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Optimal design and development of PV-wind-battery based nano-grid system: A field-on-laboratory demonstration

B. TUDU, K. K. MANDAL, N. CHAKRABORTY

《能源前沿（英文）》 2019年 第13卷 第2期   页码 269-283 doi: 10.1007/s11708-018-0573-z

摘要： The present paper has disseminated the design approach, project implementation, and economics of a nano-grid system. The deployment of the system is envisioned to acculturate the renewable technology into Indian society by field-on-laboratory demonstration (FOLD) and “bridge the gaps between research, development, and implementation.” The system consists of a solar photovoltaic (PV) (2.4 kWp), a wind turbine (3.2 kWp), and a battery bank (400 Ah). Initially, a prefeasibility study is conducted using the well-established HOMER (hybrid optimization model for electric renewable) software developed by the National Renewable Energy Laboratory (NREL), USA. The feasibility study indicates that the optimal capacity for the nano-grid system consists of a 2.16 kWp solar PV, a 3 kWp wind turbine, a 1.44 kW inverter, and a 24 kWh battery bank. The total net present cost (TNPC) and cost of energy (COE) of the system are US$20789.85 and US$0.673/kWh, respectively. However, the hybrid system consisting of a 2.4 kWp of solar PV, a 3.2 kWp of wind turbine, a 3 kVA of inverter, and a 400 Ah of battery bank has been installed due to unavailability of system components of desired values and to enhance the reliability of the system. The TNPC and COE of the system installed are found to be US$20073.63 and US$0.635/kWh, respectively and both costs are largely influenced by battery cost. Besides, this paper has illustrated the installation details of each component as well as of the system. Moreover, it has discussed the detailed cost breakup of the system. Furthermore, the performance of the system has been investigated and validated with the simulation results. It is observed that the power generated from the PV system is quite significant and is almost uniform over the year. Contrary to this, a trivial wind velocity prevails over the year apart from the month of April, May, and June, so does the power yield. This research demonstration provides a pathway for future planning of scaled-up hybrid energy systems or microgrid in this region of India or regions of similar topography.

关键词： photovoltaic (PV)     wind     battery     nano-grid     hybrid optimization model for electric renewable (HOMER)     field-on-lab demonstration (FOLD)    

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Fuel poverty and low carbon emissions: a comparative study of the feasibility of the hybrid renewable

《能源前沿（英文）》 2022年 第16卷 第2期   页码 336-356 doi: 10.1007/s11708-021-0748-x

摘要： Fuel poverty is most prevalent in North East England with 14.4% of fuel poor households in Newcastle upon Tyne. The aim of this paper was to identify a grid connected renewable energy system coupled with natural gas reciprocating combined heat and power unit, that is cost-effective and technically feasible with a potential to generate a profit from selling energy excess to the grid to help alleviate fuel poverty. The system was also aimed at low carbon emissions. Fourteen models were designed and optimized with the aid of the HOMER Pro software. Models were compared with respect to their economic, technical, and environmental performance. A solution was proposed where restrictions were placed on the size of renewable energy components. This configuration consists of 150 kW CHP, 300 kW PV cells, and 30 kW wind turbines. The renewable fraction is 5.10% and the system yields a carbon saving of 7.9% in comparison with conventional systems. The initial capital investment is $1.24 million which enables the system to have grid sales of 582689 kWh/a. A conservative calculation determined that 40% of the sales can be used to reduce the energy cost of fuel poor households by $706 per annum. This solution has the potential to eliminate fuel poverty at the site analyzed.

关键词： greenhouse gas control     low carbon target     grid connected     renewable fraction     fuel poverty     combined heat and power     HOMER Pro    

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State-of-art review of the optimization methods to design the configuration of hybrid renewable energy

Maurizio FACCIO, Mauro GAMBERI, Marco BORTOLINI, Mojtaba NEDAEI

《能源前沿（英文）》 2018年 第12卷 第4期   页码 591-622 doi: 10.1007/s11708-018-0567-x

摘要： The current research aims to present an inclusive review of latest research works performed with the aim of improving the efficiency of the hybrid renewable energy systems (HRESs) by employing diverse ranges of the optimization techniques, which aid the designers to achieve the minimum expected total cost, while satisfying the power demand and the reliability. For this purpose, a detailed analysis of the different classification drivers considering the design factors such as the optimization goals, utilized optimization methods, grid type as well as the investigated technology has been conducted. Initial results have indicated that of all optimization goals, load demand parameters including loss of power supply probability (LPSP) and loss of load probability (LLP), cost, sizing (configuration), energy production, and environmental emissions are the most frequent design variables which have been cited the most. Another result of this paper indicates that almost 70% of the research projects have been dedicated toward the optimization of the off-grid applications of the HRESs. Furthermore, it has been demonstrated that, integration of the PV, wind and battery is the most frequent configuration. In the next stage of the paper, a review concerning the sizing methods has also been carried out to outline the most common techniques which are used to configure the components of the HRESs. In this regard, an analysis covering the optimized indicators such as the cost drivers, energy index parameters, load indicators, battery’s state of charge, PV generator area, design parameters such as the LPSP, and the wind power generation to load ratio, has also been performed.

关键词： hybrid renewable energy systems (HRESs)     design and optimization     environmental pollutions     PV array     wind turbines (WTs)     inverter     diesel generator (DG)    

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Feasibility of using wind turbines for renewable hydrogen production in Firuzkuh, Iran

Ali MOSTAFAEIPOUR, Mojtaba QOLIPOUR, Hossein GOUDARZI

《能源前沿（英文）》 2019年 第13卷 第3期   页码 494-505 doi: 10.1007/s11708-018-0534-6

摘要： The present study was conducted with the objective of evaluating several proposed turbines from 25 kW to 1.65 MW in order to select the appropriate turbine for electricity and hydrogen production in Firuzkuh area using the decision making trial and evaluation (DEMATEL) and data envelopment analysis (DEA) methods. Initially, five important factors in selection of the best wind turbine for wind farm construction were determined using the DEMATEL technique. Then, technical-economic feasibility was performed for each of the eight proposed turbines using the HOMER software, and the performance score for each proposed wind turbine was obtained. The results show that the GE 1.5sl model wind turbine is suitable for wind farm construction. The turbine can generate 5515.325 MW of electricity annually, which is equivalent to $ 1103065. The average annual hydrogen production would be 1014 kg for Firuzkuh by using the GE 1.5sl model turbine.

关键词： wind turbine     hydrogen production     HOMER software     decision making trial and evaluation (DEMATEL)     data envelopment analysis (DEA)     Firuzkuh    

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Powertrain control of a solar photovoltaic-battery powered hybrid electric vehicle

P. PADMAGIRISAN, V. SANKARANARAYANAN

《能源前沿（英文）》 2019年 第13卷 第2期   页码 296-306 doi: 10.1007/s11708-018-0605-8

摘要： This paper proposes a powertrain controller for a solar photovoltaic battery powered hybrid electric vehicle (HEV). The main objective of the proposed controller is to ensure better battery management, load regulation, and maximum power extraction whenever possible from the photovoltaic panels. The powertrain controller consists of two levels of controllers named lower level controllers and a high-level control algorithm. The lower level controllers are designed to perform individual tasks such as maximum power point tracking, battery charging, and load regulation. The perturb and observe based maximum power point tracking algorithm is used for extracting maximum power from solar photovoltaic panels while the battery charging controller is designed using a PI controller. A high-level control algorithm is then designed to switch between the lower level controllers based on different operating conditions such as high state of charge, low state of charge, maximum battery current, and heavy load by respecting the constraints formulated. The developed algorithm is evaluated using theoretical simulation and experimental studies. The simulation and experimental results are presented to validate the proposed technique.

关键词： battery management system     hybrid electric vehicles (HEVs)     maximum power point tracking (MPPT)     solar photovoltaic    

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MPC-based interval number optimization for electric water heater scheduling in uncertain environments

Jidong WANG, Chenghao LI, Peng LI, Yanbo CHE, Yue ZHOU, Yinqi LI

《能源前沿（英文）》 2021年 第15卷 第1期   页码 186-200 doi: 10.1007/s11708-019-0644-9

摘要： In this paper, interval number optimization and model predictive control are proposed to handle the uncertain-but-bounded parameters in electric water heater load scheduling. First of all, interval numbers are used to describe uncertain parameters including hot water demand, ambient temperature, and real-time price of electricity. Moreover, the traditional thermal dynamic model of electric water heater is transformed into an interval number model, based on which, the day-ahead load scheduling problem with uncertain parameters is formulated, and solved by interval number optimization. Different tolerance degrees for constraint violation and temperature preferences are also discussed for giving consumers more choices. Furthermore, the model predictive control which incorporates both forecasts and newly updated information is utilized to make and execute electric water heater load schedules on a rolling basis throughout the day. Simulation results demonstrate that interval number optimization either in day-ahead optimization or model predictive control format is robust to the uncertain hot water demand, ambient temperature, and real-time price of electricity, enabling customers to flexibly adjust electric water heater control strategy.

关键词： electric water heater     load scheduling     interval number optimization     model predictive control     uncertainty    

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Sizing of hybrid PMSG-PV system for battery charging of electric vehicles

M. M. RAJAN SINGARAVEL,S. ARUL DANIEL

《能源前沿（英文）》 2015年 第9卷 第1期   页码 68-74 doi: 10.1007/s11708-015-0349-7

摘要： The number of electric vehicles are increasing in the society as they are considered as zero emission vehicles and also because conventional fuels are becoming expensive. Additional electrical power should be produced to meet the energy requirement of this increase in electric vehicle population. To use the existing grid infrastructure without any failure, installing distributed generator at secondary distribution network is essential. In this work, sizing of wind-driven permanent magnet synchronous generator—photovoltaic hybrid distributed generating system has been attempted to meet the energy demand of electric vehicles of a particular residential area. Different feasible combinations for wind generator capacity and photovoltaic capacity are obtained to satisfy the additional energy requirement. Results are analyzed based on energy, financial payback periods and daily power profile of the hybrid system. Based on this analysis, the sizes of wind generator and photovoltaic array have been chosen to meet the energy demand of electric vehicles of that particular residential locality.

关键词： electric vehicles     hybrid PMSG-PV system     smart grid    

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Layout optimization of steel reinforcement in concrete structure using a truss-continuum model

《结构与土木工程前沿（英文）》 2023年 第17卷 第5期   页码 669-685 doi: 10.1007/s11709-023-0963-0

摘要： Owing to advancement in advanced manufacturing technology, the reinforcement design of concrete structures has become an important topic in structural engineering. Based on bi-directional evolutionary structural optimization (BESO), a new approach is developed in this study to optimize the reinforcement layout in steel-reinforced concrete (SRC) structures. This approach combines a minimum compliance objective function with a hybrid truss-continuum model. Furthermore, a modified bi-directional evolutionary structural optimization (M-BESO) method is proposed to control the level of tensile stress in concrete. To fully utilize the tensile strength of steel and the compressive strength of concrete, the optimization sensitivity of steel in a concrete–steel composite is integrated with the average normal stress of a neighboring concrete. To demonstrate the effectiveness of the proposed procedures, reinforcement layout optimizations of a simply supported beam, a corbel, and a wall with a window are conducted. Clear steel trajectories of SRC structures can be obtained using both methods. The area of ​​critical tensile stress in concrete yielded by the M-BESO is more than 40% lower than that yielded by the uniform design and BESO. Hence, the M-BESO facilitates a fully digital workflow that can be extremely effective for improving the design of steel reinforcements in concrete structures.

关键词： bi-directional evolutionary structural optimization     steel-reinforced concrete     concrete stress     reinforcement method     hybrid model    

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Vibration-based crack prediction on a beam model using hybrid butterfly optimization algorithm with artificial

Abdelwahhab KHATIR; Roberto CAPOZUCCA; Samir KHATIR; Erica MAGAGNINI

《结构与土木工程前沿（英文）》 2022年 第16卷 第8期   页码 976-989 doi: 10.1007/s11709-022-0840-2

摘要： Vibration-based damage detection methods have become widely used because of their advantages over traditional methods. This paper presents a new approach to identify the crack depth in steel beam structures based on vibration analysis using the Finite Element Method (FEM) and Artificial Neural Network (ANN) combined with Butterfly Optimization Algorithm (BOA). ANN is quite successful in such identification issues, but it has some limitations, such as reduction of error after system training is complete, which means the output does not provide optimal results. This paper improves ANN training after introducing BOA as a hybrid model (BOA-ANN). Natural frequencies are used as input parameters and crack depth as output. The data are collected from improved FEM using simulation tools (ABAQUS) based on different crack depths and locations as the first stage. Next, data are collected from experimental analysis of cracked beams based on different crack depths and locations to test the reliability of the presented technique. The proposed approach, compared to other methods, can predict crack depth with improved accuracy.

关键词： damage prediction     ANN     BOA     FEM     experimental modal analysis    

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Fuel optimal control of parallel hybrid electric vehicles

PU Jinhuan, YIN Chenliang, ZHANG Jianwu

《机械工程前沿（英文）》 2008年 第3卷 第3期   页码 337-342 doi: 10.1007/s11465-008-0057-7

摘要： A mathematical model for fuel optimal control and its corresponding dynamic programming (DP) recursive equation were established for an existing parallel hybrid electric vehicle (HEV). Two augmented cost functions for gear shifting and engine stop-starting were designed to limit their frequency. To overcome the problem of numerical DP dimensionality, an algorithm to restrict the exploring region was proposed. The algorithm significantly reduced the computational complexity. The system model was converted into real-time simulation code by using MATLAB/RTW to improve computation efficiency. Comparison between the results of a chassis dynamometer test, simulation, and DP proves that the proposed method can compute the performance limitation of the HEV within an acceptable time period and can be used to evaluate and optimize the control strategy.

关键词： mathematical     Comparison     computational complexity     dimensionality     corresponding    

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A review of optimization modeling and solution methods in renewable energy systems

《工程管理前沿（英文）》   页码 640-671 doi: 10.1007/s42524-023-0271-3

摘要： The advancement of renewable energy (RE) represents a pivotal strategy in mitigating climate change and advancing energy transition efforts. A current of research pertains to strategies for fostering RE growth. Among the frequently proposed approaches, employing optimization models to facilitate decision-making stands out prominently. Drawing from an extensive dataset comprising 32806 literature entries encompassing the optimization of renewable energy systems (RES) from 1990 to 2023 within the Web of Science database, this study reviews the decision-making optimization problems, models, and solution methods thereof throughout the renewable energy development and utilization chain (REDUC) process. This review also endeavors to structure and assess the contextual landscape of RES optimization modeling research. As evidenced by the literature review, optimization modeling effectively resolves decision-making predicaments spanning RE investment, construction, operation and maintenance, and scheduling. Predominantly, a hybrid model that combines prediction, optimization, simulation, and assessment methodologies emerges as the favored approach for optimizing RES-related decisions. The primary framework prevalent in extant research solutions entails the dissection and linearization of established models, in combination with hybrid analytical strategies and artificial intelligence algorithms. Noteworthy advancements within modeling encompass domains such as uncertainty, multienergy carrier considerations, and the refinement of spatiotemporal resolution. In the realm of algorithmic solutions for RES optimization models, a pronounced focus is anticipated on the convergence of analytical techniques with artificial intelligence-driven optimization. Furthermore, this study serves to facilitate a comprehensive understanding of research trajectories and existing gaps, expediting the identification of pertinent optimization models conducive to enhancing the efficiency of REDUC development endeavors.

关键词： renewable energy system     bibliometrics     mathematical programming     optimization models     solution methods    

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Impact of crude distillation unit model accuracy on refinery production planning

Gang FU, Pedro A. Castillo CASTILLO, Vladimir MAHALEC

《工程管理前沿（英文）》 2018年 第5卷 第2期   页码 195-201 doi: 10.15302/J-FEM-2017052

摘要： In this work, we examine the impact of crude distillation unit (CDU) model errors on the results of refinery-wide optimization for production planning or feedstock selection. We compare the swing cut+ bias CDU model with a recently developed hybrid CDU model (Fu et al., 2016). The hybrid CDU model computes material and energy balances, as well as product true boiling point (TBP) curves and bulk properties (e.g., sulfur % and cetane index, and other properties). Product TBP curves are predicted with an average error of 0.5% against rigorous simulation curves. Case studies of optimal operation computed using a planning model that is based on the swing cut+ bias CDU model and using a planning model that incorporates the hybrid CDU model are presented. Our results show that significant economic benefits can be obtained using accurate CDU models in refinery production planning.

关键词： impact of model accuracy on production planning     swing cut+ bias CDU model     hybrid CDU model     refinery feedstock selection optimization     optimization of refinery operation    

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A novel hybrid model for water quality prediction based on VMD and IGOA optimized for LSTM

《环境科学与工程前沿（英文）》 2023年 第17卷 第7期 doi: 10.1007/s11783-023-1688-y

摘要：

● A novel VMD-IGOA-LSTM model has proposed for the prediction of water quality.

关键词： Water quality prediction     Grasshopper optimization algorithm     Variational mode decomposition     Long short-term memory neural network    

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Regenerative braking control strategy in mild hybrid electric vehicles equipped with automatic manual

QIN Datong, YE Ming, LIU Zhenjun

《机械工程前沿（英文）》 2007年 第2卷 第3期   页码 364-369 doi: 10.1007/s11465-007-0064-0

摘要： The actual regenerative braking force of an integrated starter/generator (ISG), which is varied with desired braking deceleration and vehicle speed, is calculated based on an analysis of the required deceleration, maximum braking force of ISG, engine braking force and state of charge (SOC) of battery. Braking force distribution strategies are presented according to the actual regenerative braking force of ISG. To recover the vehicle s kinetic energy maximally, braking shift rules for a mild hybrid electric vehicle (HEV) equipped with automatic manual transmission (AMT) are brought forward and effects of transmission ratios are considered. A test-bed is built up and regenerative braking tests are carried out. The results show that power recovered by the braking shift rules is more than that recovered by the normal braking control rules.

关键词： SOC     Braking     battery     regenerative braking     starter/generator    

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一种基于高斯过程与粒子群算法的CNN超参数自动搜索混合模型优化算法 Research Article

闫涵,仲崇权,吴玉虎,张立勇,卢伟

《信息与电子工程前沿（英文）》 2023年 第24卷 第11期   页码 1557-1573 doi: 10.1631/FITEE.2200515

摘要： 卷积神经网络（CNN）在许多实际应用领域中有着快速发展。然而，CNN性能很大程度上取决于其超参数，而为CNN配置合适的超参数通常面临着以下3个挑战：（1）不同类型CNN超参数的混合变量编码问题；（2）评估候选模型的昂贵计算成本问题；（3）确保搜索过程中收敛速率和模型性能问题。针对上述问题，提出一种基于高斯过程（GP）和粒子群优化算法（PSO）的混合模型优化算法（GPPSO），用于自动搜索最优的CNN超参数配置。首先，设计一种新的编码方法高效编码CNN中不同类型的超参数。其次，提出一种混合代理辅助（HSA）模型降低评估候选模型的高计算成本。最后，设计一种新的激活函数改善模型性能并确保收敛速率。在图像分类基准数据集上进行了大量实验，验证GPPSO优于最先进的方法。以金属断口诊断为例，验证GPPSO算法在实际应用中的有效性。实验结果表明，GPPSO仅需0.04和1.70 GPU天即可在CIFAR-10和CIFAR-100数据集上实现95.26％和76.36％识别准确率。

关键词： 卷积神经网络；高斯过程；混合模型；超参数优化；混合变量；粒子群优化    

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标题 作者 时间 类型 操作

Optimal design and development of PV-wind-battery based nano-grid system: A field-on-laboratory demonstration

B. TUDU, K. K. MANDAL, N. CHAKRABORTY

期刊论文

Fuel poverty and low carbon emissions: a comparative study of the feasibility of the hybrid renewable

期刊论文

State-of-art review of the optimization methods to design the configuration of hybrid renewable energy

Maurizio FACCIO, Mauro GAMBERI, Marco BORTOLINI, Mojtaba NEDAEI

期刊论文

Feasibility of using wind turbines for renewable hydrogen production in Firuzkuh, Iran

Ali MOSTAFAEIPOUR, Mojtaba QOLIPOUR, Hossein GOUDARZI

期刊论文

Powertrain control of a solar photovoltaic-battery powered hybrid electric vehicle

P. PADMAGIRISAN, V. SANKARANARAYANAN

期刊论文

MPC-based interval number optimization for electric water heater scheduling in uncertain environments

Jidong WANG, Chenghao LI, Peng LI, Yanbo CHE, Yue ZHOU, Yinqi LI

期刊论文

Sizing of hybrid PMSG-PV system for battery charging of electric vehicles

M. M. RAJAN SINGARAVEL,S. ARUL DANIEL

期刊论文

Layout optimization of steel reinforcement in concrete structure using a truss-continuum model

期刊论文

Vibration-based crack prediction on a beam model using hybrid butterfly optimization algorithm with artificial

Abdelwahhab KHATIR; Roberto CAPOZUCCA; Samir KHATIR; Erica MAGAGNINI

期刊论文

Fuel optimal control of parallel hybrid electric vehicles

PU Jinhuan, YIN Chenliang, ZHANG Jianwu

期刊论文

A review of optimization modeling and solution methods in renewable energy systems

期刊论文

Impact of crude distillation unit model accuracy on refinery production planning

Gang FU, Pedro A. Castillo CASTILLO, Vladimir MAHALEC

期刊论文

A novel hybrid model for water quality prediction based on VMD and IGOA optimized for LSTM

期刊论文

Regenerative braking control strategy in mild hybrid electric vehicles equipped with automatic manual

QIN Datong, YE Ming, LIU Zhenjun

期刊论文

一种基于高斯过程与粒子群算法的CNN超参数自动搜索混合模型优化算法

闫涵,仲崇权,吴玉虎,张立勇,卢伟

期刊论文