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sequential quadratic programming (SQP) Based Optimal Power Flow Methodologies for Electric Distribution System With High Penetration of DERs

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2024年第3期60卷 4810-4820页

作者： Hasan, Md Shamim Chowdhury, Md Mahmud-Ul-Tarik Kamalasadan, Sukumar Univ North Carolina Charlotte Power Energy & Intelligent Syst Lab Charlotte NC 28223 USA

This article proposes a centralized and distributed model based on nonlinear programming (NLP) for optimal power flow (OPF) analysis in power distribution networks, solved with the sequential quadratic programming (SQP) algorithm. The paper proposes the method and illustrates the necessary conditions for the global optimality of the solution. The main advantages of the methods are obtaining global optimal solutions in less than a minute (for more than 2000 nodes with high penetration of DERs) without approximations and relaxations in power flow equations and improving scalability by reducing the number of iterations significantly for both centralized and distributed OPF. The OPF analysis models have been simulated in several standard distribution networks with a wide range of DER penetration. The solution from the proposed model is compared with an interior point method (IPM) based NLP algorithm (NLP-IPM) and second-order conic programming (SOCP) algorithm-based convex OPF analysis method. The analysis confirms the global optimality of the proposed algorithm and demonstrates superior convergence and accuracy compared to other OPF methods.

关键词： Mathematical models Load flow Voltage control Voltage Computational modeling Reactive power Power systems Bus injection model distributed energy resources interior point method optimal power flow (OPF) second order conic programming sequential quadratic programming

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sequential quadratic programming-based non-cooperative target distributed hybrid processing optimization method

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Journal of Systems Engineering and Electronics 2023年第1期34卷 129-140页

作者： SONG Xiaocheng WANG Jiangtao WANG Jun SUN Liang FENG Yanghe LI Zhi Beijing Institute of Electronic Engineering China Aerospace Science and Industry Corporation LimitedBeijing 100039China School of Intelligence Science and Technology University of Science and Technology BeijingBeijing 100083China Institute of Artificial Intelligence University of Science and Technology BeijingBeijing 100083China School of Systems Engineering National University of Defense TechnologyChangsha 410073China

The distributed hybrid processing optimization problem of non-cooperative targets is an important research direction for future networked air-defense and anti-missile firepower systems. In this paper, the air-defense anti-missile targets defense problem is abstracted as a nonconvex constrained combinatorial optimization problem with the optimization objective of maximizing the degree of contribution of the processing scheme to non-cooperative targets, and the constraints mainly consider geographical conditions and anti-missile equipment resources. The grid discretization concept is used to partition the defense area into network nodes, and the overall defense strategy scheme is described as a nonlinear programming problem to solve the minimum defense cost within the maximum defense capability of the defense system network. In the solution of the minimum defense cost problem, the processing scheme, equipment coverage capability, constraints and node cost requirements are characterized, then a nonlinear mathematical model of the non-cooperative target distributed hybrid processing optimization problem is established, and a local optimal solution based on the sequential quadratic programming algorithm is constructed, and the optimal firepower processing scheme is given by using the sequential quadratic programming method containing non-convex quadratic equations and inequality constraints. Finally, the effectiveness of the proposed method is verified by simulation examples.

关键词： non-cooperative target distributed hybrid processing multiple constraint minimum defense cost sequential quadratic programming

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An improved sequential quadratic programming method for identifying the total heat exchange factor of reheating furnace

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INTERNATIONAL JOURNAL OF THERMAL SCIENCES 2024年 204卷

作者： Ji, Wenchao Li, Guojun Wei, Linyang Yi, Zhi Northeastern Univ Sch Met Shenyang 110819 Peoples R China Liaoning Engn Res Ctr Proc Ind Energy Saving & Low Shenyang 110819 Peoples R China

Accurate identification of the total heat exchange factor (THEF), which serves as the foundation for online control data in the reheating furnace, holds significant importance for enhancing the digitization and intelligence level of the furnace, mitigating environmental pollution, and improving the economic performance of enterprises. For this purpose, based on the theory of inverse heat transfer problem, a solver combining sequential quadratic programming and Broyden Combined Method (SQPBC) was developed to accurately identify highdimensional and strongly nonlinear THEF in the reheating furnace. Integrating the efficient Broyden Combined Method (BCM) into sequential quadratic programming (SQP) enables the rapid and accurate estimation of the Jacobian matrix to effectively enhance computational speed without compromising accuracy. Experimental data has been employed to validate the accuracy of the inversion results. The performance of SQPBC has been comprehensively analyzed through a series of numerical experiments, with a particular focus on investigating the impact of sampling frequency and sensor location on the inversion results. The findings reveal that after reducing the sampling period to 2 min, further decreasing the sampling period has a minor effect on the average relative error of the identification results;the closer the measurement points are to the surface of the slab, the more accurate the identification of THEF on the slab's surface.

关键词： Total heat exchange factor sequential quadratic programming Broyden combined method Reheating furnace Inversed heat conduction problem bottom THEFs points

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Hybrid improved Sparrow Search Algorithm and sequential quadratic programming for solving the cost minimization of a hybrid photovoltaic, diesel generator, and battery energy storage system

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ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS 2025年第1期47卷 6237-6253页

作者： Tian, Hao Wang, Keqing Yu, Bing Song, Changpo Jermsittiparsert, Kittisak Nanjing Univ Informat Sci & Technol Binjiang Coll Nanjing Jiangsu Peoples R China Tsinghua Univ Dept Elect Engn State Key Lab Control & Simulat Power Syst & Gener Beijing Peoples R China Duy Tan Univ Inst Res & Dev Da Nang 550000 Vietnam Duy Tan Univ Fac Humanities & Social Sci Da Nang Vietnam Henan Univ Econ & Law MBA Sch Henan Peoples R China

In this paper, a hybrid photovoltaic/battery/diesel generator power generation system is designed and optimized to power a network of a remote village in China. The purpose of the system designed here is to lessen the fuel costs of the system dependent on the load demand and some constraints. Therefore, the idea comprises an optimization problem that is solved here based on a new optimization policy by an Improved design of Sparrow Search Algorithm (imSSA) and the sequential quadratic programming (SQP). The results of the proposed method are analyzed in different seasons and also on weekdays and weekends to show their effect on the operational cost of the PV/Diesel BESS system. Final results indicate that in both winter and summer, the weekday costs are lesser than weekend fuel costs. Furthermore, the summer fuel cost is lesser than the winter fuel costs which is because of lesser demand in summer and the higher levels of summer radiation imply less usage of auxiliary origins. The results show that at the weekends cost more than the weekday. For instance, for the proposed mode, the winter weekends and the weekdays' costs are US$12.1 and US$10.2, respectively, or the summer weekends and the weekdays' costs are US$7.3 andUS$5.7, respectively.

关键词： Photovoltaic diesel generator battery energy storage system sequential quadratic programming improved sparrow search algorithm

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FULLY STOCHASTIC TRUST-REGION sequential quadratic programming FOR EQUALITY-CONSTRAINED OPTIMIZATION PROBLEMS

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SIAM JOURNAL ON OPTIMIZATION 2024年第2期34卷 2007-2037页

作者： Fang, Yuchen Na, Sen Mahoney, Michael W. Kolar, Mladen Univ Chicago Comm Comp & Appl Math Chicago IL 60637 USA Univ Calif Berkeley Int Comp Sci Inst Berkeley CA 94720 USA Univ Calif Berkeley Dept Stat Berkeley CA 94720 USA Univ Calif Berkeley Lawrence Berkeley Natl Lab Int Comp Sci Inst Berkeley CA 94720 USA Univ Calif Berkeley Dept Stat Berkeley CA 94720 USA Univ Southern Calif Marshall Sch Business Los Angeles CA 90089 USA

We propose a trust-region stochastic sequential quadratic programming algorithm (TR-StoSQP) to solve nonlinear optimization problems with stochastic objectives and deterministic equality constraints. We consider a fully stochastic setting, where at each step a single sample is generated to estimate the objective gradient. The algorithm adaptively selects the trust-region radius and, compared to the existing line-search StoSQP schemes, allows us to utilize indefinite Hessian matrices (i.e., Hessians without modification) in SQP subproblems. As a trust-region method for constrained optimization, our algorithm must address an infeasibility issue---the linearized equality constraints and trust-region constraints may lead to infeasible SQP subproblems. In this regard, we propose an adaptive relaxation technique to compute the trial step, consisting of a normal step and a tangential step. To control the lengths of these two steps while ensuring a scale-invariant property, we adaptively decompose the trust-region radius into two segments, based on the proportions of the rescaled feasibility and optimality residuals to the rescaled full KKT residual. The normal step has a closed form, while the tangential step is obtained by solving a trust-region subproblem, to which a solution ensuring the Cauchy reduction is sufficient for our study. We establish a global almost sure convergence guarantee for TR-StoSQP and illustrate its empirical performance on both a subset of problems in the CUTEst test set and constrained logistic regression problems using data from the LIBSVM collection.

关键词： constrained stochastic optimization nonlinear optimization trust-region method sequential quadratic programming

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Toolpath optimization based on sequential quadratic programming for five-axis flat-end milling with hybrid robots

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JOURNAL OF MANUFACTURING PROCESSES 2025年 141卷 1619-1630页

作者： Zhang, Shiqi Ding, Ye Shanghai Jiao Tong Univ Sch Mech Engn State Key Lab Mech Syst & Vibrat Shanghai 200240 Peoples R China

Optimal toolpath generation is crucial for improving machining efficiency and surface finish quality. However, this task becomes challenging in the context of robotic flat-end milling, where both the contact geometry of cutters on free-form surfaces and robot kinematics need to be addressed. This paper introduces a toolpath optimization framework for flat-end milling with five-axis hybrid robots. The proposed method integrates joint path smoothness and machining width into the objective function, and it simultaneously optimizes the feed direction and tool orientation of the flat-end cutter by including feed angles, inclination angles, and tilt angles as optimization variables. The analytical gradient of the optimization problem is derived by applying differential geometry of surfaces. Based on this gradient derivation, sequential quadratic programming is employed to efficiently solve the original nonconvex problem, resulting in an optimized toolpath that exhibits both improved path smoothness and increased machining width. Feedrate scheduling of the toolpath, which considers workspace and joint space constraints, demonstrates that machining time is reduced for hybrid robots characterized by highly nonlinear kinematics. Simulations and experimental validations further confirm the method's capability to enhance machining efficiency.

关键词： Toolpath optimization Flat-end milling sequential quadratic programming Hybrid robot

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Adaptive fractional-order nonsingular terminal sliding mode control and sequential quadratic programming torque distribution for lateral stability of FWID-EVs with actuator constraints

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ISA TRANSACTIONS 2024年 150卷 208-222页

作者： Hua, Xingqi Wong, Pak Kin Zhao, Jing Xie, Zhengchao Univ Macau Dept Electromech Engn Taipa 999078 Macau Sar Peoples R China South China Univ Technol Sch Mech & Automot Engn Guangzhou 510641 Peoples R China

This paper proposes a novel sliding mode control (SMC) algorithm for direct yaw moment control of four-wheel independent drive electric vehicles (FWID-EVs). The algorithm integrates adaptive law theory, fractional -order theory, and nonsingular terminal sliding mode reaching law theory to reduce chattering, handle uncertainty, and avoid singularities in the SMC system. A sequential quadratic programming (SQP) method is also proposed to optimize the yaw moment distribution under actuator constraints. The performance of the proposed algorithm is evaluated by a hardware -in -the -loop test with two driving maneuvers and compared with two existing SMC-based schemes together with the cases with the change of vehicle parameters and disturbances. The results demonstrate that the proposed algorithm can eliminate chattering and achieve the best lateral stability as compared with the existing schemes.

关键词： Sliding mode control (SMC) Direct yaw moment control Fractional-order sequential quadratic programming

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MHD slip flow through nanofluids for thermal energy storage in solar collectors using radiation and conductivity effects: A novel design sequential quadratic programming-based neuro-evolutionary approach

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MODERN PHYSICS LETTERS B 2025年第22期39卷

作者： Butt, Zeeshan Ikram Ahmad, Iftikhar Raja, Muhammad Asif Zahoor Hussain, Syed Ibrar Ilyas, Hira Shoaib, Muhammad Univ Gujrat Dept Math Gujrat 50700 Pakistan Natl Yunlin Univ Sci & Technol Future Technol Res Ctr 123 Univ RdSect 3 Yunlin 64002 Taiwan Univ Palermo Dept Math & Comp Sci Via Archirafi 34 I-90123 Palermo Italy Univ Houston Dept Math Houston TX 77004 USA Univ Chenab Dept Phys Sci Gujrat 50700 Pakistan Yuan Ze Univ Artificial Intelligence Cross Domain Innovat Appli Taoyuan Taiwan

In this research, a novel design stochastic numerical technique is presented to investigate the unsteady form magnetohydrodynamic (MHD) slip flow along the boundary layer to analyze the transportation and heat transfer in a solar collector through nano liquids which is a revolution in the field of neurocomputing. Thermal conductivity in variable form is dependent on temperature and wall slips are assumed over the boundary. For mathematical modeling, the solar collector is assumed in the form of a nonlinear stretching sheet and a quite new artificial neural networks (ANNs) based approach is used to solve the current problem in which inverse multiquadric radial basis (IMRB) kernel is sandwiched between a global search solver named genetic algorithms (GAs) and a highly effective local solver named sequential quadratic programming (SQP) i.e. IMRB-GASQP solver. The governing boundary value problem is altered in the form of a system of nonlinear ordinary differential equations (ODEs) through the utilization of similarity transformation and then the obtained system of ODEs is solved using IMRB-GASQP solver by altering the values of distinguished parameters involved in it to observe the fluctuation in the velocity and temperature profiles of nanofluid. The obtained results are effectively compared with the reference solutions using the Adams numerical technique in graphical and tabulated form. An exhaustive error analysis using performance operators is presented while the efficacy of the designed solver using various statistical operators is also part of this research.

关键词： Magnetohydrodynamic artificial neural networks genetic algorithms sequential quadratic programming inverse multiquadric radial basis function nanofluid heat transfer

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Optimizing heat source distribution in sintering molds: Integrating response surface model with sequential quadratic programming

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HELIYON 2024年第8期10卷 e29376页

作者： Liu, Sanli Chen, Min Zhu, Nan Xiang, Zhouyi Huang, Songhua Zhang, Shunqi Xian Jiaotong Liverpool Univ Sch Adv Technol Suzhou Peoples R China ZINSIGHT Technol Shanghai Co Ltd Shanghai Peoples R China Shanghai Univ Sch Mechatron Engn & Automat Shanghai Peoples R China

The sintering mold imposes strict requirements for temperature uniformity. The mold geometric parameters and the power configuration of heating elements exert substantial influence. In this paper, we introduce an optimization approach that combines response surface models with the sequential quadratic programming algorithm to optimize the geometric parameters and heating power configuration of a heating system for sintering mold. The response surface models of the maximum temperature difference, maximum temperature, and minimum temperature of the sintering area are constructed utilizing the central composite design method. The model ' s reliability is rigorously confirmed through variance analysis, residual analysis, and generalization capability validation. The models demonstrate remarkable predictive accuracy within the design space. A nonlinear constrained optimization model is established based on the response surface models, and the optimal parameters are obtained after 9 iterations using the sequential quadratic programming algorithm. Under the optimal parameters, the maximum temperature difference is maintained at less than 5 degrees C, confirming exceptional temperature uniformity. We conduct parameter analysis based on standardized effects to determine the main influencing factors of temperature uniformity, revealing that the distance between adjacent heating rods and the power density of the inner heating rods exert significant influence. Enhanced temperature uniformity can be achieved by adopting a larger distance between heating rods and configuring the power density of the heating rods to a relatively modest level. This work introduces a practical approach to optimize the heating systems for sintering molds, with potential applications in various industrial mold optimization.

关键词： Temperature uniformity Sintering mold Response surface methodology sequential quadratic programming Optimal design

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Seismic Design of Structures by sequential quadratic programming with Trust Region Strategy and Endurance Time Method

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KSCE JOURNAL OF CIVIL ENGINEERING 2024年第11期28卷 5104-5115页

作者： Feng, Yue Hainan Univ Dept Civil Engn & Architecture Hainan 570228 Peoples R China

The optimal design of structures subjected to seismic loading poses significant challenges due to the presence of high nonlinearity and computational complexity. To address these challenges, this paper presents a novel methodology that combines sequential quadratic programming with Trust-Region strategy (SQP-TR) and Endurance Time Method (ETM). SQP-TR is initially presented as a numerical optimization approach to address optimization problems by linearizing the constraints and approximating the objective function with Taylor expansion, as well as employing the filter method and trust region strategy to ensure convergence and feasibility. A five-story linear frame validates its effectiveness and demonstrates promising outcomes. ETM is successfully implemented as a seismic analysis approach to perform nonlinear time history analyses in order to capture the dynamic input feature of the seismic load and evaluate the nonlinear dynamic behaviors of structures. Its practical application is demonstrated by a nine-story structure with nonlinearity, which shows satisfactory results. Finally, the proposed methodology is applied to optimize a twelve-story three-Dimensional (3D) Reinforced Concrete (RC) nonlinear building under seismic load, and the results demonstrate that the method can accomplish optimal seismic design with high accuracy and efficiency.

关键词： Optimization Seismic sequential quadratic programming Trust region Endurance time analysis

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