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multiobjective optimization for hydro-photovoltaic hybrid power system considering both energy generation and energy consumption

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ENERGY SCIENCE & ENGINEERING 2018年第5期6卷 362-370页

作者： Li, Fang-Fang Qiu, Jun Wei, Jia-Hua China Agr Univ Coll Water Resources & Civil Engn Beijing 100083 Peoples R China Tsinghua Univ Dept Hydraul Engn State Key Lab Hydrosci & Engn Beijing 100084 Peoples R China Qinghai Univ State Key Lab Plateau Ecol & Agr Xining 810016 Qinghai Peoples R China

Hydropower can be an ideal compensation for fluctuant photovoltaic (PV) power due to its flexibility. In this study, a multiobjective optimization model considering energy generation and consumption simultaneously for a hydro-PV hybrid power system is proposed. With the daily mean radiation intensity and temperature, the PV power output is calculated. Taking reservoir release as the decision variable, the total energy generation of the hydro-PV system is maximized. Meanwhile, the gap between the energy generation and the energy consumption is minimized to reduce the abandoned PV power or hydropower. The proposed multiobjective model is optimized by Non-dominated Sorting Genetic Algorithms-II (NSGA-II). The Longyangxia Project, the largest hydro-photovoltaic hybrid power system in the world is taken as the study case to estimate the optimal operational strategies for different objectives in wet year, normal year, and dry year, respectively. The optimal operation process of the reservoir is presented, which is instructive for the operation in the future.

关键词： Energy consumption energy generation hydro-photovoltaic hybrid system multiobjective optimization NSGA-II

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multiobjective optimization for node adaptation in the analysis of composite plates using a meshless collocation method

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ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS 2015年 50卷 109-116页

作者： Roque, C. M. C. Madeira, J. F. A. Ferreira, A. J. M. Univ Porto Fac Engn IDMEC Polo FEUP P-4200465 Oporto Portugal Univ Lisbon Inst Super Tecn IDMEC LAETA P-1699 Lisbon Portugal ISEL P-1959007 Lisbon Portugal Univ Porto Fac Engn P-4200465 Oporto Portugal King Abdulaziz Univ Fac Sci Dept Math Jeddah Saudi Arabia

The bending of simply supported composite plates is analyzed using a direct collocation meshless numerical method. In order to optimize node distribution the Direct MultiSearch (DMS) for multi-objective optimization method is applied. In addition, the method optimizes the shape parameter in radial basis functions. The optimization algorithm was able to find good solutions for a large variety of nodes distribution. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Meshless method Radial basis functions multiobjective optimization Direct-search methods Paretodominance Composite plate

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multiobjective optimization design of green building envelope material using a non-dominated sorting genetic algorithm

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APPLIED THERMAL ENGINEERING 2017年 111卷 1255-1264页

作者： Yang, Ming-Der Lin, Min-Der Lin, Yu-Hao Tsai, Kang-Ting Natl Chung Hsing Univ Dept Civil Engn 250 Kuo Kuang Rd Taichung 402 Taiwan Natl Chung Hsing Univ Dept Environm Engn 250 Kuo Kuang Rd Taichung 402 Taiwan Natl Chung Hsing Univ Ctr Environm Restorat & Disaster Reduct 250 Kuo Kuang Rd Taichung 402 Taiwan Natl Chung Hsing Univ Program Landscape & Recreat 250 Kuo Kuang Rd Taichung 402 Taiwan

To realize the goal of environmental sustainability, improving energy efficiency in buildings is a major priority worldwide. However, the practical design of green building envelopes for energy conservation is a highly complex optimization problem, and architects must make multiobjective decisions. In practice, methods such as multicriteria analyses that entail capitalizing on possibly many (but in nearly any case limited) alternatives are commonly employed. This study investigated the feasibility of applying a multiobjective optimal model on building envelope design (MOPBEM), which involved integrating a building envelope energy performance model with a multiobjective optimizer. The MOPBEM was established to provide a reference for green designs. A nondominated sorting genetic algorithm-II (NSGA-lI) was used to achieve a tradeoff design set between three conflicting objectives, namely minimizing the envelope construction cost (ENVCOST), minimizing the envelope energy performance (ENVLOAD), and maximizing the window opening rate (WOPR). A real office building case was designed using the MOPBEM to identify the potential strengths and weaknesses of the proposed MOPBEM. The results showed that a high ENVCOST was expended in simultaneously satisfying the low ENVLOAD and high WOPR. Various designs exhibited obvious cost reductions compared with the original architects' manual design, demonstrating the practicability of the MOPBEM. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Green building multiobjective optimization Nondominated sorting genetic algorithm (NSGA-II) Building envelope Energy conservation

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multiobjective optimization of Control Valve Installation and DMA Creation for Reducing Leakage in Water Distribution Networks

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JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT 2019年第10期145卷 4019046.1-4019046.10页

作者： Creaco, Enrico Haidar, Hatem Univ Pavia Dipartimento Ingn Civile & Architettura Via Ferrata 3 I-27100 Pavia Italy Univ Exeter Coll Engn Phys & Math Sci Exeter EX4 4QF Devon England Univ Adelaide Sch Civil Environm & Min Engn Adelaide SA 5005 Australia Lebanese Univ Dept Civil Engn Rafic Hariri CampusHadath BP 2 Baabda Lebanon

This paper presents a novel methodology for optimizing simultaneously the installation of control valves and the creation of district metered areas (DMAs) in water distribution networks (WDNs). This methodology was developed through the multiobjective approach, by considering, as decisional variables, the sites for control valve installation and isolation valve closure. The proposed algorithm is based on the hybrid combination of three algorithms, a multiobjective genetic algorithm, which is entrusted with valve site search, and two embedded algorithms, the first based on iterated linear programming (LP) and the second based on graph theory, aimed at searching for the optimal settings of control valves and at partitioning the WDN into DMAs, respectively. The hybrid algorithm attempts to find optimal solutions in the trade-off between the following objective functions to be optimized simultaneously: total installation cost, daily leakage volume, and demand uniformity across DMAs. The applications to a small Lebanese WDN proved that the methodology can find, especially for high values of the total installation cost, effective control valve installations, and isolation valve closures in terms of leakage abatement while obtaining a uniform distribution of demands across DMAs.

关键词： multiobjective optimization Genetic algorithms Linear programming Water distribution Leakage Pressure Control valve District metered area (DMA) District Partitioning

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multiobjective optimization of the inspection intervals of a nuclear safety system: A clustering-based framework for reducing the Pareto Front

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ANNALS OF NUCLEAR ENERGY 2010年第6期37卷 798-812页

作者： Zio, E. Bazzo, R. Politecn Milan Dipartimento Energia I-20133 Milan Italy Ecole Cent Paris Supelec European Fdn New Energy EDF Paris France

In this paper, a framework is developed for identifying a limited number of representative solutions of a multiobjective optimization problem concerning the inspection intervals of the components of a safety system of a nuclear power plant. Pareto Front solutions are first clustered into "families", which are then synthetically represented by a "head of the family" solution. Three clustering methods are analyzed. Level Diagrams are then used to represent, analyse and interpret the Pareto Fronts reduced to their head-of-the-family solutions. Two decision situations are considered: without or with decision maker preferences, the latter implying the introduction of a scoring system to rank the solutions with respect to the different objectives: a fuzzy preference assignment is then employed to this purpose. The results of the application of the framework of analysis to the problem of optimizing the inspection intervals of a nuclear power plant safety system show that the clustering-based reduction maintains the Pareto Front shape and relevant characteristics, while making it easier for the decision maker to select the final solution. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Inspection interval optimization Safety system Nuclear power plant multiobjective optimization Genetic algorithms Subtractive clustering

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multiobjective optimization of ultrasound intensified and ionic liquid catalyzed in situ algal biodiesel production considering economic, environmental and safety indicators

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CHEMICAL ENGINEERING RESEARCH & DESIGN 2022年 180卷 134-152页

作者： Deshpande, Gunavant Shrikhande, Savyasachi Sawarkar, Ashish N. Patle, Dipesh S. Motilal Nehru Natl Inst Technol Allahabad Dept Chem Engn Prayagraj 211004 Uttar Pradesh India Indian Inst Technol Dept Chem Engn Roorkee 247667 Uttaranchal India

The current study focuses on the multiobjective optimization of an ultrasound intensified and ionic liquid catalyzed in situ transesterification of wet microalgae for renewable biodiesel production. The process is developed and simulated in Aspen Plus V10 simulator and an excel based multiobjective optimization (EMOO) programme for the elitist non-dominated sorting genetic algorithm-II is used for optimization. Total Annual Cost, i.e. TAC (representing economics), organic waste (representing cleaner production), individual risk, i.e. IR (representing risk to the human capital), and CO2 emission (representing environment) are chosen as the objectives for the constrained optimization of this process. The results show that the TAC reduces with the increase in the generation of organic waste, CO2 emission and IR. This article contemplates and articulates the reasons for the obtained trade-offs between objectives. The quantitative trade-offs between objectives aid to the better decision making about the process design and operation while satisfying economic, environmental and safety concerns. Finally, net flow method (NFM) has been implemented for the identification of best suitable solution in the Pareto-optimal fronts. Simultaneous optimization of all four objectives resulted in the impressive savings in TAC (~15%), organic waste (~33%), IR (~9%), and CO2 emission (~37%).& nbsp;(c) 2022 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved.

关键词： multiobjective optimization Microalgal biodiesel Ionic liquid catalyst In situ Ultrasound assisted

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multiobjective optimization of hard coating parameters designing for damping of the bladed disk

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING 2018年第9期232卷 1609-1619页

作者： Chen, Yugang Zhai, Jingyu Han, Qingkai Dalian Univ Technol Sch Mech Engn Dalian Peoples R China

In this paper, the damping capacity and the structural influence of the hard coating on the given bladed disk are optimized by the non-dominated sorting genetic algorithm (NSGA-II) coupled with the Kriging surrogate model. Material and geometric parameters of the hard coating are taken as the design variables, and the loss factors, frequency variations and weight gain are considered as the objective functions. Results of the bi-objective optimization are obtained as curved line of Pareto front, and results of the triple-objective optimization are obtained as Pareto front surface with an obvious frontier. The results can give guidance to the designer, which can help to achieve more superior performance of hard coating in engineering application.

关键词： Hard coating bladed disk multiobjective optimization damping capacity Kriging model NSGA-II

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multiobjective optimization of Multistage Synchronous Induction Coilgun Based on NSGA-II

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IEEE TRANSACTIONS ON PLASMA SCIENCE 2017年第7期45卷 1622-1628页

作者： Niu, Xiaobo Liu, Kaipei Zhang, Yadong Xiao, Gang Gong, Yujia Wuhan Univ Sch Elect Engn Wuhan 430072 Peoples R China

The structure and trigger control strategy have become the most important factors that restrict the performance of the multistage synchronous induction coilgun (MSSICG). However, it is still a difficult task to design MSSICG under overload constraint due to coupling between the multiple parameters. In this paper, the maximization of the emission efficiency and acceleration stationarity is treated as a multiobjective optimization problem. By analyzing the relationship between the number of turns and the other structural parameters of the launch, the multiobjective optimization model of MSSICG is established by the current filament method which was verified by the experimental data and finite-element method. And then the second generation nondominated sorting genetic algorithm (NSGA-II) and multiobjective particle swarm optimization (MOPSO) were employed to optimize the model in order to maximize the energy transfer efficiency while achieving the smooth acceleration of the armature. With the formulated optimization model, a five-stage synchronous induction coilgun is optimized as a special case. A decision-making procedure based on the fuzzy membership function is used for obtaining best compromise solution from the set of Pareto-solutions obtained through NSGA-II and MOPSO. In addition, the optimization performance of the proposed multiobjective optimization model and the single-objective optimization model of the MSSICG was compared. The result of optimization shows that the proposed multiobjective optimization model of MSSICG can effectively improve the performance of the coilgun compared with the single-objective optimization model which takes of the launch velocity and overload acceleration as the combination objective function or only the launch velocity.

关键词： Current filament method (CFM) fuzzy membership function (FMF) multiobjective optimization multiobjective particle swarm optimization (MOPSO) multistage synchronous induction coilgun (MSSICG) nondominated sorting genetic algorithm-II (NSGA-II)

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multiobjective optimization of ceramic-metal functionally graded plates using a higher order model

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COMPOSITE STRUCTURES 2018年第1期183卷 146-160页

作者： Franco Correia, Victor M. Aguilar Madeira, J. F. Araujo, Aurelio L. Mota Soares, Cristovao M. Univ Lisbon Inst Super Tecn IDMEC Av Rovisco Pais P-1049001 Lisbon Portugal Escola Super Naut Infante D Henrique Av Eng Bonneville Franco P-2770058 Paco De Arcos Portugal IPL ISEL Dept Math Rua Conselheiro Emidio Navarro P-1949014 Lisbon Portugal

A methodology of multiobjective design optimization of ceramic-metal composite plates with functionally graded materials, with properties varying through the thickness direction, obtained by an adequate variation of volume fractions of the constituent materials, is presented in this paper. Constrained optimization is conducted for different behavior objectives like the maximization of buckling load or fundamental natural frequency. Mass minimization and material cost minimization are also considered. The optimization problems are constrained by stress based failure criteria and other structural response constraints or manufacturing limitations. The design variables are the index of the power-law distribution in the metal-ceramic graded material and the thicknesses of the graded material and/or the metal and ceramic faces. An equivalent single layer finite element plate model having a displacement field based on a higher order shear deformation theory, accounting for the temperature dependency of the material properties, was developed and validated for the analysis of through-the-thickness ceramic-metal functionally graded plates. The optimization problems are solved with two direct search derivative-free algorithms: GLODS (Global and Local optimization using Direct Search) and DMS (Direct MultiSearch). DMS, the multiobjective optimization solver, is started from a set of local minimizers which are initially determined by the global optimizer algorithm GLODS for each one of the objective functions. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： multiobjective optimization Direct MultiSearch Higher order shear deformation theory Composites Functionally graded materials FGM plates

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multiobjective optimization of Multiproduct Batch Plants Scheduling Under Environmental and Economic Concerns

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AICHE JOURNAL 2011年第10期57卷 2766-2782页

作者： Capon-Garcia, Elisabet Bojarski, Aaron D. Espuna, Antonio Puigjaner, Luis Univ Politecn Cataluna Dept Chem Engn CEPIMA ETSEIB E-08028 Barcelona Spain

In hatch process scheduling, production trade-offs arise from the simultaneous consideration of different objectives. Economic goals are expressed in terms of plant profitability and productivity, whereas the environmental objectives are evaluated by means of metrics originated from the use of life cycle assessment methodology. This work illustrates a novel approach for decision making by using multiobjective optimization. In addition, different metrics are proposed to select a possible compromise based on the distance to a nonexistent utopian solution, whose objective function values are all optimal. Thus, this work provides a deeper insight into the influence of the metrics selection for both environmental and economic issues while considering the trade-offs of adopting a particular schedule. The use of this approach is illustrated through its application to a case study related to a multiproduct acrylic fiber production plant, special attention is put to the influence of product changeovers. (C) 2010 American Institute of Chemical Engineers AIChE J, 57: 2766-2782, 2011

关键词： LCA multiobjective optimization multiproduct batch scheduling product changeover

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