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optimization methodology of thermal energy storage systems for domestic water heating applications with different configurations

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JOURNAL OF ENERGY STORAGE 2022年 50卷

作者： Khoury, S. Maatouk, C. El Khoury, K. Khatounian, F. St Joseph Univ Beirut Fac Engn ESIB BP 1514 Riad El Solh Beirut 11072050 Lebanon Lebanese Univ Fac Engn POB 657314 Badaro Beirut Lebanon

This paper develops an optimization methodology for the Thermal Energy Storage (TES) tank embedded with Phase Change Materials (PCMs) for domestic water heating applications with respect to the design parameter constraints and tank size. It presents the optimum design conditions for two different TES configurations considering different control strategies for the conventional cascaded system and the multiple entry independent PCM modules. The optimum configurations are determined using adaptive simulated annealing algorithm aimed to enhance the energy content and compare the systems outputs, namely the available energy and the heat transfer fluid outlet temperature at the optimum conditions for the two systems. The present study is conducted during a complete melting and solidification processes. It simultaneously validates the effectiveness of the multiple entry independent PCM modules in satisfying the low and high user requirements of domestic hot water and highlights the reduction in the electric power consumption throughout the year compared to the conventional TES system.

关键词： Phase change material Control strategy optimization algorithm Energy Temperature

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Simulation optimization framework for dynamic probabilistic safety assessment

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2022年 220卷

作者： Park, Jong Woo Lee, Seung Jun UNIST Dept Nucl Engn 50 UNIST Gil Ulsan 44919 South Korea

Probabilistic safety assessment (PSA) based on event trees and fault trees has been widely used in the risk assessment of nuclear power plants. A static approach by nature, PSA has limitations to consider dynamic scenarios with time-dependent sequences and interactions. In contrast to static-based PSA, dynamic PSA has been introduced as a complementary methodology that considers dynamic scenarios between the system and human operations by interfacing physical simulation with thermal-hydraulic models for risk assessment. However, the various research on dynamic PSA has a common challenge in that the number of dynamic scenarios to be simulated increases impractically. An approach is therefore necessary to manage the number of simulations for performing dynamic PSA efficiently. The objective of this paper is to propose a simulation optimization framework using an optimization algorithm to reduce, as much as reasonably achievable, the large number of dynamic scenarios to be evaluated. The optimization algorithm is proposed to optimize the large numbers of generated dynamic scenarios while maintaining accurate risk quantification in the performance of dynamic PSA. To demonstrate the application of the proposed framework to dynamic PSA, two case studies were conducted considering loss of coolant accidents.

关键词： Dynamic PSA Simulation optimization framework optimization algorithm TH simulation Loss of coolant accident

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A Unified Electrothermal Behavior Modeling Method for Both SiC MOSFET and GaN HEMT

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2021年第10期68卷 9366-9375页

作者： Long, Xiao Jun, Zhao Zhang, Botao Chen, Dongdong Liang, Wu Minnan Univ Sci & Technol Sch Elect & Elect Engn Quanzhou 362700 Peoples R China Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110819 Peoples R China Zhejiang Univ Coll Elect Engn Hangzhou 310027 Peoples R China Wuhan Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430065 Peoples R China

This article has presented a unified electrothermal behavior modeling method for both silicon carbide (SiC) metal oxide semiconductor field effect transistor (mosfet) and gallium nitride (GaN) high electron mobility transistor (HEMT). The electrothemal behavior of these two kind of devices in both the first and the third quadrant is accurately modeled with serval compact equations. A modeling data and optimization algorithm-based parameter extraction method have been proposed to replace the previous time consuming and labor intensive one. The proposed parameter fitting algorithm is a genetic algorithm and Levenberg-Marquardt combined optimization algorithm possessing the advantages of global optimization and fast convergence speed, and modeling data can come from both datasheets and measurement. The correctness and accuracy of the proposed modeling method has been verified by simulation and experiment result. Meanwhile, it has been proved that the proposed modeling method is applicable to several commercially available SiC mosfets and GaN HEMTs.

关键词： Mathematical model Semiconductor device modeling MOSFET Silicon carbide Gallium nitride HEMTs Logic gates Electrothermal model gallium nitride (GaN) high electron mobility transistor (HEMT) optimization algorithm parameter extraction silicon carbide metal oxide semiconductor field effect transistor (MOSFET)

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The development trend of China's natural gas consumption: A forecasting viewpoint based on grey forecasting model

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ENERGY REPORTS 2021年 7卷 4308-4324页

作者： Zhang, Jun Qin, Yanping Duo, Huaqiong Inner Mongolia Agr Univ Coll Sci Hohhot 010018 Peoples R China Inner Mongolia Agr Univ Coll Mat Sci & Art Design Hohhot 010018 Peoples R China

In the context of global emission reduction, as a type of clean and eco-friendly energy, natural gas has attracted wide attention. Accurate prediction of natural gas consumption can provide reference for relevant departments to formulate the corresponding development plans and strategies. At present, there are many forecasting tools for processing and analysing natural gas consumption, but most of them have the disadvantages of complex modelling or low precision. In order to solve this problem, inspired by the polynomial regression prediction model and the discrete grey prediction model, a novel polynomial discrete grey prediction model with fractional order accumulation (abbreviated as FPDGM(1,1) model) is established in this paper. In order to find the optimal parameters of the FPDGM(1,1) model, three most popular intelligent algorithms are used to solve the parameters of the model, and then the optimal parameters from the three intelligent algorithms are selected in this paper. In addition, the advantages of the FPDGM(1,1) model over other four forecasting models are confirmed through two parts in this paper. First, the natural gas consumptions of four municipalities in China are used as cases to verify the effectiveness of the FPDGM(1,1) model in this paper. Subsequently, the FPDGM(1,1) model and several kinds of frequently used forecasting models are applied to analyse and predict China's natural gas consumption, and the FPDGM(1,1) model is used to predict China's natural gas consumption in the next 5 years. The results of these two parts indicate that the FPDGM(1,1) model shows the best predictive performance in all cases. Lastly, based on the predicted results of the FPDGM(1,1) model, some reasonable suggestions are put forward for China's natural gas development plan. (C) 2021 Published by Elsevier Ltd.

关键词： Natural gas consumption Polynomial regression prediction model Discrete grey prediction model optimization algorithm

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Adaptive mutant particle swarm optimization based precise cargo airdrop of unmanned aerial vehicles

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APPLIED SOFT COMPUTING 2022年 130卷

作者： Zhang, An Xu, Han Bi, Wenhao Xu, Shuangfei Northwestern Polytech Univ Sch Aeronaut Xian 710072 Peoples R China

Emerging unmanned system technologies and smart logistics have motivated logistics enterprises to use unmanned aerial vehicles (UAVs) for last-mile cargo delivery through the air so as to benefit from its flexibility and low cost. It is useful to deliver cargoes by airdrops from fixed-wing UAVs. However, wind and parameter errors of the UAV could make the cargo deviate from the desired landing point. To improve the accuracy of airdrop methods, this paper presents the Continuously Computed Release Point under conditions of strong wind (SW-CCRP) airdrop strategy to transport the cargo to a given position by a fixed-wing UAV. In this strategy, a set of differential equations are used to model the cargo motion and wind perturbations are considered. Based on the established motion model and the kinematic relationships between the cargo and the target position, the expected release point can be accurately predicted in real time. In order to satisfy the precision requirement, the precision assignment is studied to determine the permissible parameter error ranges. In view of that the conventional precision assignment methods are difficult to be applied in the airdrop system because of its complexity and strong nonlinearity, an adaptive mutant particle swarm optimization (AMPSO) algorithm is proposed to solve this problem, in which the adaptive inertia weight can balance the global and local search. In addition, the mutation factor of the AMPSO is able to avoid premature convergence and stagnation. Finally, two specific test scenarios are designed to validate the effectiveness of the proposed approaches.

关键词： Smart logistics Fixed-wing UAV Precision airdrop Adaptive mutant particle swarm optimization algorithm Precision assignment

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An advanced optimization strategy for enhancing the performance of a hybrid pressure-swing distillation process in effective binary-azeotrope separation

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SEPARATION AND PURIFICATION TECHNOLOGY 2022年 282卷

作者： Miao, Guang Zhuo, Kaisheng Li, Guoqing Xiao, Jing South China Univ Technol Key Lab Enhanced Heat Transfer & Energy Conservat Minist Educ Guangzhou 510640 Peoples R China South China Univ Technol Sch Chem & Chem Engn Guangzhou 510640 Peoples R China South China Univ Technol Sch Chem & Chem Engn Guangdong Prov Key Lab Green Chem Prod Technol Guangzhou 510640 Peoples R China

The separation of binary azeotropes with low cost and energy consumption is important and challenging for the production of chemicals. A hybrid heat-integrated pressure-swing distillation process (HHIPSD) with heat pump was proposed for the separation of both maximum-and minimum-boiling azeotropes in this work. Compared to the conventional fully heat-integrated pressure-swing distillation process (FHIPSD), the HHIPSD process showed lower total annual cost and higher thermodynamic efficiency in the separation of seven minimum-boiling azeotropes of benzene-ethanol, methanol-acetone, methanol-ethyl acetate (EA), ethanol-EA, acetonitrileethanol, isobutanol (IBA)/isobutyl acetate (IBAc) and diisopropyl ether (DIPE)-isopropyl alcohol (IPA), and two maximum-boiling azeotropes of water-ethylenediamine (EDA) and acetone-chloroform. For the best performance of HHIPSD process, robustness and algorithm optimization were studied in this paper. Scenario analysis method was proven to greatly enhance the convergence of HHIPSD models. The improved genetic algorithm (GA) was modified by particle-swarm optimization and pattern search method and validated by 13 benchmark functions. Meanwhile, different constraint handling methods were studied to ensure the better performance of the improve GA method. With the improvement of model robustness and optimization algorithm, the HHIPSD process achieved 21.6 % and 4.2 % decrease of TAC for water-EDA and methanol-acetone separation, respectively, compared to FHIPSD process. The proposed HHIPSD process together with the optimization strategy suggests the pressure-swing distillation technology can be highly effective in azeotrope separation.

关键词： Pressure-swing distillation Binary azeotropes Heat integration Robustness optimization optimization algorithm

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Management of Energy Storage in Transactive Energy Communities 5

Management of Energy Storage in Transactive Energy Communiti...

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5th International Conference on Smart Energy Systems and Technologies (SEST)

作者： Soares, Ana Goncalves, Goncalo Moura, Pedro Univ Coimbra Elect & Comp Engn Dept INESC Coimbra Coimbra Portugal Univ Coimbra Elect & Comp Engn Dept Coimbra Portugal Univ Coimbra ISR Coimbra Elect & Comp Engn Dept Coimbra Portugal

ISBN: (数字)9781665405577

ISBN: (纸本)9781665405577

The energy sector has been evolving towards a more sustainable model in which renewables, energy storage systems and energy communities play an important role in a successful energy transition. In the near future, a large share of small-scale renewable distributed generation is expected to be deployed in buildings, leading to a mismatch between generation and demand which needs to be addressed with energy flexibility options. In such a context, the use of energy management systems endowed with adequate control algorithms will be crucial for leveraging the spatio-temporal flexibility of controllable energy resources. This paper proposes a framework for the optimization of energy storage in a transactive energy community on a Portuguese University Campus. The used methodology ensures economic benefits with the management of dedicated storage systems coupled with renewable generation systems. The considered constraints include mechanisms to encourage renewable generation surplus sharing within the community and that export and import power flows between the building and the community are limited to the net energy demand in the building, maximum (dis)charging power of the storage systems, the minimum and maximum state of charge, among others. Results showed that the proposed framework achieves an increase in renewable self-consumption at building and community levels, as well as a reduction in electricity costs.

关键词： Battery storage system community storage energy communities optimization algorithm transactive energy

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An algorithm to optimize the optical sensor design for tip clearance and tip timing measurements 7

An algorithm to optimize the optical sensor design for tip c...

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Conference on Optical Sensing and Detection VII Part of SPIE Photonics Europe Conference

作者： Zubia, Gorka Amorebieta, Josu Zubia, Joseba Durana, Gaizka Univ Basque Country Dept Commun Engn Plaza Ingeniero Torres Quevedo 1 E-48013 Bilbao Basque Country Spain

ISBN: (纸本)9781510651555;9781510651548

In this work, an algorithm for the optimization of the design of an optical fiber bundle displacement sensor for Tip Clearance and Tip Timing measurements is presented. The former is based on the gaussian beam mathematical approach, and implements a fiber arrangement comprised of a transmitting single-mode fiber and two concentric rings of receiving multimode fibers. The software includes a graphical user interface that allows modifying relevant geometrical parameters of the sensor and fiber characteristics, and enables monitoring in real time the effects of such modifications. Results indicate that in order to achieve the most sensitive design with the largest operating range, the key parameters are the gain configuration, the distance between the receiving fiber rings and the radii of receiving fibers, and that the best fitting sensor configuration is a tradeoff among the aforementioned characteristics as it is heavily dependent on the measurement constraints. The results obtained by the simulation tool were validated in good agreement with the calibration curve of the manufactured optical fiber bundle displacement sensor in a scaled rotor.

关键词： optical fiber sensor optimization algorithm tip clearance tip timing aircraft turbines displacement measurement

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Symmetric Cryptography With a Chaotic Map and a Multilayer Machine Learning Network for Physiological Signal Infosecurity: Case Study in Electrocardiogram

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IEEE ACCESS 2021年 9卷 26451-26467页

作者： Lin, Chia-Hung Wu, Jian-Xing Chen, Pi-Yun Li, Chien-Ming Pai, Neng-Sheng Kuo, Chao-Lin Natl Chin Yi Univ Technol Dept Elect Engn Taichung 41170 Taiwan Chi Mei Med Ctr Dept Med Div Infect Dis Tainan 41710 Taiwan Natl Kaohsiung Univ Sci & Technol Dept Maritime Informat & Technol Kaohsiung 80543 Taiwan

Digital physiological signals in telecare medicine information systems have been widely applied in remote medical applications, such as telecare, tele-examination, and telediagnosis, via computer networking transmission or wireless communication. However, these medical records need to ensure authorization demands in the channel model for human body communication and remote medical servers and enhance the confidentiality, recoverability, and availability of transmission data. Hence, this study proposes a symmetric cryptography scheme with a chaotic map and a multilayer machine learning network (MMLN) to achieve physiological signal infosecurity. A chaotic pseudorandom number generator within specific control parameters can dynamically produce unordered sequence numbers to set the secret keys for a regular secret key update, thereby improving the security of private cipher codes. The chaotic map is quickly iterated to produce a pseudorandom key stream for real-time applications, and the private cipher codes are selected using the initial and specific control parameters at the data emitter and receiver ends. A general regression neural network is used to map the high-dimensional input-output pair of cipher codes for substitution and permutation processes. Its adaptive MMLN with an optimization algorithm can rapidly train the random cipher code protocol to achieve an encryptor and a decryptor for a regular encrypted communication. Using the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) Arrhythmia Database, 100 electrocardiogram fragments are used to verify the proposed model, and the peak signal-to-noise ratio (PSNR) as a quantitative quality metric is used to evaluate the visual quality after encryption and decryption processes for further diagnosis applications. Experimental results show that the proposed scheme has a higher mean PSNR (35.26 +/- 3.77 dB) and shorter mean executing time (0.16 +/- 0.01 s) compared with traditional cryptography pro

关键词： Electrocardiography Chaotic communication Ciphers Protocols Measurement Encryption Wireless communication Symmetric cryptography chaotic map general regression neural network optimization algorithm peak signal-to-noise ratio

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Data-Driven Modeling Approach for Mistuned Cyclic Structures

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AIAA JOURNAL 2021年第7期59卷 2684-2696页

作者： Kelly, Sean T. Lupini, Andrea Epureanu, Bogdan, I Univ Michigan Dept Mech Engn Ann Arbor MI 48109 USA

A data-driven approach to predict dynamic responses of mistuned cyclic dynamic structures is presented. Nominally cyclic structures such as turbomachinery bladed disks, or blisks, contain deviations from perfect symmetry, called mistuning, which can significantly increase the forced response of the structure subject to periodic excitations. The ability to accurately model the response is crucial for understanding a structure's dynamics during operation, and thus many reduced-order models have been developed. Data-driven approaches, however, are largely unexplored for predicting physical responses of cyclic structures, and are desirable due to their ability to leverage both computational and experimental data. In this paper, two feed-forward neural networks (FFNNs) are trained using physical responses and parameters from an individual sector of the cyclic structure. The desired physical responses of all sectors are predicted via a cyclic coupling procedure. By only using sector-level data, the number of simulations and/or experiments required to generate training data is substantially reduced, and the approach is not restricted to a specific projection basis unlike previous physics-based methods. A lumped mass model (LMM) of a blisk with stiffness mistuning is used to generate computational surrogate data for training and validation. Both FFNNs achieve high prediction accuracy on both training data and unseen test data. For a test case with an unseen mistuning pattern, this approach shows strong agreement with known actual responses. For this test case, prediction errors in the LMM blade tip amplitudes across all sectors are less than 2%, and the amplification factor error is less than 0.2%.

关键词： Convolutional Neural Network Structural Dynamics Turbomachinery Bladed Disks Stiffness Matrices optimization algorithm Frequency Domain Boundary Value Problems Structural Health Monitoring Graphics Processing Unit Monte Carlo Simulation

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