Axial-flux permanent magnet synchronous machine (AFPMSM), with the advantages of high power density and compact structure, are suitable for large-capacity flywheel energy storage system (FESS). FESS is often used to i...
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ISBN:
(纸本)9798350348958;9798350348965
Axial-flux permanent magnet synchronous machine (AFPMSM), with the advantages of high power density and compact structure, are suitable for large-capacity flywheel energy storage system (FESS). FESS is often used to improve efficiency as main development direction, while the traditional AFPMSM has the drawbacks of high loss and large cogging torque, which restricts the application of FESS. Therefore, the AFPMSM using soft magnetic composites (SMC) is proposed in this paper, then the parameters of machine are investigated, and finally a new optimizationstrategy combining back-propagation artificial neural network (BP-ANN) based on genetic algorithm (GA) and multi-objective particle swarm optimization (PSO) search algorithm is used for optimization design.
Power quality (PQ) problem and insufficient supply capacity have been challenges for long-distance traction power supply system (LD-TPSS). LD-TPSS based on high-voltage traction cables can enhance the power supply cap...
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ISBN:
(纸本)9798350382570;9798350382563
Power quality (PQ) problem and insufficient supply capacity have been challenges for long-distance traction power supply system (LD-TPSS). LD-TPSS based on high-voltage traction cables can enhance the power supply capacity. However, it triggers the end supply voltage overrun easily. In this paper, a new multi-voltage (MV-) TPSS is proposed, it can ensure the power supply capacity, regulate the voltage and realize the PQ management. Then, a comprehensive compensation strategy with a hierarchical structure is proposed. In the upper layer, voltage and PQ are managed in two stages to calculate the compensation power demand. The firststage, system voltage reactive power flow optimization is optimized. The second stage, unified management of PQ such as VU and power factor (PF) is completed. The control of each compensation device is realized by the lower controller. Finally, a detailed case comparison demonstrates the correctness and effectiveness of the system topology and strategy.
Real-time optimizationstrategies aim to improve the operating performance of a process using a model of its input-output behaviour. This is challenging when the true system characteristics are not fully known and the...
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ISBN:
(纸本)9781665493130
Real-time optimizationstrategies aim to improve the operating performance of a process using a model of its input-output behaviour. This is challenging when the true system characteristics are not fully known and there are safe operating limits that must be respected. In this work, we evaluate the performance of an adaptive, real-time, exploration and optimization algorithm on a simulated refrigeration plant, and show how incorporating prior knowledge based on engineering principles can improve its performance, especially during the early stages of learning when there are few observed data. The results indicate that exceedances of the safe operating limit are avoided and the improved models still learn the true system characteristic, albeit more slowly than the standard models fitted without prior knowledge.
The proceedings contain 60 papers. The topics discussed include: battery management system for enhancing the performance and safety of lithium-ion batteries;optimal placement and sizing of distributed generation for p...
ISBN:
(纸本)9798350393569
The proceedings contain 60 papers. The topics discussed include: battery management system for enhancing the performance and safety of lithium-ion batteries;optimal placement and sizing of distributed generation for power factor improvement;sleep disorder analysis: unveiling the interplay between lifestyle health and sleep quality;turbulent Reynolds stresses prediction using stochastic gradient boosting regression;load flow analysis and optimization for solar PV integration in power systems;load flow analysis and optimization for smart grid integration in power systems;a novel method to predict chronic kidney disease using optimized deep learning algorithm;accurate classification of cervical cancer based on multi-layer perceptron hunger games search optimization technique;and design of receiver RF front end for mm-wave 5G applications.
In nearly decades, direct drive permanent magnet synchronous machines have garnered substantial interest within the realm of electric vehicles (EV s). This work deals with the design optimization and performance compa...
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Parasitic electromagnetic (EM) effects within passive components are a critical problem in EMI filter applications, especially when specific filter specifications must be met. In this study, a surrogate model-based op...
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ISBN:
(纸本)9798350348958;9798350348965
Parasitic electromagnetic (EM) effects within passive components are a critical problem in EMI filter applications, especially when specific filter specifications must be met. In this study, a surrogate model-based optimization methodology is proposed to determine the optimal internal geometry of a surface-mounted (SMT) ferrite bead to maximize the inductance of the device over a wide frequency range from 1 MHz to 1 GHz. Preliminary results show an improvement of the device behavior compared to the original design provided by the manufacturer over the entire frequency range of interest.
Nowadays, energy buildings have a huge impact in society regarding the active role in the management of energy consumption. Hence, building owners are required to avoid energy losses and improve energy efficiency as h...
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ISBN:
(纸本)9783031820724;9783031820731
Nowadays, energy buildings have a huge impact in society regarding the active role in the management of energy consumption. Hence, building owners are required to avoid energy losses and improve energy efficiency as high as possible. Therefore, it is required to plan an optimizationstrategy to buy and sell energy in the market ahead of time. To formulate this optimization plan, building owners require the work of specialists responsible for processing, training, forecasting, and evaluation tasks regarding the prediction of energy consumption data from a building for a specific target of time. Therefore, a multiagent-system is needed to allow the cooperation of various agents including the building owner, forecast provider, data structurer and error analysis. Moreover, forecasting algorithms such as artificial neural networks should be taken into consideration in order to process large quantities of energy consumption data during the training and forecasting phases.
In decomposition-based evolutionary multi-objective optimization algorithms (MOEA/Ds) with adaptive strategies for weight vectors, the vectors are updated periodically. Their updates' timing and frequency signific...
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The reliable operation of the Modular Multilevel Co-Phase Power Supply Device (MM-CPD), as a key component of the Co-Phase Traction Power Supply system (CTPSS), is of paramount importance. However, the access of photo...
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ISBN:
(纸本)9798350382570;9798350382563
The reliable operation of the Modular Multilevel Co-Phase Power Supply Device (MM-CPD), as a key component of the Co-Phase Traction Power Supply system (CTPSS), is of paramount importance. However, the access of photovoltaic (PV) and hybrid energy storage systems (HESS) can change the port current of the MM-CPD and affect its reliability. Therefore, firstly, a day-ahead optimization model of the CTPSS is developed to minimize the traction substation's daily operating cost, and the compensation current of each phase of the MM-CPD is determined. Secondly, the reliability calculation model for MM-CPD is established according to the physical failure mechanism and reliability prediction manual. Finally, the impact of PV and HESS access on the reliability of the MM-CPD is analyzed with actual traction load data as an example, and its best redundancy configurations are determined to maximize the reliability of the device.
In this paper, the thermal connection problem in the production scheduling of forging workshop is studied, and an optimization algorithm is proposed. First of all, we established a mathematical model of the production...
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ISBN:
(纸本)9798350388084;9798350388077
In this paper, the thermal connection problem in the production scheduling of forging workshop is studied, and an optimization algorithm is proposed. First of all, we established a mathematical model of the production scheduling of the forging workshop, taking into account the thermal connection between the processes, as well as practical factors such as resource constraints. Then, combined with the genetic algorithm and the tabu search algorithm, an optimization algorithm that meets the needs was designed, and the optimization method achieved the goal of improving equipment efficiency and reducing energy consumption through case verification. This study has certain theoretical guiding significance and practical application significance for optimizing the production scheduling and improving the production efficiency of the forging workshop.
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