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2021 International Conference on Intelligent Computing, Automation and Systems, ICICAS 2021

作者： Huazhen, Cao Yabin, Chen Yu, Sui Bin, Wei Power System Planning Research Center of Guangdong Power Grid Co. Ltd. Guangzhou510030 China

ISBN: (纸本)9781665428101

Smart distribution grid can support the national ambitious goal of 'carbon peak and carbon neutral' and the development strategy of building a new power system with new energy as the mainstay, and is also an important material basis for economic and social development. The application of smart distribution grid technology is an important technical means to realize the transformation of distribution grid intelligence. This paper constructs a smart distribution grid construction target system based on the demand of distribution grid intelligence enhancement, and proposes a method to develop a differentiated construction target set by combining the assessment of target importance and satisfaction. Further, taking into account multiple attributes such as technology development maturity, grid construction adaptability and application value of technologies, a combined evaluation method is used to score smart distribution network technologies comprehensively. Considering the goal-oriented variability and complexity of technology types, the optimal combination of technology solutions is the goal, and a mixed integer nonlinear programming model for the differentiated configuration of smart distribution network technology solutions is constructed. Finally, a certain distribution network construction scenario is used for analysis to verify the feasibility and validity of the model. © 2021 IEEE.

关键词： nonlinear programming

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Method for Calculating the Air Pollution Emission Quotas 1

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20th International Conference on Mathematical Optimization Theory and Operations Research , MOTOR 2021

作者： Krutikov, Vladimir Bykov, Anatoly Tovbis, Elena Kazakovtsev, Lev Kemerovo State University 6 Krasnaya Street Kemerovo650043 Russia Institute of Computational Technologies SB RAS 21 Rukavishnikov Street Kemerovo650025 Russia Reshetnev Siberian State University of Science and Technology prosp. Krasnoyarskiy Rabochiy 31 Krasnoyarsk660031 Russia Siberian Federal University 79 Svobodny pr. Krasnoyarsk660041 Russia

ISBN: (数字)9783030864330

ISBN: (纸本)9783030864323

The main purpose of quotas is to limit emissions for facilities that have a negative impact on the environment. When calculating emission quotas, it is necessary to solve a nonlinear programming problem with a nonlinear objective function and linear constraints. Variables of the problem are emission reduction coefficients for objects that have a negative impact on the environment. Constraints of the problem are determined by the admissibility of the emission contributions from objects to the concentration of pollutants in the air at the locations of quotas. As a rule, the number of constraints of this problem is significantly less than the number of variables (the problem can include up to 10,000 variables and 1,000 linear constraints). In this regard, it seems relevant to use the theory of duality for the purposes of substantive analysis and simplification of computational methods for problem solving. We suggest the transition from primal to dual nonlinear programming. As a result, we gain a nonsmooth problem of unconstrained minimization of a much smaller order, and the solution can be obtained by effective subgradient minimization methods with an alteration in the space metric. We propose an effective method for solving the problem of emission quotas to be determined, and confirm its efficiency by a computational experiment on both test and applied data. The explicit form of the dependence of primal and dual variables is useful for the analysis of the solution and the selection of the object priority parameters by an expert. © 2021, Springer Nature Switzerland AG.

关键词： nonlinear programming

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Multiple underwater magnetic targets location method based on neural network 4

Multiple underwater magnetic targets location method based o...

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4th International Conference on Advanced Electronic Materials, Computers and Software Engineering, AEMCSE 2021

作者： Liang, Kang Xie, Hongtu Wang, Guoqian Sun Yat-Sen University School of Electronics and Communication Engineering Guangzhou China Sun Yat-sen University Sun Yat-sen Memorial Hospital Guangzhou China

ISBN: (纸本)9781665415965

The problem of locating magnetic target is the solution of nonlinear programming problems. The biggest characteristic of the problem is that the calculation process of the objective function is quite complicated. With the increase of the number of magnetic targets, the more unknowns need to be solved, which increase a lot of calculation. However, the speed of the objective function calculation could have a great influence on the real-time performance of the magnetic target location. Thus, this paper proposes an multiple underwater magnetic targets location method based on the neural network, which can get the position coordinates of the magnetic target without solving the objective function. Finally, the experimental results show that the magnetic target position obtained by this method has high accuracy and good real-time performance. © 2021 IEEE.

关键词： nonlinear programming

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Sigmoid Function Optimization for Path Following Control with Obstacle Avoidance of an Autonomous Truck-trailer 7

Sigmoid Function Optimization for Path Following Control wit...

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7th International Conference on Instrumentation, Control, and Automation, ICA 2021

作者： Asrofudin, Bani Widyotriatmo, Augie Siregar, Parsaulian I Apeco Putra, Dimas Institut Teknologi Bandung Instrumentation and Control Program Bandung Indonesia Engineering Physics Program Institut Teknologi Bandung Bandung Indonesia

ISBN: (纸本)9781665432955

In this study, an obstacle avoidance maneuver with sigmoid function optimization is applied on the path following control of the Autonomous truck-trailer. The accumulation of trailers and traffic density become obstacles in the lanes traversed by trailer trucks. A control design is needed that can perform obstacle avoidance actions in the form of optimal path changes. In the application of a path-following autonomous truck-trailer, the avoidance path reference must be dynamically adjusted to bring the system to a lane change. The optimization of the sigmoid function was proposed to obtain the optimal obstacle avoidance path reference based on the traction speed and steering angle. The MATLAB Fmincon nonlinear programming function is used to get the optimal solution which affects the concavity and distance of the turning path to the obstacle. The optimal turning path is integrated with the Lyapunov stability-based path follower control. This is intended to obtain a global asymptotic stable condition both under normal conditions and to avoid obstacles. Simulation is done by comparing the path pattern of the optimized and unoptimized sigmoid curves. The simulation results show the optimal turn path based on the mean of orientation angle and traction velocity in addition to the value of the performance index. © 2021 IEEE.

关键词： nonlinear programming

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Optimization of Opening Scheme of ETC/MTC Toll Lane Based on Cost and Benefit Analysis 3

Optimization of Opening Scheme of ETC/MTC Toll Lane Based on...

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2020 3rd International Symposium on Traffic Transportation and Civil Architecture, ISTTCA 2020

作者： Zhang, Hao Cheng, Cheng Zhang, Changjian He, Jie Xu, Yang Chen, Yikai Hong, Qiong School of Transportation Southeast University Nanjing Jiangsu211189 China School of Traffic Engineering Huaiyin Institute of Technology Huaian Jiangsu223003 China School of Automotive and Transportation Engineering Hefei University of Technology Hefei Anhui230009 China Business School Jiangsu Vocational College of Electronics and Information Huaian Jiangsu223003 China

In recent years, with the popularization of electronic toll collection systems (ETC), expressway toll stations in China have developed into a mixed toll form jointly deployed by ETC toll lanes and MTC toll lanes, presenting a development trend based on ETC toll lanes. Since the toll collection system has the important function of "credit repayment", the relationship between operation benefit and cost will become an important indicator for measuring the toll station system. Taking the minimum cost and the maximum benefit of the toll station under normal operating condition as the optimization goals, a multi-objective nonlinear optimization model is established within the seek for balance between cost and benefit, so as to obtain an open plan with better toll lanes. The Nanjing-Hangzhou toll station is used as an example to verify the model. Furthermore, based on the trend of the future traffic flow and the increase in the proportion of ETC vehicles, the distribution law of the optimal opening schemes of the toll lane under different traffic volumes and different traffic flow structures is analyzed, which provides experience support for the construction and operation of toll stations in the future. © Published under licence by IOP Publishing Ltd.

关键词： nonlinear programming

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A set-theoretic model predictive control approach for transient stability in smart grid

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IET CONTROL THEORY AND APPLICATIONS 2020年第5期14卷 700-707页

作者： Bagherzadeh, Maryam Lucia, Walter Concordia Univ Elect & Comp ECE Dept Montreal PQ Canada Concordia Univ CIISE Montreal PQ Canada

In this study, the authors deal with the transient stability control problem in smart grids. They consider an operative scenario where a physical fault or a cyber-attack produces an impulsive perturbation in the state of the system, and a controller must be designed to robustly recover, in a finite-time, transient stability despite initial perturbation and uncertainties. The authors propose a solution that is based on a low-demanding model predictive control (MPC) idea that is known as set-theoretic MPC. They show that such a controller can be used as an emergency controller to deal with the considered scenario. A peculiar capability of the proposed solution is that the worst-case time to transient stability can be apriori established. Moreover, most of the required computations are moved into an off-line phase leaving into the on-line phase a simple and computationally affordable convex optimisation problem. Finally, the authors have conducted an extensive simulation campaign to testify the validity of the proposed solution experimentally and to investigate its performance when contrasted with a competitor scheme.

关键词： optimisation power system transient stability power distribution reliability concave programming convex programming nonlinear programming power generation dispatch set theory predictive control power system control smart power grids set-theoretic model predictive control approach smart grid transient stability control problem operative scenario impulsive perturbation initial perturbation uncertainties model predictive control idea set-theoretic MPC emergency controller considered scenario worst-case time simple convex optimisation problem computationally affordable convex optimisation problem

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Research on Reservoir Application Allocation based on nonlinear Prediction and Genetic Algorithm

International Core Journal of Engineering

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International Core Journal of Engineering 2022年第7期8卷 295-302页

作者： Zuhan Wang

Aiming at the problem of reservoir supply distribution in the southwestern United States this year, this paper aims at the water distribution between Glenn Canyon Dam (Lake Powell) and Hoover Dam (Lake Meade). A nonlinear programming model is established to optimize the pumping allocation of each dam, and the model is upgraded and extended to multiple scenarios to closely coordinate the operation of the two dams. First of all, based on the nonlinear programming model, the geomorphological environment, policy changes, time lapse and other factors that may affect the water demand and electricity consumption of the five states are quantified and analyzed, and the water consumption and electricity consumption data of the five states are obtained. Then a nonlinear programming model is established to maximize benefits while meeting the water and electricity needs of the five states, and the multivariate function optimization flow chart is derived by using genetic algorithm, and finally the optimal solution of the water level of the two lakes after pumping is obtained. And finally carry on the sensitivity to the change of the surrounding conditions. The sensitivity analysis results of the model show that the model used in this paper has the characteristics of high accuracy, good stability and wide application range, and has important application value.

关键词： Water Scheduling nonlinear programming Genetic Algorithms First Law of Thermodynamics

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Research on Orderly Charging Control Strategy in Demond Response 4

Research on Orderly Charging Control Strategy in Demond Resp...

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4th IEEE International Conference on Renewable Energy and Power Engineering, REPE 2021

作者： Peng, Xiaofeng Yang, Ye Meng, Da Cheng, Han Dai, Yinping Zhang, Xiaoqing Zhong, Yulu State Grid EV Service Energy Department Beijing China Chengdu Huamod Energy Technology Co Ltd RD Department Chengdu China Strategic Development Chengdu Huamod Energy Technology Co Ltd Chengdu China

ISBN: (纸本)9781665443715

The increasing amount of electric vehicle has brought threat on the distribution network reliability, but it also provides great load flexibility opportunities. With appropriate guidance, electric vehicle charging loads can be an important demand response resource. The charging of electric vehicles for demand response can be formulized as a nonlinear multiple-objective optimization problem. This article studies mathematical optimization models for orderly charging in different demand response scenarios and proposes a strategy of orderly charging for demand response. The effectiveness of the ordered charging model and solution method are demonstrated using both simulation data and actual charging data. © 2021 IEEE.

关键词： nonlinear programming

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Design and optimization of a novel 2-DOF synchronous linear rotary drive 21

Design and optimization of a novel 2-DOF synchronous linear ...

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21st International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2021

作者： Denkena, Berend Bergmann, Benjamin Ahlborn, Patrick Fuchs, Jonathan Leibniz University Hanover Germany

ISBN: (纸本)9780995775190

Achieving movements of machine tool components in 2 degrees of freedom (DOF) usually requires a serial arrangement of at least two drives. The serial kinematic reduces the stiffness at the tool center point (TCP) and leads to an accumulation of the positioning and measuring errors of each drive. To achieve a high level of precision, a novel 2-DOF drive without serial kinematics is being developed. The drive consists of a static primary part and a secondary part with a linear and a rotary DOF. The secondary part is able to move in both DOFs independently. For this purpose, two separate windings which generate rotation and translation forces are stacked in the primary part. To generate magnetic forces in both DOFs, the secondary part is equipped with a checkerboard-like array of permanent magnets. The coupling between both windings and thus the induction of forces can be bypassed. This means that the windings can be controlled independently. The combination of the primary and secondary parts reduces the drive length. In comparison to current linear rotary drives, the novel drive is more compact and has a higher performance. In this paper, the motor geometry is optimized by parametric FEM-simulations. The goal of said optimization is to improve the torque and feed force as well as to reduce power losses and disturbing forces. For this purpose, a parametric model of the drive is developed. The simulations are carried out in ANSYS Maxwell and are run in 2D to save computing time. A genetic algorithm and sequential nonlinear programming are used to optimize the magnet height, pole-to-pole coverage, tooth angle and slot height. The simplifying assumptions of the 2D-simulation are compared to an additionally performed 3D-simulation. The result is an optimized drive with 8% higher performance and 65% less power loss compared to the non-optimized initial geometry. © 2021 Proceedings of the 21st International Conference of the European Society for Precision Engineering and Nan

关键词： nonlinear programming

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Lunar campaign optimization using machine learning

Lunar campaign optimization using machine learning

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Accelerating Space Commerce, Exploration, and New Discovery conference, ASCEND 2021

作者： Bartkiewicz, Jacob Haws, Terry Fuller, Michael Northrop Grumman Space Systems Brigham CityUT84302 United States

ISBN: (数字)9781624106125

ISBN: (纸本)9781624106125

The lunar campaign optimizer provided a very complex and non-linear optimization problem. Gradient based optimizers and other numerical optimizers failed to optimize this problem effectively. A novel approach using machine learning was used to overcome this issue. Machine learning was used to train a surrogate model of the objective function which could then be used to predict the minimum. Results showed high optimality and reflected real world solutions. © 2021, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： nonlinear programming

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