technique and the fabricated prototype demonstrate the DSPM utilization for low-speed/high torque applications.

AbstractThe objective of this research is to study the preparation of dye sensitized solar cell from red sandal wood, mangosteen and lac, respectively. The samples is extracted by acetone and purified with dichloromethen. The results show that the efficiencies of red sandal wood, mangosteen and lac are 1.47%, 0.78% and 0.27% respectively. Short circuit current densities are 7.83mA/cm2, 2.65mA/cm2 and 1.09mA/cm2, respectively. Open circuit voltages are 0.39, 0.46 and 0.40, respectively.