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Hybrid approach to FACTS devices allocation using multi-objective function with NSPSO and nsga-ii algorithms in Fuzzy framework

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2014年 62卷 586-598页

作者： Sedighizadeh, M. Faramarzi, H. Mahmoodi, M. M. Sarvi, M. Shahid Beheshti Univ Fac Elect & Comp Engn Tehran Iran Imam Khomeini Int Univ Fac Engn & Technol Qazvin Iran Islamic Azad Univ Saveh Branch Dept Elect Engn Saveh Iran

FACTS allocation and assessing its optimal capacity and their undeniable role on improvement of system's operation is one of most discussed themes in planning and exploitation of the power system. According to the importance of the objects such as power loss reduction, increase of the stability margin, voltage profile improvement and also, less cost imposition need to establish a partial balance between these several goals, FACTS allocation problem introduced as a multi-objective optimization problem. It postulates that the attainment of those registered goals simultaneously, implicates the utilization of the multi-objective optimization methods and finally reaches the Pareto optimal sets. Because of the achievement of this important object, two hybrid approaches based on NSPSO and nsga-ii algorithm and Fuzzy logic is presented in this paper that is able to present the Pareto optimal sets meanwhile to attend the technical and economic aspects. In this work, the problem's formulation and its analysis is described and finally the efficiency of these approaches in IEEE 14-bus and 30-bus test systems is analyzed. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： FACTS devices allocation nsga-ii algorithm NSPSO algorithm Fuzzy logic Multi-objective optimization

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Multi-Objective Optimization Strategy of Microgrid Based on Cooperative Operation of Optical Storage in Industrial Park

Multi-Objective Optimization Strategy of Microgrid Based on ...

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2025 International Conference on Electrical Automation and Artificial Intelligence, ICEAAI 2025

作者： Jin, Long Zhang, Yanchi School of Electrical Engineering Shanghai DianJi University Shanghai China

ISBN: (纸本)9798331506797

With the continuous development of photovoltaic power generation and energy storage technology, microgrid systems in industrial parks have gradually become an important means to achieve efficient use of green energy. Aiming at the energy demand of industrial parks, this paper proposes a multi-objective optimization strategy based on the cooperative operation of photovoltaic power generation and energy storage. By analyzing the fluctuation of photovoltaic power generation and the charge-discharge characteristics of the energy storage system, a multi-objective optimization model which can achieve energy balance and maximize economic benefits under different working conditions is constructed. Optimization objectives cover many aspects such as maximizing photovoltaic utilization, minimizing energy storage costs, matching load demand and reducing environmental pollution. In order to solve the multi-objective optimization problem, the non-dominated sorting genetic algorithm (nsga-ii) was used to solve the optimization model, and the actual data of the industrial park was simulated and verified. The results show that the optimization strategy can effectively improve the photovoltaic consumption rate, reduce the operating cost of the system, and ensure the stable operation of important loads, which provides a new technical solution for energy management in industrial parks. © 2025 IEEE.

关键词： Light storage collaboration Microgrid multi-objective optimization nsga-ii algorithm power Industrial Park

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Multi - Objective optimization of the global tungsten trade network for supply risk reduction and economic benefit improvement

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INTERNATIONAL REVIEW OF ECONOMICS & FINANCE 2025年 98卷

作者： Jia, Nanfei Pi, Zhengrong Zuo, Min Shi, Yuhang Xu, Xin Beijing Technol & Business Univ Sch Comp & Artificial Intelligence Beijing 102488 Peoples R China Beijing Technol & Business Univ Natl Engn Res Ctr Agriprod Qual Traceabil Beijing 102488 Peoples R China Beijing Wuzi Univ Beijing 101149 Peoples R China Nanjing Univ Finance & Econ Sch Finance Nanjing Peoples R China

As key minerals, tungsten resources are crucial for various industries. But uneven reserves and unstable international conditions increase the risk of supply disruption, impacting the stability and economic benefits of international trade. Therefore, this paper applies the multi-objective optimization model and nsga-ii algorithm to optimize the global tungsten trade network (GTTN) in 2022 by adjusting its supply relationship structure and trade volume.1 The results show that all optimized GTTNs improve stability and total value flow compared to the actual ones. Adding trade relationships, KOR-*CHN and ARE-*RUS, is beneficial to enhance total value flow of the GTTN. Adding trade relationships, PRT-*VNM and THA-*VNM, helps improve stability of the GTTN. The increase in value flow of added trade relationships follows power-law distribution. The research provides different options for trading countries to optimize supply relationships to improve stability and economic benefits of global tungsten trade.

关键词： Tungsten Trade stability Total trade value flow Multi-objective optimization model Supply relationship structure nsga-ii algorithm

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The objective design of triangular bucket for dam's spillway using Non-dominated Sorting Genetic algorithm ii: nsga-ii

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SCIENTIA IRANICA 2017年第1期24卷 19-27页

作者： Hojjati, S. H. Hojjati, S. H. Neyshabouri, S. A. A. Salehi Tarbiat Modares Univ Fac Civil & Environm Engn Tehran Iran Babol Univ Technol Fac Elect & Comp Engn Babol Sar Iran Tarbiat Modares Univ Fac Civil & Environm Engn Water Engn Res Inst Tehran Iran Amirkabir Univ Fac Civil & Environm Engn Tehran Iran

Ski jump is one of the most effective structures in energy dissipation over spillways. Spillways have long been of practical importance to safety of dams. The major criteria in hydraulic design are based on the analytical and empirical methods. In the current study, in order to increase chute spillway efficiency, a multi-objective evolutionary algorithm known as the Non-dominated Sorting Genetic algorithm ii (nsga-ii) has been utilized to design the optimal triangular bucket angle and chute width. In design method, two separate objective functions have been used. In the first objective function, equations of dynamic pressure of the bucket, the jet length after bucket, and the scour depth have been used. The second objective function is related to construction volume of chute spillway. For calibrating the first objective function, characteristics of Karoon iiI dam have been used as a case study. The difference between design parameters of Karoon iiI spillway and those from nsga-ii algorithm method is less than 12 percent. According to the results, if the jet length is considered as the most impressive parameter in the first objective function, design of the spillway becomes frugal. (C) 2017 Sharif University of Technology. All rights reserved.

关键词： Triangular flip bucket Chute spillway width Ski jump nsga-ii algorithm Karoon iiI dam

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Multi-point design optimization of hydrofoil for marine current turbine

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Journal of Hydrodynamics 2014年第5期26卷 807-817页

作者：罗兴锜朱国俊冯建军 Institute of Water Resources and Hydro-electric Engineering Xi’an University of Technology

The comprehensive performance of the marine current turbine is an important issue in the ocean energy development. Its key is the performance of the hydrofoil, which is used to form the turbine blade. A multi-point optimization method of the hydrofoil is proposed in this paper. In this method, the Bezier curve is used to parameterize the hydrofoil. The geometrical parameters are used as variables while the lift-drag ratio and the cavitation performance of the hydrofoil are used as the objective functions. The nsga-ii algorithm is chosen as the optimization algorithm. In order to resolve the difficulty of this high-dimensional multi-objective optimi- zation problem, the conception of the distance metric in the metric space is introduced to unify the lift-drag ratio and the cavitation performance under different working conditions. And then, the above optimization method is applied in the NACA63-815 hydro- foil＇s optimal design under three typical conditions. Finally, the results from the performance comparison of the original and optimi- zed hydrofoils obtained by using the CFD simulation are analyzed in detail. It is indicated that the optimized hydrofoils enjoy a better hydrodynamic performance than the original ones under the three conditions. The feasibility and the theoretical validity of this optimization method are confirmed by the results.

关键词： marine current turbine hydrofoil multi-point optimization metric space nsga-ii algorithm

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Efficient power performance analyses and multi-objective optimizations for closed regenerative gas turbine cycle based on five objectives and nsga-ii

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Energy 2025年

作者： Wanfeng Li Lingen Chen Yanlin Ge Huijun Feng Hubei Provincial Key Laboratory of Chemical Equipment Intensification and Intrinsic Safety Wuhan Institute of Technology Wuhan 430205 P. R. China Hubei Provincial Engineering Technology Research Center of Green Chemical Equipment Wuhan Institute of Technology Wuhan 430205 P. R. China Institute of Thermal Science and Power Engineering Wuhan Institute of Technology Wuhan 430205 P. R. China School of Mechanical &Electrical Engineering Wuhan Institute of Technology Wuhan 430205 P. R. China

Based on finite-time-thermodynamic (FTT) theory and irreversible closed regenerative gas turbine cycle model established before, the cycle’s efficient power ( ) expression is deduced, impacts of cycle parameters on are analyzed. The power, thermal efficiency, , power density and ecological function are taken as optimization objectives (OOs), HC distribution of hot-side heat-exchanger (HSHE) and compressor pressure ratio are taken as optimization variables, and single-, two-, three-, four- and five-objective optimizations for arbitrary combinations of OOs, which are totally 31 combinations, are carried out based on nsga-ii algorithm. The best set of solutions is obtained by comparing deviation indexes of decision-making methods: TOPSIS, LINMAP and Shannon Entropy. Results show that can be clearly enhanced by improving temperature ratio of heat reservoirs, efficiencies of turbine and compressor, and effectivenesses of regenerator, cold-side heat-exchanger and HSHE. For five-objective optimization, optimal HC distribution of HSHE is distributed between 0.355 and 0.405, mainly distributed between 0.375 and 0.405, and optimal pressure ratio is distributed between 7.5 and 20 for irreversible cycle. Endoreversible case is also provided and compared. The major contributions are introducing analysis and optimization and performing the five-objective optimizations for regenerative gas turbine cycle by applying the FTT theory and MOO.

关键词： irreversible closed regenerative gas turbine cycle efficient power performance analysis multi-objective optimization finite-time thermodynamics nsga-ii algorithm

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Time-of-use Pricing Model Considering Wind Power Uncertainty

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CSEE Journal of Power and Energy Systems 2022年第4期8卷 1039-1047页

作者： Gang Zhang Ye Yan Kaoshe Zhang Pingli Li Meng Li Qiang He Hailiang Chao State Key Laboratory of Eco-Hydraulics in Northwest Arid Region Xi'an University of TechnologyXi'an 710048China Institute of Electrical Engineering Xi'an University of TechnologyXi'an 710048China Shaanxi Gas Group New Energy Development Co. LtdXi'an 710016China

Large-scale new energy pressures on the grids bring challenges to power system's security and *** order to optimize the user's electricity consumption behavior and ease pressure,which is caused by new energy on the grid,this paper proposes a time-of-use price model that takes wind power uncertainty into ***,the interval prediction method is used to predict wind *** typical wind power scenes are selected by random sampling and bisecting the K-means *** this basis,integer programming is used to divide the peak-valley period of the multi-scenes ***,under the condition of many factors such as user response based on consumer psychology,user electricity charge and power consumption,this paper takes the peak-valley difference of equivalent net load and the user dissatisfaction degree as the goal,and using the nsga-ii multi-objective optimization algorithm,evaluates the Pareto solution set to obtain the optimal *** order to test the validity of the model proposed in this paper,we apply it to an industrial user and wind farms in Yan'an city,*** results show that the model can effectively ensure the user's electrical comfort while achieving the role of peak shaving and valley flling.

关键词： Bisecting K-means algorithm interval prediction integer programming nsga-ii algorithm peakvalley difference time-of-use price user dissatisfaction wind power uncertainty

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An artificial intelligence optimization method of back analysis of unsteady-steady seepage field for the dam site under complex geological condition

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BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT 2024年第4期83卷 127-127页

作者： Yu, Jia'ao Shen, Zhenzhong Li, Haoxuan Li, Fangzhi Huang, Zhangxin Hohai Univ Coll Water Conservancy & Hydropower Engn Nanjing 210024 Peoples R China Minist Transport Key Lab Transport Ind Comprehens Transportat Theor Nanjing Modern Multimodal Transportat Lab Nanjing 211100 Peoples R China Hohai Univ State Key Lab Hydrol Water Resources & Hydraul Eng Nanjing 210024 Peoples R China Longkou Housing & Urban Rural Dev Adm Yantai Peoples R China

The investigation of seepage situation of a reservoir under complex geological conditions is greatly significant and is necessary to be determined by geologic survey or numerical analysis. Based on previous geological survey data, a 3-dimensional seepage back analysis was conducted. In this study, two hydraulic conditions of unsteady and steady seepage were considered, and the corresponding back analysis came down to a multi-objective decision-making problem. The GRNN model was trained by PSO algorithm for obtaining the relationship between permeability coefficients and monitoring data, and by combining the nsga-ii algorithm, the best unbiased solution of permeability coefficients for the multi-objective function established by monitoring data of seepage discharge and pressure head was searched via iteration calculation. On this basis, the seepage safety of the reservoir was evaluated. Through taking the seepage discharge of the whole reservoir into account, the problem in the traditional seepage field back analysis that the foundation strata seepage parameters are insensitive to the pressure head inside the dam was solved. And the inversion results can provide a supplement for the geological survey under complex geological conditions. The method adopted in this paper may provide significant references for the anti-seepage design and reinforcement of hydraulic structures with complex geological conditions.

关键词： Complex geological condition Dam site area Seepage field PSO-GRNN model nsga-ii algorithm Back analysis Multi-objective decision

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Sensitivity analysis and multi-objective optimization of the virtual track train parameters considering the coupling effect between vehicles

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2024年第6期238卷 1368-1379页

作者： Zhang, Jimin Wang, Chengping Zhou, Hechao Lu, Haiying Tongji Univ Inst Rail Transit Shanghai Peoples R China CRRC Changchun Rail Bus Co Ltd Jilin Peoples R China Tongji Univ Sch Rail Transit 4800 Caoan Rd Shanghai 201800 Peoples R China

To improve vehicle stability, passenger comfort and road friendliness of the virtual track train (VTT) negotiating curves, a multi-parameter and multi-objective optimization platform combining the VTT dynamics model, Sobal sensitivity analysis, nsga-ii algorithm and k - epsilon optimal selection method is developed. Considering the mutual coupling between vehicles and taking random road roughness as excitation, the VTT dynamics model with 66-DOF is constructed and verified. Design variables and objective functions are defined, and then key design variables are obtained via Sobol sensitivity analysis. The nsga-ii algorithm is used to optimize the key design variables of the VTT, and the k - epsilon optimal selection method is used to select the Pareto solution sets. The results demonstrate that the optimization platform can effectively reduce the number of design variables (from 11 to 6) and improve stability, lateral comfort, vertical comfort and road friendliness, (2.78%, 1.19% and 14.71%, 3.09%, respectively). Also, a multi-parameter and multi-objective optimization platform of the VTT has certain applicability to straight-line conditions and different curve radius conditions. This research provides a feasible solution for the comprehensive performance improvement of the VTT passing through a minor curve. In addition, it also provides a reference for the optimization analysis of multi-marshaling vehicles considering the interaction between vehicles.

关键词： Virtual track train Sobol sensitivity analysis nsga-ii algorithm k epsilon optimal selection method

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An approach for blank dimension design considering energy consumption

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2016年第5-8期87卷 1229-1235页

作者： Xiao, Yongmao Zhang, Hua Jiang, Zhigang Wuhan Univ Sci & Technol Coll Machinery & Automat Wuhan Hunan Peoples R China

A blank dimension is not only a premise of blank design and manufacture, but also plays a significant role to decide the machining process and the energy consumption of the machining process. The design of an appropriate blank dimension is important to ensure efficient energy usage. However, consideration of a workpiece machining process and energy consumption during the machining process in the blank dimension design phase is often neglected. To design a blank dimension scientifically and effectively, this paper proposes an optimization approach for blank dimension design, by considering energy consumption, machine cost, and process time. The three objectives are affected by three variables, cutting depth, feed rate, and cutting speed. The non-dominated sorting genetic algorithm-ii (nsga-ii) algorithm was used to solve multi-objective optimization problem, and blank dimensions could be calculated from the cutting depth of minimum energy consumption and workpiece dimension. The results indicated that the proposed approach is effective in realizing energy savings due to the appropriate blank dimension design. The optimization approach not only offers some insights for designing a new blank dimension, but also provides a theoretical basis for existing blank dimension selection.

关键词： Blank dimension design Energy saving nsga-ii algorithm Machining parameters optimization Sustainable production

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