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In engineering applications, the accuracy of on-load tap changer (OLTC) mechanical fault identification methods based on vibration signals is constrained by the quantity and quality of the samples. Therefore, a novel small-sample-size OLTC mechanical fault identification method incorporating short-time Fourier transform (STFT), synchrosqueezed wavelet transform (SWT), a dual-stream convolutional neural network (DSCNN), and support vector machine (SVM) is proposed. Firstly, the one-dimensional time-series vibration signals are transformed using STFT and SWT to obtain time–frequency graphs. STFT time–frequency graphs capture the global features of the OLTC vibration signals, while SWT time–frequency graphs capture the local features of the OLTC vibration signals. Secondly, these time–frequency graphs are input into the CNN to extract key features. In the fusion layer, the feature vectors from the STFT and SWT graphs are combined to form a fusion vector that encompasses both global and local time–frequency features. Finally, the softmax classifier of the traditional CNN is replaced with an SVM classifier, and the fusion vector is input into this classifier. Compared to the traditional fault identification methods, the proposed method demonstrates higher identification accuracy and stronger generalization ability under the conditions of small sample sizes and noise interference.

The On-Load Tap Changer (OLTC) is the only movable mechanical component in a converter transformer. To ensure the reliable operation of the OLTC and to promptly detect mechanical faults in OLTCs to prevent them from developing into electrical faults, this paper proposes a fault diagnosis method for OLTCs based on a combination of Particle Swarm Optimization (PSO) algorithm and Least Squares Support Vector Machine (LSSVM) with multi-feature fusion. Firstly, a multi-feature extraction method based on time/frequency domain statistics, synchrosqueezed wavelet transform, singular value decomposition, and multi-scale modal decomposition is proposed. Meanwhile, the random forest algorithm is used to screen features to eliminate the influence of redundant features on the accuracy of fault diagnosis. Secondly, the PSO algorithm is introduced to optimize the hyperparameters of LSSVM to obtain optimal parameters, thereby constructing an optimal LSSVM fault diagnosis model. Finally, different types of feature combinations are utilized for fault diagnosis, and the impact of these feature combinations on the fault diagnosis results is compared. Experimental results indicate that features of different types can complement each other, making the OLTC state information carried by multi-dimensional features more comprehensive, which helps to improve the accuracy of fault diagnosis. Compared with four traditional fault diagnosis methods, the proposed method performs better in fault diagnosis accuracy, achieving the highest accuracy of 98.58%, which can help to detect mechanical faults in the OLTC early and reduce the system’s downtime.

The pumped storage unit has good adjustment characteristics of a fast power response and convenient start and stop, which provides support for the safe and stable operation of the power system. To this end, this paper proposes a fractional order PID (FOPID) optimization control method for the regional load frequency of pumped-storage power plants. Specifically, based on IEEE standards, this paper established a single-region model of pumped storage. Then, a fractional order PID (FOPID) controller was designed, and the parameters of the controller were optimized via using the chaos particle swarm optimization (CPSO) algorithm. The effectiveness of the proposed method is verified by example simulation in the two-zone model of the pumped storage based on IEEE standards. The results of the example show that the proposed method exhibits stronger robustness and stability in the regional load frequency control.

Electrical energy substitution is an important way to achieve the optimization of the energy consumption structure as well as to alleviate environmental problems, and it is also an important source of benefits of the integrated energy system. However, there are few works that study the effects of electrical energy substitution on the construction of the integrated energy system (IES) and electrical energy substitution work without incentives carried out in the IES. To this end, this paper proposed a G1 method with constructing consistency matrix to determine the evaluation index weights for the IES with electrical energy substitution. Specifically, we firstly construct the evaluation index system for the IES including electrical energy substitution indicators, low-carbon indicators, technical indicators and economic indicators as well as their secondary indicators. Then, a tri-level evaluation index system of target-criteria-indicator benefits is established based on pertinent standards and norms, taking the practical operability into account. Finally, a G1-method-constructed consistency judgment matrix is proposed. Compared with the G1 method, it is simple and practical, and the weight calculation results are more in line with the reality, which effectively solves the consistency problem of the judgment matrix. The rationality and feasibility of the proposed weight calculation method are verified by the calculation and analysis of an example.

The interface of perovskite solar cells (PSCs) determines their power conversion efficiency (PCE). Here, the buried bottom surface of a perovskite film is efficiently passivated by using MoS2 quantum dots. The perovskite films prepared on top of MoS2-assisted substrates show enhanced crystallinity, as evidenced by improved photoluminescence and a prolonged emission lifetime. MoS2 quantum dots with a large bandgap of 2.68 eV not only facilitate hole collection but also prevent the photogenerated electrons from flowing to the hole transport layer. Overall promotion leads to decreased trap density and an enhanced built-in electric field, thus increasing the device PCE from 17.87% to 19.95%.

Against a background of the energy internet and low-carbon electricity, regional integrated energy system (RIES) has become a key way to achieve sustainable energy development, leading to reduced operating costs and system carbon emissions, and improved system operating efficiency. This paper puts forward a low-carbon economic dispatching optimization method for RIES with a heating network and power-to-gas (P2G). First, the heating network model and the mathematical model of P2G were constructed. Second, the carbon trading mechanism was introduced, the objective function being: to minimize the sum of the system operating cost and carbon trading cost; and ensure that the balance of cooling, heating, electric power, and the operating constraints—of RIES and the heating network—were comprehensively considered. Finally, the CPLEX optimization software simulation was used. The results show that the proposed method can take into account both low-carbon and economic factors, and can provide a reference for RIES low-carbon economic dispatch.

In this study, lychee (Litchi chinensis Sonn.) pericarp powder was added to chitosan (CHS) matrix to develop active packaging films, and their structure, physicochemical, antibacterial, antioxidant, and functional properties were investigated. FT-IR results showed that intermolecular hydrogen bonds were formed between CHS and polyphenols in lychee pericarp powder (LPP), and the intermolecular interaction interfered with the assembly of CHS into semi-crystal structure, which reduced the crystallinity of CHS film. Incorporation of LPP significantly reduced water vapor permeability, water solubility, swelling degree, and elongation at break of CHS film (p < 0.05). However, UV-visible light barrier, tensile strength, and antibacterial and antioxidant properties of CHS films were increased by LPP incorporation. CHS-LPP film remarkably lowered the weight loss, firmness, titratable acidity, and total soluble solids of fresh-cut apple after five days storage. CHS-LPP film packaging effectively inhibited the browning of fresh-cut apple and the reduction of polyphenol content in apple juice caused by polyphenol oxidase (PPO)-mediated oxidation during storage. Therefore, CHS-LPP films have great potential as food packaging material to ensure the quality and extend the shelf life of food products.

In this paper, a method to increase the output power of a button zinc–air battery by applying acoustofluidics induced by ultrasonic excitation to the battery is proposed and demonstrated. In the structural design of the device, a flat piezoelectric ring was bonded onto the top of the outer surface of the cathode shell to excite an ultrasonic field in the battery. The maximum output power of the zinc–air battery increased by 46.8% when the vibration velocity and working frequency were 52.8 mm/s (the corresponding vibration amplitude was 277 nm) and 161.2 kHz and the rating capacity increased by about 20% with the assistance of the acoustofluidic field induced by ultrasonic excitation. Further analyses indicated that the discharge performance improvement can be attributed to the acoustic microstreaming vortices and the decrease of the viscosity coefficient in the electrolyte solution, which were both caused by ultrasonic excitation of the piezoelectric ring.

Multiple reflection has been proven to be an effective method to enhance the gas detection sensitivity of Raman spectroscopy, while Raman gas probes based on the multiple reflection principle have been rarely reported on. In this paper, a multi-reflection, cavity enhanced Raman spectroscopy (CERS) probe was developed and used for in situ multi-component gas detection. Owing to signal transmission through optical fibers and the miniaturization of multi-reflection cavity, the CERS probe exhibited the advantages of in situ detection and higher detection sensitivity. Compared with the conventional, backscattering Raman layout, the CERS probe showed a better performance for the detection of weak signals with a relatively lower background. According to the 3σ criteria, the detection limits of this CERS probe for methane, hydrogen, carbon dioxide and water vapor are calculated to be 44.5 ppm, 192.9 ppm, 317.5 ppm and 0.67%, respectively. The results presented the development of this CERS probe as having great potential to provide a new method for industrial, multi-component online gas detection.

A newly developed integrated fluorescence-Raman spectral system (λex = 532 nm) for detecting Chlorophyll-a (chl-a), Chromophoric Dissolved Organic Matter (CDOM), carotenoids and SO42− in situ was used to successfully investigate the diurnal variability of all above. Simultaneously using the integration of fluorescence spectroscopy and Raman spectroscopy techniques provided comprehensive marine information due to the complementarity between the different excitation mechanisms and different selection rules. The investigation took place in offshore seawater of the Yellow Sea (36°05′40′′ N, 120°31′32′′ E) in October 2014. To detect chl-a, CDOM, carotenoids and SO42−, the fluorescence-Raman spectral system was deployed. It was found that troughs of chl-a and CDOM fluorescence signal intensity were observed during high tides, while the signal intensity showed high values with larger fluctuations during ebb-tide. Chl-a and carotenoids were influenced by solar radiation within a day cycle by different detection techniques, as well as displaying similar and synchronous tendency. CDOM fluorescence cause interference to the measurement of SO42−. To avoid such interference, the backup Raman spectroscopy system with λex = 785 nm was employed to detect SO42− concentration on the following day. The results demonstrated that the fluorescence-Raman spectral system has great potential in detection of chl-a, carotenoids, CDOM and SO42− in the ocean.