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作者： Anthony M. Baldessari Naval Postgraduate School

学位级别：硕士

The Navy Operational Planner project develops tools that help the Navy optimize operational planning in terms of time, manpower, and resources. Its purpose is to help decision makers use available platforms efficiently to accomplish as many missions as completely as possible over a finite time period. We adapt the anti-submarine warfare (ASW) component of this model by adding time-dependent performance data that reflect ocean or atmospheric conditions that vary over the planning horizon. We develop three test cases with varying degrees of time-dependence in the performance data, and show that taking this new information into account changes the operational plans generated and can lead to better employment of ASW platforms due to the more realistic representation of platform performance.

关键词： search and detection anti-submarine warfare optimization navy operational planning mixed-integer linear program

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Modeling gas flow directions as state variables: Does it provide more flexibility to power systems?

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ELECTRIC POWER SYSTEMS RESEARCH 2022年 212卷

作者： Shin, Junesoo Werner, Yannick Kazempour, Jalal Tech Univ Denmark Dept Wind & Energy Syst Lyngby Denmark Norwegian Univ Sci & Technol Dept Ind Econ & Technol Management Trondheim Norway

As a common practice, the direction of natural gas flow in every pipeline is determined ex-ante for simplification purposes, and treated as a given parameter within the scheduling problem. However, in integrated gas and electric power networks with a large share of intermittent renewable power supply, it is no longer straightforward to optimally predetermine the gas flow directions. A wrong predetermination of gas flow directions may result in feasible but not necessarily optimal schedules. We propose a mixed-integer linear optimization model to determine the optimal gas flow directions while scheduling the system. This unlocks additional flexibility to power systems, provided that a tight coordination between power and gas systems exists. The increased flexibility, although it comes at the cost of increased computational complexity, is quantified by comparing the total operational cost of the entire system with bidirectional gas flows as opposed to unidirectional gas flows. We numerically show that modeling gas flow directions as state variables may bring added value not only in the meshed but also in the radial gas networks.

关键词： Integrated energy systems Optimal gas flow directions Flexibility Linepack mixed-integer linear program

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Packing computing servers into the vessel of an underwater data center considering cooling efficiency

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APPLIED ENERGY 2022年 314卷

作者： Hu, Zhi-Hua Zheng, Yu-Xin Wang, You-Gan Shanghai Maritime Univ Qingdao Inst Qingdao 266034 Shandong Peoples R China Shanghai Maritime Univ Logist Res Ctr Shanghai 201306 Peoples R China Queensland Univ Technol Sch Math Sci Brisbane Qld 4001 Australia

An Underwater Data Center (UDC) is an underwater vessel full of computing servers and designed with a cooling system using cold water in the ocean. A UDC vessel is composed of cabinets for computing servers, and the cabinets are finally packed into racks that facilitate the installments of the computing servers. We formulate the problem of packing cabinets into the vessel by considering the water volume required for server cooling and the placement of the cabinets of servers. Due to different patterns of racks, a set of mixed-integer linear programs were developed, and they were solved by methods with several stages. As demonstrated by experiments, the proposed models and strategies effectively solve the simulated instances generated by considering the cooling principles. The cabinets with more considerable differences in their width and height are better than single-sized cabinets because the smaller cabinets make the packing process more flexible. Moreover, multi-sized cabinet packing is significantly better than single-sized cabinet packing. Additionally, it is not always appropriate to use racks with large capacities. However, racks with multiple capacities may improve the space and energy utilization degrees when the size and the designed heat power consumption of the data center are fixed.

关键词： Underwater data center Packing optimization Cooling system Data centers mixed-integer linear program

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Economic dispatch of power systems with LMP-dependent demands: A non-iterative MILP model

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ENERGY 2021年 233卷 121015-121015页

作者： Shen, Ziqi Wei, Wei Wu, Lei Shafie-khah, Miadreza Catalao, Joao P. S. Tsinghua Univ Dept Elect Engn State Key Lab Power Syst Beijing 100084 Peoples R China Stevens Inst Technol ECE Dept Hoboken NJ 07030 USA Univ Vaasa Sch Technol & Innovat Vaasa 65200 Finland Univ Porto Fac Engn P-4200465 Porto Portugal INESC TEC P-4200465 Porto Portugal

The proliferation of demand response programs in the smart grid provides the system operator unique opportunities to reduce the load peak and alleviate network congestions. This paper considers the economic dispatch problem with elastic demands which flexibly respond to the locational marginal prices (LMPs). However, LMP is the dual variable of optimal power flow (OPF) problem and thus is unknown before the OPF problem is solved. Without LMP, the elastic demand is unclear, and the OPF problem cannot be set up. Given this interactive nature, it is difficult to acquire the dispatch strategy as well as the LMP according to the traditional OPF method. This paper thoroughly addresses this problem. Specifically, the limitation of the traditional LMP scheme in the described situation is analyzed. An equilibrium solution may not exist because the demand function and the discontinuous LMP may not have an intersection. To overcome this difficulty, LMP at the discontinuity point is redefined, so that the dispatch problem always has an equilibrium solution. A mixed-integer linear programming model for the economic dispatch problem with LMP-dependent load is proposed, and the equilibrium solution simultaneously offers the dispatch strategy and LMPs. Case studies demonstrate the difficulties of traditional approaches and the effectiveness of the proposed method. (c) 2021 Elsevier Ltd. All rights reserved.

关键词： Direct-current optimal power flow Elastic demand Locational marginal price mixed-integer linear program

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A network design problem for upgrading decentrally produced biogas into biomethane

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JOURNAL OF CLEANER PRODUCTION 2024年 452卷

作者： Schroeer, Daniel Herlicka, Lisa Heinold, Arne Latacz-Lohmann, Uwe Meisel, Frank Univ Kiel Dept Agr Econ Kiel Germany Univ Kiel Fac Business Econ & Social Sci Kiel Germany Kuhne Logist Univ Hamburg Germany

In this paper, we explore the possibility of connecting decentralized biogas plants via a pipeline network to terminals that upgrade biogas into biomethane. We present a mixed-integer linear program that forms subnetworks of such plants, decides on suitable terminal locations, and establishes pipeline connections to maximize profit. We apply this model to a real-world scenario in Northern Germany. The results show a much higher total profit for the optimized network compared to the benchmark solutions where each plant upgrades biogas into biomethane on its own. Therefore, plants can increase their profitability by collaborating with other (neighboring) plants. However, the collaboration requires a fair profit-sharing model as network participation is not individually profitable for all plants, especially small ones.

关键词： Biogas network Biogas pipeline Biomethane upgrade Economies of scale mixed-integer linear program

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Assessing mixed-integer-based heat pump modeling approaches for model predictive control applications in buildings

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APPLIED ENERGY 2022年 326卷

作者： Maier, Laura Schoenegge, Marius Henn, Sarah Hering, Dominik Mueller, Dirk Rhein Westfal TH Aachen EON Energy Res Ctr Inst Energy Efficient Bldg & Indoor Climate Mathieustr 10 D-52074 Aachen Germany

Model predictive control can reduce heating systems' operating costs and energy consumption. This especially applies to heat pumps, whose operation efficiency highly depends on the heating system's source and sink temperatures. In literature, process models for heat pumps mostly introduce the coefficient of performance as a parameter thus assuming constant supply temperatures. However, supply temperature adjustment is crucial to overcharge buffer storages and hence shift energy to more favorable times, which is the basis of model predictive control concepts. We close this gap by developing two different air-source heat pump modeling approaches using the supply temperature as control variable: a piecewise linear model based on simulation results and a quadratic modeling approach. Both methods are benchmarked with a simplified linear model representing the state of research. The simplified linear model underestimates the cost of storage charging as it neglects the supply temperature's influence on the coefficient of performance and results in 8.7% higher operating costs and 12.1 % higher energy demand than the piecewise linear approach. However, the simplified linear model yields the lowest average computation time compared to the piecewise and quadratic approaches. The quadratic approach results in both lower operating costs (-1.9 %) and energy demand (-1.8 %), as well as lower computation times than the piecewise approach, consequently representing the best trade-off between performance and computational effort. We recommend future work to apply the method to a ground-or water-source heat pump and to a coupled building energy system to investigate the transferability of our findings.

关键词： Model predictive control mixed-integer linear program Optimal control Supply temperature control Heat pump system

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Two-stage robust telemedicine assignment problem with uncertain service duration and no-show behaviours

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COMPUTERS & INDUSTRIAL ENGINEERING 2022年第0期169卷 108226页

作者： Ji, Menglei Wang, Shanshan Peng, Chun Li, Jinlin Beijing Inst Technol Sch Management & Econ Beijing 100081 Peoples R China HEC Montreal Dept Decis Sci Montreal PQ H3T 2A7 Canada GERAD Montreal PQ H3T 2A7 Canada

The current pandemic of COVID-19 has caused significant strain on medical center resources, which are the main plac healthcare managers to make an effective assignment plan for the patients and telemedical doctors when providing telemedicine services. Motivated by this, we present the first comprehensive study of a two-stage robust telemedicine assignment problem when three different sources of uncertainty are incorporated, including uncertain service duration, no-show behaviours of both patients and telemedical doctors. From an algorithmic viewpoint, we propose an efficient nested column-and-constraint generation (C&CG) solution scheme that decomposes the model into an outer level problem and an inner level problem. Our results show that we can solve the problems of realistic sizes within a reasonable time (e.g., up to 100 patients, 10 telemedical doctors, and 200 scenarios within two hours). On the empirical side, we demonstrate how the hyper-parameters make a balance between cost management and the coverage level of the served patients in the presence of three different sources of uncertainty. Our comparison with a two-stage stochastic programming model implies that our model is not overly conservative and seems to provide a relatively cheaper modeling alternative that requires much less information support when hedging against three different sources of uncertainty under a worst-case situation.

关键词： Telemedicine assignment Two-stage robust optimization mixed-integer linear program NestedC&CG Uncertain service duration No-show behaviours

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Optimising makespan and energy consumption in task scheduling for parallel systems

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COMPUTERS & OPERATIONS RESEARCH 2023年 154卷

作者： Stewart, Russell Raith, Andrea Sinnen, Oliver Univ Auckland Engn Sci Auckland New Zealand Univ Auckland Elect Comp & Software Engn Auckland New Zealand

In parallel computing, the scheduling of the tasks of an application onto the processors of the parallel system is crucial. A task schedule determines both the allocation of tasks to the processors, and the order in which they are executed. Formally defined, this task scheduling problem is a challenging optimisation problem (strongly NP-hard), even for the case where there is only one objective, e.g. to minimise the total execution time, also known as makespan. Today task scheduling is often a constrained optimisation problem, where the makespan needs to be minimised, while keeping energy consumption below a threshold, or vice versa, where the energy consumption needs to be minimised, while keeping the makespan below a threshold. In a generalisation of this problem, we consider here a bi-objective version of this scheduling problem that aims to minimise both makespan and energy consumption in a Pareto-efficient manner. Based on a model of processor energy consumption, a bi-objective integer linear programming problem is formulated. Different approaches to modelling processor static (background) energy consumption are described. The task scheduling problems can be solved using bi-objective optimisation methods based on weighted sum scalarisation or epsilon-constraint scalarisation. In an extensive evaluation, the computational performance and the characteristics of sets of Pareto-efficient solutions of this bi-objective problem are studied and discussed, with interesting insights into the nature and shape of the Pareto-efficient sets.

关键词： Task scheduling Parallel processing Bi-objective mixed-integer linear program Pareto-efficient solutions

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Modelling and flexible predictive control of buildings space-heating demand in district heating systems

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ENERGY 2019年 188卷 116042-000页

作者： Aoun, Nadine Baviere, Roland Vallee, Mathieu Aurousseau, Antoine Sandou, Guillaume Univ Paris Saclay Univ Paris Sud CNRS L2SCent Supelec F-91190 Gif Sur Yvette France CEA LITEN 17 Rue Martyrs F-38054 Grenoble France ADEME 20 Ave Gresille F-49000 Angers France

This paper presents and demonstrates, by numerical simulation, a mixed-integer linear programming (MILP)-based Model Predictive Control (MPC) strategy for space-heating demand in buildings connected to a district heating system. The proposed MPC deals with space-heating demand with extended flexibility. It exploits thermal inertia, inherently present in the building and its heating system, to optimally plan space-heating load in anticipation of weather conditions and energy cost variations. MPC is based on a reliable Reduced-Order Model (ROM). Heating circuit and internal mass are carefully modelled within the ROM structure since these elements can be used for short-term heat storage and therefore play an important role in demand-side management. As for the model parameters identification, training data is restricted to non-intrusive, easily accessible measurements available at the substation level. The model identification approach and control strategy are applied to a well-insulated radiator-heated case-study building simulator developed in Modelica. Results show that the proposed ROM is reliable enough for an MPC application. Compared to conventional weather-compensation control, flexible MILP-based MPC proved to be cost-efficient, while preserving a decent indoor thermal comfort level. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： mixed-integer linear program Model predictive control Reduced order building model Lumped capacitance model Parameters identification Building thermal dynamic simulation

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Optimization for vaccination demand allocation and distribution routes in pandemics based on a hierarchy decision model

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COMPUTERS & INDUSTRIAL ENGINEERING 2023年第1期184卷

作者： Guo, Haixiang Gao, Lijuan Shi, Yong Wu, Yang Wang, Lei Zhang, Wenkai China Univ Geosci Sch Econ & Management Wuhan 430074 Peoples R China China Univ Geosci Inst Nat Disaster Risk Prevent & Emergency Managem Wuhan 430074 Peoples R China Hubei Prov Ctr Dis Control & Prevent Wuhan 430079 Peoples R China China Univ Geosci Sch Econ & Management Beijing 100083 Peoples R China Xian Univ Finance & Econ Sch Management Xian Peoples R China

Vaccination plays a significant role in interrupting the spread of pandemics, the process of moving the vaccine from the distribution center (DC) through the vaccination station and ultimately to the consumer involves many decisions. Which vaccination stations are open each day, how to allocate demand residents to the open stations, how many medical personnel to arrange at the open stations and the route of refrigerated vehicles to deliver vaccines to the open stations are issues that need to be addressed in this process. To improve the efficiency of vaccination and vaccine delivery during the actual vaccination scheduling process and to reduce the total cost, this study constructs two levels to describe the above problems and proposes a hierarchical decision mixedinteger linear program (MILP) that combines vaccine delivery and vaccination that jointly addresses the problems involved in both hierarchies. A case study of the COVID-19 vaccine administered at the Center for Disease Control and Prevention (CDC) in Hongshan District, Wuhan City, China, is then given to demonstrate the feasibility of the MILP and to highlight the managerial implications. It was found that opening more vaccination stations could reduce vaccination travel costs for the demand communities, opening a reasonable number of stations and rationally allocating the demand communities to these stations could reduce the costs of the whole system. This model also provides guidance for the CDC to address similar problems and has the potential to assist in the scheduling of public medical materials.

关键词： Pandemic and crisis Vaccination stations mixed-integer linear program Demand allocation

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