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Robust energy-efficient train speed profile optimization in a scenario-based position-time-speed network

Frontiers of Engineering Management 2021年第4期8卷 595-614页

作者： Yu CHENG Jiateng YIN Lixing YANG State Key Laboratory of Rail Traffic Control&Safety Beijing Jiaotong UniversityBeijing 100044China E-mail:jiatyin@***

Train speed profile optimization is an efficient approach to reducing energy consumption in urban rail transit *** from most existing studies that assume deterministic parameters as model inputs,this paper proposes a robust energy-efficient train speed profile optimization approach by considering the uncertainty of train modeling ***,we first construct a scenario-based position-time-speed(PTS)network by considering resistance parameters as discrete scenariobased random ***,a percentile reliability model is proposed to generate a robust train speed profile,by which the scenario-based energy consumption is less than the model objective value at a confidence *** solve the model efficiently,we present several algorithms to eliminate the infeasible nodes and arcs in the PTS network and propose a model reformulation strategy to transform the original model into an equivalent linear programming ***,on the basis of our field test data collected in Beijing metro Yizhuang line,a series of experiments are conducted to verify the effectiveness of the model and analyze the influences of parameter uncertainties on the generated train speed profile.

关键词： robust train speed profile percentile reliability model scenario-based position-time-speed network mixed-integer programming

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Real-Time Control of an Electric Vehicle Charging Station While Tracking an Aggregated Power Setpoint

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2020年第5期56卷 5750-5761页

作者： Rudnik, Roman Wang, Cong Reyes-Chamorro, Lorenzo Achara, Jagdish Boudec, Jean-Yves Le Paolone, Mario Ecole Polytech Fed Lausanne CH-1015 Lausanne Switzerland Univ Austral Chile Fac Ciencias Ingn Valdivia 5090000 Chile

We consider the problem of controlling the charging of electric vehicles (EVs) connected to a single charging station that follows an aggregated power setpoint from a main controller of the local distribution grid. To cope with volatile resources such as load or distributed generation, this controller manages in real time the flexibility of the energy resources in the distribution grid and uses the charging station to adapt its power consumption. The aggregated power setpoint might exhibit rapid variations due to other volatile resources of the local distribution grid. However, large power jumps and minicycles could increase the EV battery wear. Hence, our first challenge is to properly allocate the powers to EVs so that such fluctuations are not directly absorbed by EV batteries. We assume that EVs are used as flexible loads and that they do not supply the grid. As the EVs have a minimum charging power that cannot be arbitrarily small, and as the rapid fluctuations of the aggregated power setpoint could lead to frequent disconnections and reconnections, the second challenge is to avoid these disconnections and reconnections. The third challenge is to fairly allocate the power in the absence of the information about future EVs arrivals and departures, as this information might be unavailable in practice. To address these challenges, we formulate an online optimization problem and repeatedly solve it by using a mixed-integer-quadratic program. To do so in real time, we develop a heuristic that reduces the number of integer variables. We validate our method by simulations with real-world data.

关键词： Batteries Charging stations Real-time systems Optimization Switches Resource management Delays Battery protection dispatching of active distribution networks electric vehicles (EVs) fairness mixed-integer programming real-time control

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Two mixed Logical Dynamical Real-Time Receding Horizon Control Schemes for Microgrids Operation Optimization 29

Two Mixed Logical Dynamical Real-Time Receding Horizon Contr...

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29th Iranian Conference on Electrical Engineering (ICEE)

作者： Kheradmand, Seyed Shahab Haghpanah, Reyhaneh Farsangi, Malihe Maghfouri Yazdi, Mojtaba Barkhordary Shahid Bahonar Univ Kerman Dept Elect Engn Shiraz Iran Shiraz Univ Thechnol Dept Elect Engn Shiraz Iran

ISBN: (纸本)9781665433655

In this paper, a control scheme based on hybrid model predictive control (HMPC) is presented with two different cost functions for the energy management of a grid-connected microgrid (MG), including a battery storage device, a diesel generator, a photovoltaic system, and critical load. The real-time controller relies on the mixed-logical dynamical (MLD) model of the system and is in charge of computing the operating conditions for each MG component over a 24-hour horizon, with a sampling period of 60 min. An economic cost function is proposed to minimize the operation cost. Furthermore, considering the terminal equality constraint an alternative cost function based on minimization of the battery tracking error is presented. The mentioned constraint is in charge of stability and recursive feasibility of the operation. Moreover, simulation results are provided to show the advantages and disadvantages of both approaches.

关键词： Distributed generation Economic dispatch Model predictive control mixed-integer programming Unit commitment

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Optimal Sizing of Grid-Scaled Battery with Consideration of Battery Installation and System Power-Generation Costs

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ENERGIES 2022年第13期15卷 4742页

作者： Klansupar, Chalermjit Chaitusaney, Surachai Chulalongkorn Univ Fac Engn Dept Elect Engn Bangkok 10330 Thailand

Variable renewable energy (VRE) generation changes the shape of residual demand curves, contributing to the high operating costs of conventional generators. Moreover, the variable characteristics of VRE cause a mismatch between electricity demand and power generation, resulting in a greater expected energy not supplied (EENS) value. EENS involves an expected outage cost, which is one of the important components of power-generation costs. A utility-scale battery energy storage system (BESS) is popularly used to provide ancillary services to mitigate the VRE impact. The general BESS ancillary-service applications are as a spinning reserve, for regulation, and for ramping. A method to determine optimal sizing and the optimal daily-operation schedule of a grid-scale BESS (to compensate for the negative impacts of VRE in terms of operating costs, power-generation-reliability constraints, avoided expected-outage costs, and the installation cost of the BESS) is proposed in this paper. Moreover, the optimal BESS application at a specific time during the day can be selected. The method is based on a multiple-BESS-applications unit-commitment problem (MB-UC), which is solved by mixed-integer programming (MIP). The results show a different period for a BESS to operate at its best value in each application, and more benefits are found when operating the BESS in multiple applications.

关键词： energy storage system expected energy not supplied mixed-integer programming optimal sizing optimal daily-operation schedule power-generation cost variable renewable energy

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Rest break policy comparison for heavy vehicle drivers in Australia

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2022年第0期159卷 102518-102518页

作者： Eskandarzadeh, Saman Fahimnia, Behnam Univ Sydney Business Sch Inst Transport & Logist Studies Sydney Australia

Carriers and postal companies are under increasing pressure to reduce their operating costs and increase efficiency. One way to reduce costs is to improve the utilisation of drivers' working hours by employing more efficient rest break policies. A rest break policy is a restrictive set of rules consistent with national regulations for hours of service. We develop and validate a novel framework to model and analyse a class of these policies that concern the location of the rest breaks. In particular, we compare two representative rest break policies using data from a major Australian postal carrier. The first policy imposes no restriction on the location of a rest break. The second policy requires the driver to return to a depot for rest taking allowing time for socialising and making use of full amenities. Using postal transport data from Sydney metropolitan area, we find that the difference between the two policies in terms of tour length is only over 1%. We further apply the proposed framework to assess the impact of increasing the minimum break time on the two representative policies.

关键词： Parcel delivery Rest break policy Truck driver mixed-integer programming Australia

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An evolution strategy approach for the distributed permutation flowshop scheduling problem with sequence-dependent setup times

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COMPUTERS & OPERATIONS RESEARCH 2022年 142卷 105733-105733页

作者： Karabulut, Korhan Oztop, Hande Kizilay, Damla Tasgetiren, M. Fatih Kandiller, Levent Yasar Univ Dept Software Engn Izmir Turkey Izmir Democracy Univ Dept Ind Engn Izmir Turkey Auburn Univ Dept Ind & Syst Engn Auburn AL USA Yasar Univ Dept Ind Engn Izmir Turkey

This paper considers a distributed permutation flowshop scheduling problem with sequence-dependent setup times (DPFSP-SDST) to minimize the maximum completion time among the factories. The global economy has enabled large companies to have distributed production centers to become widespread, and effective production scheduling between these centers plays a vital role in the competitiveness of companies. To provide effective scheduling for the DPFSP-SDST, we propose a new mixed-integer linear programming (MILP) model and a new constraint programming (CP) model, which is presented for the first time in literature to the best of our knowledge. As the CP has become a solid competitor to the MILP in the literature, this study aims to exploit the effectiveness of CP to solve such a complex DPFSP-SDST. Since the problem is NP-hard, we also offer an evolution strategy (ES_en) algorithm that employs a self-adaptive scheme to obtain high-quality solutions in a short time. A ruin-and-recreate procedure is also embedded into the developed ES_en. We calibrate the parameters of the proposed ES_en using a design of experiment approach. We also compare the proposed ES_en algorithm's performance with three state-of-the-art metaheuristic algorithms from the literature, i.e., the IG2S (a variant of an iterated greedy algorithm with NEH2_en initialization), IGR (another variant of an iterated greedy algorithm with a restart scheme), and discrete artificial bee colony (DABC) algorithm. A detailed computational experiment is carried out to evaluate the performance of the mathematical models (MILP and CP) and the heuristic algorithms (ES_en, IG2S, IGR, and DABC). A comprehensive benchmark set is generated for the DPFSP-SDST from the well-known PFSP instances from the literature, considering various combinations of jobs, machines, factories, and SDST settings, resulting in 2880 benchmark instances. For 216 out of 240 small-size instances, optimal results are reported by solving the propose

关键词： Distributed flowshop scheduling Sequence-dependent setup times Evolution strategy mixed-integer programming Constraint programming

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Economic Generation Scheduling of a Microgrid Using mixed integer Linear programming

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中国电机工程学报 2013年第28期 -25--25--25--25页

作者： WU Xiong WANG Xiuli WANG Jianxue BIE Zhaohong Xi’an Jiaotong University

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An iterative exact algorithm for the weighted fair sequences problem

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COMPUTERS & OPERATIONS RESEARCH 2022年 148卷

作者： Sinnl, Markus Johannes Kepler Univ Linz Inst Prod & Logist Management JKU Business Sch Linz Austria

In this work, we present a new iterative exact solution algorithm for a recently introduced NP-hard sequencing problem. In the problem we are given an upper bound on the allowed solution sequence length and a list of symbols. For each symbol, there is a positive weight and a number, which gives the minimum amount of times the symbol has to occur in a feasible solution sequence. The goal is to find a feasible sequence, which minimizes the maximum weight-distance product, which is calculated for each consecutive appearance of each symbol in the sequence, including the last and first appearance in the sequence, i.e., the sequence is considered to be circular for the calculation of the objective function. Our proposed solution algorithm is based on a new mixed-integer programming model for the problem with a fixed sequence length. We also present various enhancements for our algorithm. We conduct a computational study on the instances from literature to assess the efficiency of our newly proposed solution *** approach solves 404 of 440 instances to optimality within the given time limit, most of them within five minutes. The previous best existing solution approach for the problem only solves 229 of these instances and its exactness depends on an unproven conjecture. Moreover, our approach is up to two orders of magnitude faster compared to this best existing solution approach.

关键词： Scheduling problem mixed-integer programming Sequencing problem Iterative algorithm

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A chance-constrained dial-a-ride problem with utility-maximising demand and multiple pricing structures

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2022年第0期158卷 102601-102601页

作者： Dong, Xiaotong Chow, Joseph Y. J. Waller, S. Travis Rey, David UNSW Sch Civil & Environm Engn Sydne NSW 2052 Australia NYU Tandon Sch Engn C2SMART Univ Transportat Ctr Brooklyn NY USA Univ Cote Azur SKEMA Business Sch Sophia Antipolis Campus Sophia Antipolis Campus Nice France

The classic Dial-A-Ride Problem (DARP) aims at designing the minimum-cost routing that accommodates a set of user requests under constraints at an operations planning level, where users' preferences and revenue management are often overlooked. In this paper, we present a mechanism for accepting/rejecting user requests in a Demand Responsive Transportation (DRT) context based on the representative utilities of alternative transportation modes. We consider utility-maximising users and propose a mixed-integer programming formulation for a Chance Constrained DARP (CC-DARP), that captures users' preferences via a Logit model. We further introduce class-based user groups and consider various pricing structures for DRT services. A customised local search based heuristic and a matheuristic are developed to solve the proposed CC-DARP. We report numerical results for both DARP benchmarking instances and a realistic case study based on New York City yellow taxi trip data. Computational experiments performed on 105 benchmarking instances with up to 96 nodes yield average profit gaps of 2.59% and 0.17% using the proposed local search heuristic and matheuristic, respectively. The results obtained on the realistic case study reveal that a zonal fare structure is the best strategy in terms of optimising revenue and ridership. The proposed CC-DARP formulation provides a new decision-support tool to inform on revenue and fleet management for DRT systems on a strategic planning level.

关键词： Dial-a-ride problem Demand-responsive transportation Chance constraint mixed-integer programming Local search Matheuristic

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Distributionally Robust Fair Transit Resource Allocation During a Pandemic

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TRANSPORTATION SCIENCE 2022年第4期57卷 954页

作者： Sun, Luying Xie, Weijun Witten, Tim Virginia Tech Dept Ind Syst Engn Blacksburg VA 24061 USA Blacksburg Transit Blacksburg VA 24060 USA

This paper studies the distributionally robust fair transit resource allocation model (DrFRAM) under the Wasserstein ambiguity set to optimize the public transit resource allocation during a pandemic. We show that the proposed DrFRAM is highly nonconvex and nonlinear, and it is NP-hard in general. Fortunately, we show that DrFRAM can be reformulated as a mixed integer linear programming (MILP) by leveraging the equivalent representation of distributionally robust optimization and monotonicity properties, binarizing integer variables, and linearizing nonconvex terms. To improve the proposed MILP formulation, we derive stronger ones and develop valid inequalities by exploiting the model structures. Additionally, we develop scenario decomposition methods using different MILP formulations to solve the scenario subproblems and introduce a simple yet effective no one left-based approximation algorithm with a provable approximation guarantee to solve the model to near optimality. Finally, we numerically demonstrate the effectiveness of the proposed approaches and apply them to real-world data provided by the Blacksburg Transit.

关键词： distributionally robust mixed-integer programming strong formulations valid inequalities

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