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Robust liner ship routing and scheduling schemes under uncertain weather and ocean conditions

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2022年 137卷

作者： Li, Mingyu Xie, Chi Li, Xinghua Karoonsoontawong, Ampol Ge, Ying-En Tongji Univ Key Lab Rd & Traff Engn Minist Educ 800 Dongchuan Rd Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Sch Naval Architecture Ocean & Civil Engn 1239 Siping Rd Shanghai 200092 Peoples R China Tongji Univ Sch Transportat Engn Shanghai Peoples R China Tongji Univ Natl Inst Innovat & Dev Shanghai Peoples R China King Mongkuts Univ Technol Thonburi Dept Civil Engn 126 Pracha Utid Rd Bangkok 10140 Thailand Changan Univ Coll Transportat Engn Middle Sect Naner Huan Rd Xian 710064 Shaanxi Peoples R China

Since sailing along the Northern Sea Route (NSR) through the Arctic Ocean comes into reality, commercial shipping developments including opening new liner services along this route have been put on the agenda. However, uncertainties within weather and ocean conditions in this region, especially during temperature-varying seasons, may cause failure to on-time arrivals, resulting unignorable or even unaffordable monetary losses. As a result, these uncertainties will inevitably affect cargo shippers' willingness of choosing this being-explored route, even if on average its shipping time is much shorter than that of the traditional Asia-Europe shipping lines. In this context, the present paper describes a liner ship routing and scheduling problem considering schedule-sensitive demand and late-arrival penalty for operating incoming NSR shipping lines in the future. By using two types of uncertainty sets, bounded and budget-bounded uncertainty sets, we construct and solve two robust counterparts of this problem. The deterministic model and bounded robust model can be seen as special cases of the budget-bounded robust model when the uncertainty budget is set to null and full, respectively. A multifaceted case study of planning liner shipping routes and schedules along the NSR is conducted to validate the efficacy and efficiency of the proposed models and identify the effects of uncertainty bounds and budgets on the solution performance. The following facts and conclusions are revealed from the optimization results of the case study: The budget-bounded robust model functions the best in the worst condition;low revenue rate and high demand sensitivity are the major factors for excluding a candidate port from the route;the order of a visited port in the route decides the weight of its uncertainty budget on the entire shipping line;setting the uncertainty budget in a decelerative way will enhance the scheduling robustness of solutions.

关键词： Liner ship routing and scheduling Uncertain weather and ocean conditions Uncertainty bound Uncertainty budget Robust optimization mixed integer linear programming

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Convex Approximation for LTL-based Planning

Convex Approximation for LTL-based Planning

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Tokuda, Shumpei Yamakita, Masaki Oyama, Hiroyuki Takano, Rin Tokyo Inst Technol Dept Syst & Control Engn Meguro Ku 1-11-1 Oh Okayama Tokyo 1518551 Japan NEC Corp Ltd Data Sci Res Labs Nakahara Ku 1753 Shimonumabe Kawasaki Kanagawa 2118666 Japan

ISBN: (纸本)9781665417143

We present a formulation for linear temporal logic (LTL)-based task planning of nonlinear dynamical systems. We consider pick-and-place task planning as a typical example of the planning task that can be modeled as a hybrid system that includes the states of robots and objects. LTL-based planning for hybrid systems is solved as a mixed-integer problem (MIP), especially a mixed-integer linear programming problem (MILP). Due to the formulation by the MILP, we could only deal with linear systems and linear constraints. In our proposed method, we apply a convex approximation to systems that have bilinear terms and quadratic terms in their dynamics. And we incorporate nonlinear systems into existing LTL-based planning as an MILP. We demonstrate the effectiveness through numerical simulations of a simple robot arm system and drone system.

关键词： linear systems programming Numerical simulation Planning Nonlinear dynamical systems Trajectory mixed integer linear programming

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A Multi-Trip Customized Bus Network Design Model

A Multi-Trip Customized Bus Network Design Model

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IEEE International Conference on Intelligent Transportation Engineering (ICITE)

作者： Qi Wang Peng Wu School of Economics & Management Fuzhou University Fuzhou P. R. China

ISBN: (数字)9798350314212

ISBN: (纸本)9798350314229

Customized bus services offer irreplaceable advantages in meeting passengers' diverse travel needs and promoting eco-friendly transportation. It is essential to undertake a scientifically planned and strategically laid-out customized bus operation network to achieve the efficient operation of customized buses. In this study, we address a new multi-trip customized bus network design problem with considering passenger time windows, walking limitations, bus capacity, multi-trip, and stop location decisions to simultaneously minimize customized bus operational cost and maximize the number of passengers served. We formulate it as a mixed-integer linear programming model. Computational results for a case based on the well-known Sioux Falls network verify the effectiveness and efficiency of the model.

关键词： Legged locomotion Costs Computational modeling Transportation mixed integer linear programming Computational efficiency

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Operation Scheduling for Multiple HVAC Systems under Power Constraints

Operation Scheduling for Multiple HVAC Systems under Power C...

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IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Theint Theint Thu Kenshiro Kato Dafang Zhao Hiroki Nishikawa Ittetsu Taniguchi Takao Onoye Graduate School of Information Science and Technology Osaka University Suita Japan

ISBN: (数字)9798350318098

ISBN: (纸本)9798350318104

This paper proposes operation scheduling for multiple HVAC systems. Uncoordinated scheduling of multiple HVAC systems can lead to a significant power imbalance and increase energy consumption. To minimize the total energy consumption of HVAC systems, we propose a coordinated load scheduling for multiple HVAC systems, considering thermal comfort under power constraints. This work is based on mixed integer linear programming and employs model predictive control (MPC). The simulation results highlight that our scheduling problem reduces the total energy consumption by 5.7 kWh (8.7%) on average with satisfying thermal comfort compared to a state-of-the-art one.

关键词： Energy consumption Schedules HVAC Simulation Heuristic algorithms mixed integer linear programming Thermal loading

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Optimal Operation of Energy Hubs in an Auction-Based Peer-To-Peer Energy Trading Framework

Optimal Operation of Energy Hubs in an Auction-Based Peer-To...

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IEEE PES Conference on Innovative Smart Grid Technologies - Middle East (ISGT Middle East)

作者： Kirkland Rowe Geev Mokryani Kavian Cooke F. Campean Therese Chambers Faculty of Engineering and Informatics University of Bradford UK Faculty of Engineering and Computing University of Technology Jamaica

This paper presents a bi-level stochastic mixed-integer linear programming (MILP) model for the optimal operation of the energy hubs participating in the peer-to-peer (P2P) energy market in an integrated electricity-gas energy system. The upper-level problem represents the strategic behaviour of the Distribution Network Operator (DNO) to maximize their profit. The lower level corresponds to the P2P market clearing problem, where energy hubs operate to minimize cost and strategically exchange energy with each other and the distribution network. The model is transformed into a single-level model using the Karush-Kuhn-Tucker (KKT) optimality conditions. The proposed model is validated on an integrated 16-bus 33 kV UK generic distribution system (UKGDS) and a 6-node natural gas system, which is used to demonstrate the model’s effectiveness.

关键词： Costs Stochastic processes Distribution networks Peer-to-peer computing Smart grids mixed integer linear programming Natural gas

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Pave the way for sustainable smart homes: A reliable hybrid AC/DC electricity infrastructure

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ELECTRIC POWER SYSTEMS RESEARCH 2022年 210卷

作者： Ardalan, Chenour Vahidinasab, Vahid Safdarian, Amir Shafie-khah, Miadreza Catalao, Joao P. S. Shahid Beheshti Univ Fac Elect Engn Tehran 69411 Iran Nottingham Trent Univ Sch Sci & Technol Dept Engn Nottingham NG11 8NS England Sharif Univ Technol Dept Elect Engn Tehran Iran Univ Vaasa Sch Technol & Innovat Vaasa 65200 Finland Univ Porto Fac Engn P-4200465 Porto Portugal INESC TEC P-4200465 Porto Portugal

The development of emerging smart grid technologies has led to more and more penetration of renewable energy resources and electric energy storage in the residential sectors. Besides, owing to the significant evolution of power electronic devices, there is a rapid growth in penetration of DC loads and generations, such as PV and electric vehicles (EVs), into the buildings and homes as a building block of the future smart cities. This is despite the fact that the electricity infrastructure of the conventional buildings is designed based on AC electricity and as a result, there would be a lot of losses due to the frequent power conversion from AC to DC and vice versa. Besides, according to a significant amount of energy consumption in the residential sector, buildings have a prominent role to confront environmental problems and obtain sustainability. In such circumstances, and considering the energy outlook, rethinking the electrification structure of the built environment is necessary. This work is an effort in this regard and looks for a sustainable energy infrastructure for the cyber-physical homes of the future. Three disparate electrification architectures are analyzed. The proposed framework, which is formulated as a mixed-integer linear programming (MILP) problem, not only considers costs associated with investment and operation but also evaluates the reliability of each structure by considering the different ratios of DC loads. Moreover, the optimal size of renewable energy resources and the effect of EV demand response, and different prices of PV and battery are precisely investigated. The efficacy of the proposed approach is evaluated via numerical simulation.

关键词： Smart homes Reliability Optimization Renewable Energy Resources Hybrid AC DC Electric vehicle mixed integer linear programming

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A new clustering method for the optimization of distribution networks layout considering energy efficiency and continuity of service

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SUSTAINABLE ENERGY GRIDS & NETWORKS 2022年 30卷

作者： Falabretti, Davide Sabbatini, Gianluca Politecn Milan Dept Energy Via La Masa 34 I-20156 Milan Italy

The electrification of final consumptions and the spreading of distributed generation have fostered the search for new and more advanced electrical grid planning techniques, considering many of the aspects affecting electrical grids operation, such as their electrical and economic performance, as well as system reliability. Distribution network clustering is defined to be the division of the utility service territory into several high voltage-medium voltage substation service areas, and it represents one of the most important steps for grids planning. In this context, the purpose of this paper is to propose an innovative clustering algorithm based on mixed integer linear programming (MILP) formulation, able to take into account some fundamental aspects of the distribution networks planning process, such as the electrical losses along lines, the existing distribution network layout, and the reliability of the system. The approach, tested on the medium voltage network of the medium-sized city of Meran in the North of Italy, has proved to effectively manage the computational burden needed to model and optimize the structure of a complex distribution grid, as those that usually cover large urban areas. (c) 2022 Elsevier Ltd. All rights reserved.

关键词： Distribution networks Clustering optimization Continuity of service Energy efficiency mixed integer linear programming

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Optimal design of solar-assisted steam and power system under uncertainty

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JOURNAL OF CLEANER PRODUCTION 2022年 336卷

作者： Wang, Fengyuan Zhang, Shuai Lv, Chenyu Liu, Linlin Zhuang, Yu Zhang, Lei Du, Jian Dalian Univ Technol Inst Chem Proc Syst Engn Dalian 116024 Liaoning Peoples R China

Solar energy, as an important clean energy source, is difficult to be widely used in process industry due to its intermittent nature. So in order to improve the process sustainability and also flexibility, a systematic method is proposed to design the solar-assisted steam and power system with the uncertainty factors, including the solar radiation and the real-time demands of steam and power from production processes, are simultaneously considered at the same time. A two-stage stochastic programming model with the objectives of minimum total annual cost and minimum environmental impact is formulated to implement the optimal design of the system, and the epsilon-constraint method is adopted to deal with the resultant multi-objective problem. Considering the characters of uncertainty, the clustering-based method and the 3-point approximation method are adopted to generate the operation scenarios. At last, the effectiveness of the proposed modelling framework is illustrated through a case study, and several guiding opinions at the system design stage are summarized by weighing the economic and environmental goals, analysing the distribution of different goals with scenarios, and discussing the resulting cost compositions. In addition, comparisons between the deterministic and the stochastic programming models are performed as well. The results show that the total annual cost by latter is only 5.2% higher than by former when the same environmental impact (1.08 x 10(6) Ec/year) is caused.

关键词： Solar-assisted steam power system Uncertainty Stochastic programming mixed integer linear programming Multi-objective optimization

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Feasibility of Behind-the-Meter Battery Storage in Wind Farms Operating on Small Islands

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BATTERIES-BASEL 2022年第12期8卷

作者： Dratsas, Pantelis A. Psarros, Georgios N. Papathanassiou, Stavros A. NTUA Sch Elect & Comp Engn Zografou Campus 9Iroon Polytech Str Athens 15780 Greece

This paper investigates the anticipated benefits from the introduction of a battery energy storage system (BESS) behind-the-meter (BtM) of a wind farm (WF) located in a small non-interconnected island (NII) system. Contrary to the standard storage deployment applications for NII, where storage is either installed in front of the meter as a system asset or integrated into a virtual power plant with renewable energy sources, the BESS of this paper is utilized to manage the power injection constraints imposed on the WF, aiming to minimize wind energy curtailments and improve WF's yield. A mixed integer linear programming generation scheduling model is used to simulate the operation of the system and determine the permissible wind energy absorption margin. Then, a self-dispatch algorithm is employed for the operation of the WF-BESS facility, using the BESS to manage excess wind generation that cannot be directly delivered to the grid. Additionally, the contribution of BESS to the capacity adequacy of the NII system is investigated using a Monte Carlo-based probabilistic model, amended appropriately to incorporate storage. Finally, an economic feasibility analysis is carried out, considering the possible revenue streams. By examining several BESS configurations, it has been shown that BtM BESS reduces energy curtailments and contributes substantially to resource adequacy as its energy capacity increases. However, the investment feasibility is only ensured if the capacity value of the BtM storage is properly monetized or additional dependability of wind production is claimed on the ground that the inherent intermittency of the wind production is mitigated owing to storage.

关键词： battery energy storage stations wind energy management principle autonomous power systems non-interconnected island renewable penetration unit commitment capacity adequacy economic assessment mixed integer linear programming

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Aggregate production planning considering organizational learning with case based analysis

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AIN SHAMS ENGINEERING JOURNAL 2022年第2期13卷

作者： Attia, El-Awady Megahed, Ashraf AlArjani, Ali Elbetar, Ahmed Duquenne, Philippe Prince Sattam Bin Abdulaziz Univ Coll Engn Al Kharj Ind Engn Dept Al Kharj 16273 Saudi Arabia Benha Univ Shoubra Fac Engn Mech Engn Dept Cairo 11672 Egypt Elaraby Grp Qalubia Governorate Egypt Benha Univ Fac Engn Benha Mech Engn Dept Banha Egypt Toulouse Univ Ind Engn Dept INPT ENSIACET Toulouse France

Responding rapidly to customer needs is one of the main targets of industrial organizations that want to survive in the current market competition. This objective can be attained through robust planning. Workforce productivity is considered one of the important entities in production planning. However, it has a dynamic nature, i.e. the productivity growths thanks to on-job training or learning phenomenon. Considering this fact in manufacturing planning enhances the robustness of the developed plans. The present paper presents a mathematical model for medium-range production planning that is used to find the optimal aggregate production plan. The model aims to optimize the total production costs while respecting most of the operational constraints and considering the process of organizational learning. The presented model is constructed relying on the real industrial practices;the outcome is a mixed-integer linear program. The model was validated and checked using real data collected from an Egyptian factory that produces electric motors for home appliances. The proposed mathematical model was optimally solved using "ILOG-CPLEX 12.6". By comparing the results obtained versus that of the method adopted in the factory, a cost reduction of 6.3% is achieved for the presented data set. A set of managerial aspects are concluded after the model analysis. Moreover, the impact of using detailed learning rates on the production cost is discussed. (c) 2021 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Ain Shams University. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Aggregate production planning Learning curves Organizational learning mixed integer linear programming Manufacturing of electric motors

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