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Optimal planning and design of run-of-river hydroelectric power projects

RENEWABLE ENERGY 2019年 141卷 858-873页

作者： Ibrahim, Mohamed Imam, Yehya Ghanem, Ashraf Cairo Univ Fac Engn Dept Irrigat & Hydraul Giza Egypt Univ Sci & Technol Zewail City Sci & Technol Environm Engn Program Giza Egypt

An optimal planning and preliminary-design (OPD) model was developed to maximize the annual net benefit of run-of-river (RoR) hydropower projects along a stream. The OPD model identifies optimal, non-overlapping RoR projects along the given stream. For each project, the OPD model determines intake location;penstock diameter and length;and type, number, and discharge of turbines. The OPD model applies genetic algorithm in two stages. The first stage optimizes design of individual potentially overlapping projects densely spaced at uniform intervals along the stream and the second stage determines the set of non-overlapping projects that maximizes the net hydropower benefit. Results of the OPD model compared favorably to results of previous models for a hypothetical case study. Further application of the OPD model to idealized case studies with different stream elevation profiles and with tributary flows indicated that the model gives reliable results. The OPD model was used to identify optimal RoR projects for the Guder River, Ethiopia. The OPD model identified 22 optimal RoR projects covering similar to 49 km of the 127-km-long Guder River. The total annual generated energy from the identified projects is similar to 540 GWh and the installed capacity for individual projects ranges between similar to 1 MW and 21 MW. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Hydropower Run-of-river genetic algorithm optimization Guder river

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optimization-Based Mitigation Techniques of the Temporary Overvoltage in Large Offshore Wind Farm

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IEEE ACCESS 2023年 11卷 6320-6330页

作者： Said, Abdelrahman Ezzat, Mahmoud Abd-Allah, Mousa A. A. Fouda, Mostafa M. M. Abouelatta, Mohamed A. A. Benha Univ Fac Engn Shoubra Dept Elect Engn Cairo 11672 Egypt Idaho State Univ Coll Sci & Engn Dept Elect & Comp Engn Pocatello ID 83209 USA

Overvoltage transient is the major danger facing large offshore wind farms, as it may lead to a complete failure of the system components. A 150 MW offshore wind farm was modeled using the ATP-EMTP package to analyze the effect of the temporary overvoltage resulting from de-energization conditions, and the ferro resonance phenomenon resulting from the asymmetric opening of circuit breaker pole(s). The results showed that the best scenario to shut down such a system from the grid with minimum values of temporary overvoltage is to disconnect it, feeder, by a feeder. The stuck of one or more poles during the opening operation of the circuit breaker is a dangerous phenomenon, as it induces a high overvoltage value, which lasts for a long time causing more electric stress on the sensitive components of the system. The use of the Pre-Insertion Resistor PIR was recommended as a mitigation technique for the temporary overvoltage in large offshore wind farms, as it proves a significant reduction in the overvoltage values reaches to 79.44 % compared to surge arrester and shunt reactor which reduce the over voltage by 68.33%, 66.29% respectively. The genetic algorithm was used to find the optimum value of the PIR and shunt reactor that leads to the minimum TOV. The optimum value of PIR which was recorded is equal to 57.352 Ohm, which leads to more reduction in the overvoltage value by 9.67%. Also, the optimum values of the resistor and inductor of the shunt reactor were found to be 11.238 Ohms and 37.246 mH which leads to more reduction in the overvoltage value by 21.97% compared to the reduction without optimization.

关键词： Voltage control Wind turbines Transient analysis Wind farms Circuit faults Circuit breakers Rotors Temporary overvoltage overvoltage mitigation ATP modeling genetic algorithm optimization

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optimization of cellulose extraction process from sugar beet pulp and preparation of its nanofibers with choline chloride-lactic acid deep eutectic solvents

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BIOMASS CONVERSION AND BIOREFINERY 2023年第16期13卷 14457-14469页

作者： Soleimanzadeh, Hamid Bektashi, Fatemeh Mirzaee Ahari, Samaneh Zamani Salari, Dariush Olad, Ali Ostadrahimi, Alireza Univ Tabriz Fac Chem Dept Appl Chem Tabriz Iran Tabriz Univ Med Sci Fac Nutr & Food Sci Nutr Res Ctr Tabriz Iran

In this novel bench-top experimental and statistical investigation, the effects of influencing parameters on cellulose extraction have been studied and optimized. Chemically isolated cellulose was used at the optimum condition for the purpose of cellulose nanofiber preparation by deep eutectic solvent (DES) application. For this purpose, the Taguchi method was applied for experimental design. Six parameters which have more signal-to-noise ratio were selected as influencing parameters. These parameters consist of solvent ratio for dewaxing, depectinization pH and time, delignification pH and time, and pH of hemicellulose removal. The effect of these parameters on the cellulose extraction was modeled and optimized by the application of artificial neural network (ANN), coupled with genetic algorithm (GA). The ANN model, by establishing of feedforward backpropagation network with topologies 6, 13, and 1, was applied to model the relation between the extraction condition and cellulose extraction. The results confirmed that the best neural network structure has the ability of cellulose extraction yield prediction with an acceptable level of accuracy. The optimization results show the maximum cellulose extraction would be achieved at the following conditions: pectin extraction time of 1.62 h, delignification time of 2.19 h, the solvent ratio for dewaxing of 0.89 (V/V%), depectinization pH of 2.06, delignification pH of 5.48, and hemicellulose removal pH of 11.36. Under these conditions, the experimental extraction condition yield was 91.7% for cellulose extraction, which matched with the predictive extraction yield of 92.3%. Chemically extracted cellulose at the above condition was applied to prepare cellulose nanofibers. For this purpose, choline chloride-lactic acid-based DES pretreatment was used. The structure of the extracted cellulose and prepared cellulose nanofibers by the application of FTIR, XRD, Fe-SEM, and TEM methods was characterized. The XRD diffractograms a

关键词： Cellulose extraction optimization Artificial neural network genetic algorithm optimization Cellulose nanofibers Deep eutectic solvent (DESs)

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Research on fault tolerant control system based on optimized neural network algorithm

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2020年第6期39卷 9073-9083页

作者： Shan, Xianming Liu, Huixin Liu, Yefeng Liaoning Key Lab Informat Phys Fus & Intelligent Fushun 113122 Liaoning Peoples R China Shenyang Inst Technol Sch Informat & Control Fushun Liaoning Peoples R China Shenyang Inst Technol Sch Mech Engn & Automat Fushun Liaoning Peoples R China

Due to the strict personnel control measures in COVID-19 epidemic, the control system cannot be maintained and managed manually. This puts forward higher requirements for the accuracy of its fault-tolerant performance. The control system plays an increasingly important role in the rapid development of industrial production. When the sensor in the system fails, the system will become unstable. Therefore, it is necessary to accurately and quickly diagnose the faults of the system sensors and maintain the system in time. This paper takes the control system as the object to carry out the fault diagnosis and fault-tolerant control research of its sensors. A network model of wavelet neural network is proposed, and an improved genetic algorithm is used to optimize the weights and thresholds of the neural network model to avoid the deficiencies of traditional neural network algorithms. For the depth sensor of a certain system, an online fault diagnosis scheme based on RBF (Radial Basis Function) neural network and genetic algorithm optimized neural network was designed. The disturbance fault, "stuck" fault, drift fault and oscillation fault of the depth sensor are simulated. Simulation experiments show that both online fault diagnosis schemes can accurately identify sensor faults and the genetic algorithm optimized neural network is superior to RBF neural network in both recognition accuracy and training time under the influence of COVID-19.

关键词： Fault diagnosis COVID-19 fault-tolerant control neural network genetic algorithm optimization

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genetic Based Approach for Optimal Power and Channel Allocation to Enhance D2D Underlaied Cellular Network Capacity in 5G

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Computers, Materials & Continua 2022年第8期72卷 3751-3762页

作者： Ahmed.A.Rosas Mona Shokair M.I.Dessouky Department of Electronics and Electrical Communication Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

With the obvious throughput shortage in traditional cellular radio networks,Device-to-Device(D2D)communications has gained a lot of attention to improve the utilization,capacity and channel performance of nextgeneration *** this paper,we study a joint consideration of power and channel allocation based on genetic algorithm as a promising direction to expand the overall network capacity for D2D underlaied cellular *** genetic based algorithm targets allocating more suitable channels to D2D users and finding the optimal transmit powers for all D2D links and cellular users efficiently,aiming to maximize the overall system throughput of D2D underlaied cellular network with minimum interference level,while satisfying the required quality of service QoS of each *** simulation results show that our proposed approach has an advantage in terms of maximizing the overall system utilization than fixed,random,BAT algorithm(BA)and Particle Swarm optimization(PSO)based power allocation schemes.

关键词： 5G D2D communication spectrum allocation power allocation genetic algorithm optimization BAT-optimization particle swarm optimization

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A sustainable exergy model for energy-water nexus in the hot regions: integrated combined heat, power and water desalination systems

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JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY 2021年第3期145卷 709-726页

作者： Ansari, Mehran Beitollahi, Armin Ahmadi, Pouria Rezaie, Behnaz Univ Tehran Sch Mech Engn Coll Engn POB 11155-4563 Tehran Iran Univ Idaho Appl Energy Res Lab AERL Dept Mech Engn Coll Engn 875 Perimeter Dr Moscow ID 83844 USA

Water scarcity is a worldwide concern for Earth citizens. Finding new methods for water concentration is essential for the extension of life. The water issue is more intense in the regions with a warm to the tropical environment. Considering the cooling demand of these regions, which consequently requires excess energy to satisfy the cooling load, having a thermal system to support three concerns of the water, cooling, and power would be the key for the warm/hot weather areas. In the present study, a novel model by integration of gas turbine power cycle with a solar parabolic collector, a steam turbine, heat recovery, steam generator, multi-effect desalination, and absorption chiller is proposed. The suggested model is optimized through developing a comprehensive multi-objective function to maximize the exergy efficiency and minimize the cost. Using the genetic algorithm method, the model is optimized based on six design parameters such as condenser pressure, number of solar parabolic through collector rows, gas turbine and steam turbine inlet temperature, high and low pressure, high- and low-pressure pinch points. The final optimal design point of this cycle enables the overall exergy efficiency of 36.16% and 188.43 $ h(-1) of the total cost rate value;also, this integrated energy system provides the net electrical generation of 5.18 MW and the cooling load rate of 406.18 KW and generates 2.57 kg s(-1) of desalinated water. In this novel cycle solar energy is used for preheating the inflow of the combustion chamber. A dual pressure heat recovery exploits thermal energy of flue gas, which runs both desalination and multi-effect absorption system and circulates in simultaneous water and cooling load generation. Finally, by utilizing the genetic 1 algorithm, the optimal system is developed.

关键词： Integrated combined power plant Gas turbine Heat recovery Absorption chiller genetic algorithm optimization Double-effect desalination

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Development of sensor placement optimization tool and application to large-span cable-stayed bridge

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JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING 2019年第1期9卷 77-90页

作者： Wu, Zheng Yi Zhou, Kai Shenton, Harry W., III Chajes, Michael J. Bentley Syst Inc Watertown CT 06795 USA Univ Delaware Dept Civil & Environm Engn Newark DE USA

Structural health monitoring (SHM) is essential for engineers to effectively evaluate structural performance. The accelerometers and strain gauges are commonly used for monitoring and testing structural performance. Placing both types of sensors is the key step for SHM and structural testing. This paper presents the development and application of the sensor placement optimization methods, which have been integrated and implemented in a versatile software tool for maximizing the sensor coverage capacity for structural performance assessment. The sensor placement solutions are optimized using a parallel optimization framework based on the competent genetic algorithm, leading to a number of features that enrich the application flexibility. The developed methods and software tool provide a generic approach for multi-type sensor placement. The integrated tool has been applied to the Indian River Inlet Bridge a large-span cable-stayed bridge to demonstrate and validate the effectiveness of the proposed solution methods for facilitating real world SHM practice.

关键词： Strain gauge placement Accelerometer placement Structural health monitoring genetic algorithm optimization

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Lay-up optimisation of fibre-metal laminates panels for maximum impact absorption

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JOURNAL OF COMPOSITE MATERIALS 2020年第29期54卷 4591-4609页

作者： Arhore, Edore G. Yasaee, Mehdi Cranfield Univ Sch Aerosp Transport & Mfg Cranfield MK43 0AL Beds England

This paper introduces a methodology utilising a ply-ply damage Finite Element models with genetic algorithm optimisation procedure to investigate the effect of lay-up configuration on the impact absorption properties of fibre metal laminates (FMLs). The methodology was carried out in two steps. In the first step, a pseudo-2D model was used to explore the vast design space to identify potential optimised layup-configurations. In the second step, the optimised configurations were studied in full 3 D, with high fidelity simulations, verifying the results obtained from the optimisation process. The design variables used include thickness and material (including fibre orientation) of each ply. The results produced an optimised configuration consisting of a metallic ply on the impacted side followed by a cross-ply composite lay-up. The results also suggest that the first composite ply (second ply of the FML) should be about 3 times thicker than the other plies.

关键词： Fibre-metal laminate FML genetic algorithm optimization impact energy absorption ABAQUS

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DTester: Diversity-Driven Test Case Generation for Web Applications

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INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING 2024年第2期34卷 357-390页

作者： Wu, Shumei Chang, Zexing Zhang, Zhanwen Li, Zheng Liu, Yong Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing 100000 Peoples R China

Search-based Test Case Generation (TCG) for web applications suffers from unstable performance and suboptimal test suite problems due to diversity loss. However, previous diversity metrics mainly only focus on client-side models or server-side code, which are prone to low robustness and poor generalization in practical applications. We propose a diversity-driven TCG method DTester, which can maximize behavior exploration and minimize the test suite size while covering more server-side vulnerable paths. Three diversity metrics (i.e. phenotypic coupling, intent coupling and competitiveness) are proposed to measure the underlying relationship between test cases from user behavior, code logic and test execution history. Moreover, a 3-dimensional weight graph is designed to model association among metrics, which provides fine-grained guidance for the genetic algorithm to generate diverse test cases from the client-side behavior model. Our empirical evaluation on five web applications shows that DTester can efficiently and robustly generate better test suites than the state-of-the-art TCG method. The maximum improvement is 85%, 60%, 716% and 88% in efficiency, test suite size, diversity and robustness.

关键词： Web application test case generation genetic algorithm optimization diversity metric vulnerable path

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Comparison Among Resilience and Entropy Index in the Optimal Rehabilitation of Water Distribution Networks Under Limited-Budgets

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WATER RESOURCES MANAGEMENT 2018年第12期32卷 3997-4011页

作者： Cimorelli, L. Morlando, F. Cozzolino, L. D'Aniello, A. Pianese, D. Univ Naples Federico II Dept Civil Architectural & Environm Engn Via Claudio 21 I-80125 Naples Italy Parthenope Univ Ctr Direz Napoli Is C4 Dept Engn I-80143 Naples Italy

The replacement of existing pipes is a strategy for the rehabilitation of water distribution networks that is frequently adopted by water companies. Usually, the optimal choice of the pipes diameter is a difficult optimization task, because limited budgets are available. In order to support the selection of a rehabilitation strategy, surrogate reliability measures are often used as an indirect measure of the water distribution system hydraulic performance. Among others, the resilience and entropy indices have attracted considerable interest because they both represent a measure of the network robustness. In the present work, a comparison between these indices is provided in the framework of the optimal rehabilitation of an existing network under limited budget constraint. The resilience and entropy indices are applied to the case of a realistic water distribution network in an extended period simulation framework. Several values of the maximum budget allocable for rehabilitation are considered, and hydraulic calculations are undertaken by means of a pressure driven approach within a modified EPANET 2 environment. The effectiveness of the two surrogate reliability measures is demonstrated by an a-posteriori reliability assessment.

关键词： Water distribution networks rehabilitation Surrogate reliability measures comparison Network resilience Network entropy genetic algorithm optimization

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