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Innovative Application of Model-Based Predictive Control for Low-Voltage Power Distribution Grids with Significant Distributed Generation

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ENERGIES 2021年第6期14卷 1773-1773页

作者： Dkhili, Nouha Salas, David Eynard, Julien Thil, Stephane Grieu, Stephane Univ Perpignan PROMES UPR 8521 CNRS Via Domitia F-66100 Perpignan France Univ OHiggins Inst Ciencias Ingn Ohiggins 2841935 Chile

In past decades, the deployment of renewable-energy-based power generators, namely solar photovoltaic (PV) power generators, has been projected to cause a number of new difficulties in planning, monitoring, and control of power distribution grids. In this paper, a control scheme for flexible asset management is proposed with the aim of closing the gap between power supply and demand in a suburban low-voltage power distribution grid with significant penetration of solar PV power generation while respecting the different systems' operational constraints, in addition to the voltage constraints prescribed by the French distribution grid operator (ENEDIS). The premise of the proposed strategy is the use of a model-based predictive control (MPC) scheme. The flexible assets used in the case study are a biogas plant and a water tower. The mixed-integer nonlinear programming (MINLP) setting due to the water tower ON/OFF controller greatly increases the computational complexity of the optimisation problem. Thus, one of the contributions of the paper is a new formulation that solves the MINLP problem as a smooth continuous one without having recourse to relaxation. To determine the most adequate size for the proposed scheme's sliding window, a sensitivity analysis is carried out. Then, results given by the scheme using the previously determined window size are analysed and compared to two reference strategies based on a relaxed problem formulation: a single optimisation yielding a weekly operation planning and a MPC scheme. The proposed problem formulation proves effective in terms of performance and maintenance of acceptable computational complexity. For the chosen sliding window, the control scheme drives the power supply/demand gap down from the initial one up to 38%.

关键词： low-voltage power distribution grids smart grid paradigm distributed generation model-based predictive control flexible asset management mixed-integer nonlinear programming relaxation computational complexity

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Railway Rapid Transit Timetables with Variable and Elastic Demand

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Procedia - Social and Behavioral Sciences 2014年 111卷 538-548页

作者： David Canca Encarnación Algaba Eva Barrena Alejandro Zarzo E.T.S. Ingenieros Universidad de Sevilla Camino de los Descubrimientos s/n 41092. Seville Spain CIRRELT (Centre interuniversitaire de recherche sur les reseaux d’entreprise la logistique et le transport) Montréal. Canada E.T.S.I.I. Universidad Politécnica de Madrid José Gutiérrez Abascal 2 28006. Madrid Spain

This paper focuses on the design of railway timetables considering a variable elastic demand profile along a whole design day. Timetabling is the third stage in the classical hierarchical railway planning process. Most of previous works on this topic consider a uniform demand behavior for short planning intervals. In this paper, we propose a MINLP model for designing non-periodic timetables on a railway corridor where demand is dependent on waiting times. In the elastic demand case, long waiting times lead to a loss of passengers, who may select an alternative transportation mode. The mode choice is modeled using two alternative methods. The first one is based on a sigmoid function and can be used in case of absence of information for competitor modes. In the second one, the mode choice probability is obtained using a Logit model that explicitly considers the existence of a main alternative mode. With the purpose of obtaining optimal departure times, in both cases, a minimization of the loss of passengers is used as objective function. Finally, as illustration, the timetabling MINLP model with both mode choice methods is applied to a real case and computational results are shown.

关键词： Train timetabling elastic demand mixed-integer nonlinear programming

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Location-routing problem with time-dependent demands

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COMPUTERS & INDUSTRIAL ENGINEERING 2021年 151卷 106936-106936页

作者： Yu, Vincent F. Normasari, Nur Mayke Eka Chen, Wei-Hao Natl Taiwan Univ Sci & Technol Dept Ind Management 43Sect 4Keelung Rd Taipei 10607 Taiwan Natl Taiwan Univ Sci & Technol Ctr Cyber Phys Syst Innovat 43Sect 4Keelung Rd Taipei 10607 Taiwan Gadjah Mada Univ Dept Mech & Ind Engn Jl Graf 2 Yogyakarta 55281 Indonesia

This study, by considering the time-dependent demand (TDD) characteristic, investigates the location-routing problem with time-dependent demands (LRPTDD) as an extension of the location-routing problem (LRP). The demand in each customer site is represented by a constant demand rate over a known production period. In the LRPTDD, the locations are selected, and the routes are constructed to pick up all the demands and minimize the total distance. The picked load depends on the vehicle arrival time at the site;thus, the "time-dependency" characteristic of the LRPTDD is based on the vehicle arrival time. A mixed-integer nonlinear programming (MINLP) formulation is presented. A simulated annealing (SA) algorithm for the LRPTDD is developed. The computational study demonstrates the competitiveness of the proposed SA heuristic against other well-known algorithms for LRPs, and most importantly, its effectiveness for the LRPTDD.

关键词： Location-routing problem Time-dependent demand Simulated annealing mixed-integer nonlinear programming

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Synthesis of isothermal fluid-fluid two-phase CSTR networks

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COMPUTERS & CHEMICAL ENGINEERING 1998年第SUPPL.1期22卷 S671-S674页

作者： Esparta, ARJ Obertopp, T Gilles, ED Univ Stuttgart Inst Syst Dynam & Regelungstech D-70550 Stuttgart Germany

A systematic procedure is presented to synthesize isothermal two-phase continuous stirred tank reactor networks. The interaction of reaction and transport phenomena is modelled using the two-film theory and the optimal reactor network is selected from a superstructure by means of a MINLP solver. The proposed synthesis is applied to a pseudo-first order reaction and to the nitration of an aromatic compound. (C) 1998 Elsevier Science Ltd. All rights reserved.

关键词： design/synthesis of processes reactor network two-phase system film theory superstructure mixed-integer nonlinear programming aromatic nitration

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Relaxation approaches for nonlinear sparse optimization problems

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OPTIMIZATION 2024年第10期73卷 3237-3258页

作者： Steffensen, Sonja Rhein Westfal TH Aachen Inst Geometrie & Prakt Math Aachen Germany

In many recent applications, sparse solutions of the optimization problems are favoured over non-sparse solutions with comparable objective values. A standard method to induce the sparsity of the solution is based on the use of the l(0) norm in the objective. However, if the underlying optimization problem is nonlinear, the solution of the nonlinear (sparse) l(0)optimization problem is difficult. Therefore, it is often approximated using the convex l(1)-norm although this can lead to suboptimal solutions for the sparsity of the solution. In this paper, we follow another direction. We present exact reformulations (with respect to the l(0) norm) and their relaxations leading to standard nonlinear but nonconvex programmes. Wediscuss and relate the relations between the different reformulations with repect to the original problem. We accompany our theoretical results by some numerical tests using randomly generated datasets.

关键词： Sparse optimization nonlinear programming complementarity constraints mixed-integer nonlinear programming

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Review of Optimization Methods for Scheduling of Chemical Processes Based on the Time Representation

Review of Optimization Methods for Scheduling of Chemical Pr...

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7th World Congress on Intelligent Control and Automation

作者： Zhou, Xiaohui Chen, Chun Xue, Anke Tian, Minliang Zhejiang Univ Comp Sch Hangzhou 310012 Zhejiang Peoples R China HangZhou Dianzi Univ Inst Informat & Control Hangzhou 310018 Peoples R China

ISBN: (纸本)9781424421138

According to multiproduct/multipurpose batch and continuous processes scheduling, an overview of developments in the chemical processes scheduling is presented. Two scheduling methodologies based on time representation are introduced: one is discrete-time approaches the other is various continuous-time approaches, and the strengths and limitations of these approaches are examined. Also, important characteristics of chemical processes challenging to the scheduling problem are discussed, further research area and possible directions in the production scheduling problem are pointed out.

关键词： Process scheduling Discrete-time model Continuous-time model mixed-integer linear programming mixed-integer nonlinear programming

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Automated patient-robot assignment for a robotic rehabilitation gym: a simplified simulation model

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JOURNAL OF NEUROENGINEERING AND REHABILITATION 2022年第1期19卷 126-126页

作者： Miller, Benjamin A. Adhikari, Bikranta Jiang, Chao Novak, Vesna D. Univ Wyoming Dept Elect & Comp Engn 1000 E Univ Ave Laramie WY 82071 USA Univ Cincinnati Dept Elect Engn & Comp Sci 2600 Clifton Ave Cincinnati OH 45221 USA

Background A robotic rehabilitation gym can be defined as multiple patients training with multiple robots or passive sensorized devices in a group setting. Recent work with such gyms has shown positive rehabilitation outcomes;furthermore, such gyms allow a single therapist to supervise more than one patient, increasing cost-effectiveness. To allow more effective multipatient supervision in future robotic rehabilitation gyms, we propose an automated system that could dynamically assign patients to different robots within a session in order to optimize rehabilitation outcome. Methods As a first step toward implementing a practical patient-robot assignment system, we present a simplified mathematical model of a robotic rehabilitation gym. mixed-integer nonlinear programming algorithms are used to find effective assignment and training solutions for multiple evaluation scenarios involving different numbers of patients and robots (5 patients and 5 robots, 6 patients and 5 robots, 5 patients and 7 robots), different training durations (7 or 12 time steps) and different complexity levels (whether different patients have different skill acquisition curves, whether robots have exit times associated with them). In all cases, the goal is to maximize total skill gain across all patients and skills within a session. Results Analyses of variance across different scenarios show that disjunctive and time-indexed optimization models significantly outperform two baseline schedules: staying on one robot throughout a session and switching robots halfway through a session. The disjunctive model results in higher skill gain than the time-indexed model in the given scenarios, and the optimization duration increases as the number of patients, robots and time steps increases. Additionally, we discuss how different model simplifications (e.g., perfectly known and predictable patient skill level) could be addressed in the future and how such software may eventually be used in practice. Conclu

关键词： Rehabilitation robotics Rehabilitation gym Group rehabilitation Optimization Mathematical modeling Task scheduling mixed-integer nonlinear programming

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Cyclic Cleaning Scheduling of Industrial Boiler Based on Steepest Descent Approximate Linear programming

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IFAC Proceedings Volumes 2013年第13期46卷 478-483页

作者： Yan Zhaoyang Ma Xin Gao Dong Liu Pingping Zhang Beike College of Information Science and Technology Beijing University of Chemical Technology Beijing China

In this paper, the planning for the multi-period cleaning of an industrial boiler is formulated as a mixed-integer nonlinear program (MINLP). The objective function accounted for both the cost of fuel consumption and boiler cleaning & maintenance costs. And a subsection method was proposed for solving the MINLP problem using the steepest descent approximate linear programming (SDALP), which exhibits the advantages of the approximate linear programming (ALP) algorithm, such as easy implementation and convenient solution, and then introduces the principle of purposeful search and rapid convergence via the steepest descent method. This new method can eliminate the negative effect of the subjective step restriction and reduction coefficient, improve the convergence speed, and enhance the solution accuracy. The computation time for the method was proportional to the number of periods, and global solution of the MINLP was guaranteed. At last, the effectiveness of the proposed method was illustrated with an example.

关键词： cyclic cleaning of industrial boiler scheduling algorithm steepest descent approximate linear programming mixed-integer nonlinear programming

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Simultaneous Synthesis Of Heat Exchanger Network With Stream Split Based On Quantum-behaved Particle Swarm Optimization Algorithm 33

Simultaneous Synthesis Of Heat Exchanger Network With Stream...

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33rd Chinese Control Conference (CCC)

作者： Ye Zhen Cheng Qian Zhi Yuan Luo Na Zhao Liang E China Univ Sci & Technol Key Lab Adv Control & Optimizat Chem Proc Minist Educ Shanghai 200237 Peoples R China

ISBN: (纸本)9781479947249

Simultaneous synthesis problem of heat exchanger network is formulated as a mixed-integer nonlinear programming model. Limited by the Characteristic of the nonlinearity, the convexity and the discontinuity of the model, the classical optimization algorithms which is used to solving the model are easy to fall into local minima. Based on the superstructure model with non-isothermal mixing of split stream, a two-level approach combined with quantum-behaved particle swarm optimization (QPSO) algorithm is proposed to find the optimum structure with a minimum annual cost. In the upper level, QPSO is utilized to generate the structure of the network, while in the lower level, split-stream fractions and heat load of exchangers are optimized by QPSO. Benchmark problems are solved and results show that the two level quantum particle swarm algorithm effectively avoids falling into local minima and it is feasible and effective for heat exchanger network problems.

关键词： Heat Exchanger Network Synthesis Quantum-behaved Particle Swarm Optimization Algorithm mixed-integer nonlinear programming

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Solving reliability redundancy allocation problems with orthogonal simplified swarm optimization

Solving reliability redundancy allocation problems with orth...

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International Joint Conference on Neural Networks

作者： Wei-Chang Yeh Vera Yuk Ying Chung Yun-Zhi Jiang Xiangjian He Department of Industrial Engineering and Engineering Managemen National Tsing Hua University Hsinchu 300 Taiwan School of Information Technology University of Sydney NSW 2006 Australia School of Software Jiangxi Agricultural University Nanchang China 330045 School of Software Engineering South China University of Technology Guangzhou China 510006 Computer Vision and Recognition Laboratory Research Centre for Innovation in IT Services and Applications (iNEXT) University of Technology Sydney (UTS) PO Box 123 Broadway NSW 2007 Australia

ISBN: (纸本)9781479919611

This study applies a penalty guided strategy and the orthogonal array test (OA) based on the Simplified Swarm Optimization algorithm (SSO) to solve the reliability redundancy allocation problems (RRAP) in the series system, the series-parallel system, the complex (bridge) system, and the overspeed protection of gas turbine system. For several decades, the RRAP has been one of the most well known techniques. The maximization of system reliability, the number of redundant components, and the reliability of corresponding components in each subsystem have to be decided simultaneously with nonlinear constraints, acting as one difficulty for the use of the RRAP. In other words, the objective function of the RRAP is the mixed-integer programming problem with the nonlinear constraints. The RRAP is of the class of NP-hard. Hence, in this paper, the SSO algorithm is proposed to solve the RRAP and improve computation efficiency for these NP-hard problems. There are four RRAP problems used to illustrate the applicability and the effectiveness of the SSO. The experimental results are compared with previously developed algorithms in literature. Moreover, the maximum-possible-improvement (MPI) is used to measure the amount of improvement of the solution found by the SSO to the previous solutions. According to the results, the system reliabilities obtained by the proposed SSO for the four RRAP problems are as well as or better than the previously best-known solutions.

关键词： Reliability Redundancy allocation problem RRAP Simplified Swarm Optimization algorithm SSO mixed-integer nonlinear programming

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