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An MILP model based on a processing strategy of complex multisource constraints for the short-term peak shaving operation of large-scale cascaded hydropower plants

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RENEWABLE ENERGY 2024年 231卷

作者： Fang, Zhou Liao, Shengli Zhao, Hongye Cheng, Chuntian Liu, Benxi Wang, Huan Li, Shushan Dalian Univ Technol Inst Hydropower & Hydroinformat Dalian 116024 Peoples R China Power Dispatching Control Ctr China Southern Power Guangzhou 510623 Peoples R China

Hydropower with flexible regulation plays an important role in short-term peak shaving operations. However, short-term peak shaving operation is a challenging problem due to the large scale, the nonconvex and nonlinear characteristics, and the complex multisource tasks. This study proposes a mixed integer linear programming (MILP) model, termed MILPoPSC, based on a processing strategy for complex multisource constraints, tailored for short-term peak shaving in large-scale cascaded hydropower plants. The MILP model, designed to incorporate multisource tasks by abstracting them into constraints, ensures that task requirements are met. A novel multisource constraint transformation method is introduced to derive constraint expressions related to power flow, facilitating the unification of constrained variables. Additionally, a classification and integration method based on restriction mode and set theory is proposed to improve solving efficiency by integrating constrains of the same type. The proposed method was applied to 7 hydropower cascade plants in the Wujiang River. The results showed that the linearization method and the processing strategy of complex multisource constraints can successfully reduce the complexity of the MILP model without affecting the solution quality. This indicates that MILPoPSC has good practical value for the short-term peak shaving operation of large-scale cascaded hydropower plants in China.

关键词： Cascade hydropower plants Short-term peak shaving operation mixed integer linear programming Multisource constraints

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Enhancing target benefits of power system stakeholders: A columns and constraint generation-based power-to-gas linked economic dispatch

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ELECTRIC POWER SYSTEMS RESEARCH 2024年 229卷

作者： Son, Yeong-Geon Kwak, Joosik Park, Seong-Jun Kim, Sung-Yul Keimyung Univ Daegu South Korea Korea Elect Power Res Inst Daejeon South Korea

Economic dispatch (ED) plays a crucial role in optimizing power plant output to minimize the cost of electricity production and ensure economic efficiency in complex power systems. However, with the growing emphasis on carbon neutrality policies and the increased use of renewable energy sources (RES), traditional ED models may lead to economic losses for independent power producers (IPP) and renewable energy providers (REP). To address this challenge, a new ED model is proposed in this study, which integrates power-to-gas (P2G) technology and takes into account the perspectives of all stakeholders, including independent system operator (ISO) IPP, and REP. The proposed approach is tested in the context of the cost based pool (CBP) market structure in S. Korea, where a mixed integer linear programming (MILP) problem is solved for each target benefit using columns and constraint generations (C&CG). By ensuring the target benefits of each stakeholder group, this improved ED model aims to encourage their participation in the power system and support economic efficiency. The simulation results of the P2G-linked ED proposed in this paper verify that as the capacity of the integrated P2G increases, there is an increase in the improvement rate of each target benefit for ISO, IPP, and REP.

关键词： Economic dispatch Power to Gas Columns and constraint generations mixed integer linear programming Two -stage Taylor Series

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Electric vehicle charging scheduling with mobile charging stations

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JOURNAL OF CLEANER PRODUCTION 2024年 434卷

作者： Li, Hua Son, Dongmin Jeong, Bongju Yonsei Univ Dept Ind Engn 50 Yonsei Ro Seoul 03722 South Korea

Mobile charging station (MCS) is a brand-new technology to electric vehicle charging, which is a supplementary service for addressing the shortcomings associated with fixed charging station (FCS), such as prolonged waiting time of charging, charging congestion of FCS, and user travel anxiety. While MCSs offer convenience to electric vehicle users, the challenge faced in the MCS operation is that MCS equipped with large batteries to provide charging services to users by visiting them one by one not only leads to high operating costs, but also prolongs the waiting time for users to utilize MCS services. To overcome the issues, a novel framework is proposed by optimizing the MCS operation in economic efficiency. In this study, a variant of mixed integer linear programming (MILP) model is developed to maximize the MCS operator's profits with considering the user's perspective, including clustering, and covering user demands, setting temporary charging location for users, dispatching MCSs for charging and discharging, and scheduling EV charging. As the scale of the problem increases, the solution time of using the proposed MILP model is inefficient. Whereas an improved genetic algorithm is developed for solving a large-scale of the proposed model. Solomon's benchmarking instance data is adopted to evaluate the performance and validity of the proposed algorithm, complemented by various sensitivity analyses aimed at providing managerial insights into MCS operations.

关键词： Mobile charging Dispatching Charging scheduling Genetic algorithms mixed integer linear programming Electric vehicle

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Augmenting electric vehicle fast charging stations with battery-flywheel energy storage

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JOURNAL OF ENERGY STORAGE 2024年 97卷

作者： Mouratidis, Panagiotis Batterien Montage Zentrum BMZ Germany GmbH Zeche Gustav 1 D-63791 Karlstein Germany

This work investigates the economic efficiency of electric vehicle fast charging stations that are augmented by battery-flywheel energy storage. Energy storage can aid fast charging stations to cover charging demand, while limiting power peaks on the grid side, hence reducing peak power demand cost. The investigated fast charging station is based on a common DC bus, to which all electrical equipment is connected. The arrival time to the charging station is described by a normal distribution for passenger cars and a uniform distribution for heavyduty vehicles, which result in a stochastic charging profile. The size of the fast charging station is optimized through mixed integer linear programming, so that its net present value is maximized. The results reveal that the battery-flywheel augmented fast charging station can achieve a net present value that is up to 12 % greater than that of a fast charging station without energy storage. Nevertheless, due to the additional investment cost for energy storage, fast charging stations without storage achieve a higher internal rate of return and a lower discounted payback period than fast charging stations with energy storage.

关键词： Electric vehicle fast charging Energy storage Lithium-ion battery storage Flywheel storage mixed integer linear programming

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A MILP model and heuristic method for the time-dependent electric vehicle routing and scheduling problem with time windows

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JOURNAL OF CLEANER PRODUCTION 2024年 434卷

作者： Zhou, Saiqi Zhang, Dezhi Ji, Bin Zhou, Shaoyu Li, Shuangyan Zhou, Likun Cent South Univ Sch Traff & Transportat Engn Changsha 410075 Hunan Peoples R China Cent South Univ Forestry & Technol Coll Logist & Transportat Changsha 410004 Hunan Peoples R China Shanghai Wanxin Informat Technol Co Ltd Shanghai 200441 Peoples R China

As an emerging and sustainable technology, electric vehicles (EVs) are becoming increasingly popular in the transportation system. However, they still have limitations in terms of energy capacity and high consumption. By implementing flexible scheduling for EV routings, it is hoped that improved efficiency and saved energy consumption can be achieved. This paper focuses on studying a time-dependent electric vehicle routing and scheduling problem with time windows (TDEVRSPTW). The goal is to minimize the total cost of energy consumption, travel distance, and the number of EVs, while considering vehicle travel process scheduling that allows stops at any nodes and along any arcs during periods of time-dependent congestion. For the first time, a mixed integer linear programming model is formulated for the problem, allowing for optimal solutions to small-scale problems using CPLEX. Meanwhile, a variable neighborhood search with partial model (VNS-PM) method is developed to handle the large-scale problem with 200 customers and obtain effective solutions. The numerical experiments demonstrate significant savings in energy consumption by the vehicle travel process scheduling. The proposed method further validates its strong performance by finding 11 new best solutions out of the 56 related EVRPTW benchmark instances. In addition, a case study is conducted to verify the application and energy consumption savings of the proposed problem, which also derives some additional recommendations by sensitivity analysis.

关键词： Electric vehicle Energy consumption saving Vehicle routing and scheduling mixed integer linear programming Variable neighborhood search

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Decomposition-based heuristic approaches for the satellite constellation design problem

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ENGINEERING OPTIMIZATION 2024年

作者： Mencarelli, Luca Floquet, Julien Univ Pisa Dipartimento Informat Pisa Italy ACRI ST Sophia Antipolis France

Satellite constellation design problems have been vastly investigated in the existing literature. This work explores decomposition-based methods for the satellite constellation design problem with discontinuous coverage and revisit time. Specifically, two methodologies are provided, based on the decomposition approach and enriched with two novel heuristic rules, to identify a low, possibly minimum, size satellite constellation that allows periodic observation of a set of targets within a specific time window. Numerical experiments are presented to demonstrate the validity of the proposed model.

关键词： Satellite constellation design discontinuous coverage mission planning satellites decomposition approach mixed integer linear programming

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Variable fixing heuristics for solving multiple depot vehicle scheduling problem with heterogeneous fleet and time windows

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OPTIMIZATION LETTERS 2021年第1期15卷 153-170页

作者： Dauer, Armando Teles Prata, Bruno de Athayde Univ Fed Ceara Campus Cratetus Cratetus Brazil Univ Fed Ceara Dept Ind Engn Campus Pici Fortaleza Ceara Brazil

This paper aims at presenting the multiple depot vehicle scheduling problem with heterogeneous fleet and time windows (MDHFVSP-TW). We used a time-space network (TSN) to perform the modeling of MDHFVSP-TW, along with two methodologies to reduce its size and, therefore, its complexity. Along with size reduction methods, a mixed integer programming (MIP) heuristic with variable fixation was presented. Its operation is based on the use of the solution for this problem with relaxed variables as a basis for the removal of arcs from the problem, reducing its size and enabling its resolution in reasonable computational time. Extensive tests were performed for a collection of randomly generated instances. Subsequently, a case study arising from a real instance from a Brazilian city is presented. The computational results showed that the proposed heuristic and size reduction methods obtained good performance, providing high-quality solutions in an adequate computational time.

关键词： Combinatorial optimization Public transport systems mixed integer linear programming Machine learning

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A Variable Performance Parameters Temperature-Flowrate Scheduling Model for Integrated Energy Systems

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ENERGIES 2021年第17期14卷 5400页

作者： Niu, Hong-Hai Zhao, Yang Wei, Shang-Shang Li, Yi-Guo Southeast Univ Sch Energy & Environm Key Lab Energy Thermal Convers & Control Minist Educ Nanjing 210096 Peoples R China Nanjing NARI RELAYS Elect Co Ltd Nanjing 211102 Peoples R China

Optimal scheduling strategy of integrated energy systems (IES) with combined cooling, heating and power (CCHP) has become increasingly important. In order to make the scheduling strategy fit to the practical implementation, this paper proposes a variable performance parameters temperature-flowrate scheduling model for IES with CCHP. The novel scheduling model is established by taking flowrate and temperature as decision variables directly. In addition, performance parameters are treated as variables rather than constants in the proposed model. Specifically, the efficiencies of the gas turbine and the waste heating boiler are estimated with the partial load factor, and the coefficient of performance (COP) of the electrical chillers and heat pumps are estimated with the partial load factor and outlet water temperature. Then, to deal with the model nonlinearities caused by considering the variability of COPs, the COP-expansion method is developed by adopting a specific representation of the COP and the expansion of the outlet water temperature. Finally, case studies show that the variable performance parameters' temperature-flowrate scheduling model can account for the variation of performance parameters, especially the impacts of water temperature and the part load factor on the COP. Therefore, the proposed scheduling model can obtain more adequate and feasible operation strategy, thereby suggesting its applicability in engineering practice.

关键词： integrated energy system in China optimal operation strategy variable performance parameter temperature-flowrate based scheduling model mixed integer linear programming linearization technique COP-expansion method

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A Case Study on Scheduling of Repairs in an Automobile Shop 1st

A Case Study on Scheduling of Repairs in an Automobile Shop

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1st International Conference on Innovation in Engineering (ICIE)

作者： Pilar, M. Fatima Costa e Silva, Eliana Borges, Ana Politecn Porto ESTG CIICESI Porto Portugal

ISBN: (纸本)9783030791650;9783030791643

The classical combinatorial problem of scheduling is extensively studied and arises in several economic domains. However, there are few studies in the automobile sector, particularly in scheduling vehicle repair tasks and using real instances. This paper intends to contribute to fill this gap, focusing on the scheduling of the repairs of the mechanical section of a Portuguese firm in the automobile sector. A mathematical model is presented that will assist the shop manager on the scheduling of the repairs, taking into account: the mechanics and other resources that are available, the mechanical interventions to be performed on each vehicle and its expected processing time. The aim is to reduce the time of inactivity of the vehicles between interventions, as well as, the downtime of mechanics, and therefore improve productivity. The results, from real instances extracted from the data provided by the firm, show that the interventions are scheduled in a suitable form, and there is a reduction of the downtimes.

关键词： Scheduling mixed integer linear programming Automobile sector Real-world application

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Scheduling multimodal alternative services for managing infrastructure maintenance possessions in railway networks

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2021年 154卷 147-174页

作者： Borecka, Jacob Trepat Besinovic, Nikola Delft Univ Technol Dept Transport & Planning Delft Netherlands

Highly utilized railway networks require regular infrastructure maintenance. Different track sections often need to be closed for entire days to carry out engineering works, which makes the regular timetables no longer feasible and thus adjusted railway services and temporary alternative services need to be planned. We introduce the Multimodal Alternative Services for Possessions (MASP) problem to support the planning of alternative services, from the passenger and transport operator points of view, including an adjusted train timetable, bus-bridging services and extra train services. The MASP problem is formulated based on the Service Network Design Problem and the Vehicle Routing Problem. To solve it efficiently, we develop a solution framework that incorporates heuristics based on the column and row generation with mixed-integer linear programming. The developed framework provides the optimized alternative service routes, schedules and passenger flows routing. We demonstrated the performance of the MASP solution framework on the real-life Dutch railway network. The results show that the MASP framework is capable of efficiently generating alternative services to route passenger flows affected by possessions with a very limited increase in the total passenger costs compared to a scenario with no link closures. High computational efficiency is observed even for highly disrupted networks.

关键词： Railway disruption Maintenance Possessions Timetable Alternative services mixed integer linear programming Column generation Resilience

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