Accurate wind farm cluster power prediction (WFCPP) is of vital significance for new powersystems with large-scale wind power integration. The current WFCPP modeling method ignores the important role of wind directio...
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As the core part of metal oxide arresters, ZnO varistor plays an important part in suppressing the overvoltage of powersystems. With the development of UHV technology, the residual voltage and energy capacity of ZnO ...
As the core part of metal oxide arresters, ZnO varistor plays an important part in suppressing the overvoltage of powersystems. With the development of UHV technology, the residual voltage and energy capacity of ZnO varistors have put forward higher requirements. The research is carried out from the perspective of material calculation, studied the correlation mechanism between micro-structure parameters and various macroscopic electrical characteristics of ZnO varistor based on Voronoi network. And the microstructure parameters such as grain size and size inhomogeneity were calculated and studied. The study simplified the optimization problem with multiple variates and objectives, into the one with two categories of variates and two categories of objectives. And then proposed specific strategies. The research provides important theoretical basis for improving the performance of ZnO varistors, and witch is of great significance for the design and manufacture of high-performance lightning arresters.
Modular multilevel converter based high voltage direct current (MMC-HVDC) transmission technology has been widely applied in powersystems, such as AC systems interconnection and renewable energy access, due to its su...
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Accurate assessment of the powergeneration capacity of the wind farm is the key basis for incorporating it into power system scheduling and other optimizing operation activities. Traditional evaluation methods, such ...
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Silicone rubber (SIR) has been widely used in the insulation of cable accessories due to its excellent performance. In this paper, pure SIR and nano $\boldsymbol{\text{Al}_2 \mathrm{O}_3 / \text{SIR}}$ composites are ...
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ISBN:
(数字)9781665407502
ISBN:
(纸本)9781665407519
Silicone rubber (SIR) has been widely used in the insulation of cable accessories due to its excellent performance. In this paper, pure SIR and nano $\boldsymbol{\text{Al}_2 \mathrm{O}_3 / \text{SIR}}$ composites are thermally aged for 0–80 days at $\boldsymbol{200^{\circ} \mathrm{C}}$ . The effects of long-term thermal aging on the space charge transport are analyzed. The results show that with the increase of thermal aging time, the accumulation of heteropolar charge of pure SIR and nano $\boldsymbol{\text{Al}_{2}\mathrm{O}_{3}/\text{SIR}}$ composites gradually decreases and changes to the accumulation of homopolar charge. Compared with pure SIR, the space charge accumulation of $\boldsymbol{\text{Al}_{2}\mathrm{O}_{3}/\text{SIR}}$ composites decreases significantly and changes little with the increase of thermal aging time. It is believed that when doped nano $\boldsymbol{\text{Al}_{2}\mathrm{O}_{3}}$ in SIR, the increase of carrier mobility and the introduction of metal oxides reacting with fallen free radicals to form stable compounds both lead to less space charge accumulation of $\boldsymbol{\text{Al}_{2}\mathrm{O}_{3}/\text{SIR}}$ composites.
Addressing the weak generalization capability and suboptimal prediction performance of single mechanistic and data-driven models, this paper proposes a transformer fault detection method based on the fusion of mechani...
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ISBN:
(数字)9798350363609
ISBN:
(纸本)9798350363616
Addressing the weak generalization capability and suboptimal prediction performance of single mechanistic and data-driven models, this paper proposes a transformer fault detection method based on the fusion of mechanism and data models. Firstly, vibration and current data are collected on-site to train the SVM vibration model and the Adaboost current model. Secondly, current simulation data is obtained using laboratorysimulation software. This simulation data, combined with the current data collected under the same conditions on-site, is used as input to train the GBDT error compensation model. Finally, these three models are used as inputs to the GRNN, completing the overall model design. This fusion of mechanistic and data-driven models not only addresses the parameter mismatch issue of the mechanistic model under complex working conditions but also deeply mines time-series data. Experimental results show that The mean squared error of the fusion model is 0.002 lower than that of the data model, and the coefficient of determination is improved by 5.07% compared to the mechanistic model, enhancing the overall predictive accuracy of the model.
With wide application of power electronic equipment in power system, voltage stability and power supply reliability need to be improved. In this paper, voltage sag caused by AC port load increase and the influencing f...
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In response to the difficulty in obtaining combustion information within coal-fired boiler furnaces, a method is proposed in this study to improve the reduced-order model using clustering segmentation. This approach a...
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This paper focuses on optimal sizing of photovoltaic (PV) and battery energy storage system (BESS) of special-use charging station for electric taxi cabs. Aiming to minimize annual equivalent cost of the charging stat...
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The wind farm has only one NWP data point, which cannot accurately reflect the wind resources inside the wind farm. To solve the problem of a poor match between short-term wind power prediction numerical weather forec...
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The wind farm has only one NWP data point, which cannot accurately reflect the wind resources inside the wind farm. To solve the problem of a poor match between short-term wind power prediction numerical weather forecast and wind farm measured weather. Put forward a kind of based on clustering and temporal characteristics of the modified liters of scale wind power prediction method, first of all, using EOF orthogonal decomposition method to extract the features of each fan, using hierarchical analysis method of the characteristics of the data matrix clustering, and then, each cluster sample selected representative of a fan, using the error transfer characteristic of the NWP data sequence is modified. Finally, The CNN prediction model is used for power prediction, and the weight is determined according to the cluster sample size. A wind farm in northern Hebei, China, is used to verify the effectiveness of the proposed method.
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