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Volt/var optimization of unbalanced distribution feeders via mixed integer linear programming

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2015年第Nov.期72卷 40-47页

作者： Borghetti, Alberto Napolitano, Fabio Nucci, Carlo Alberto Univ Bologna I-40126 Bologna Italy

The paper presents a mixed integer linear programming (MILP) model for the solution of the three-phase volt/var optimization (WO) of medium voltage unbalanced distribution feeders. The WO of a distribution feeder is aimed at calculating the most efficient operating conditions by means of the scheduling of transformers equipped with an on-load tap changer and distributed reactive power resources (such as embedded generators and switchable capacitors banks). The proposed model allows the representation of feeders composed by three-phase, two-phase, and single-phase lines, by transformers with different winding connections, by unbalanced wye- and delta-connected loads, by three-phase and single phase capacitor banks and embedded generators. The accuracy of the results is verified by using IEEE test feeders. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Power distribution feeders Unbalanced networks Volt/var optimization mixed integer linear programming

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Single elevator scheduling problem with complete information: An exact model using mixed integer linear programming

Single elevator scheduling problem with complete information...

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American Control Conference

作者： Jingyang Xu Tianke Feng Innovative Decisions and Analytics L.L.C.

ISBN: (纸本)9781467386838

In this paper, we model a single elevator scheduling problem as a mixed integer linear program (MILP). Based on an industrial prototype model for elevator moving dynamics, the nonlinear travel activities for the elevator are linearized in the scheduling problem. We propose a set of cutting planes that accelerate the computation time for solving the MILP for a set of testing cases under different scenarios. For the first time, an exact scheduling model is modeled with MILP, and the elevator moving dynamics model is based on a high-accuracy industrial prototype model. According to the model structure, it can be easily extended to various objectives and can be easily implemented. This model can serve as benchmarks for other approaches in simulation.

关键词： Elevators Dynamic scheduling Mathematical model Job shop scheduling Computational modeling Prototypes Automobiles Elevators Job shop scheduling dynamic scheduling Automobiles mixed integer linear programming Computational modeling original mold Mathematical Model PROTOTYPE Cars CASING INSPECTION computational time

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A multi-period mixed integer linear programming model for water and energy supply planning in Kuwait

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CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY 2015年第2期17卷 485-499页

作者： AlQattan, Nael Ross, Mark Sunol, Aydin K. Univ S Florida Coll Engn Tampa FL 33620 USA

The demand for water often necessitates desalination, particularly in arid coastal environments. Desalination is often integrated with electrical cogeneration. The demands for water and electricity change over time and are subject to uncertainty. A country-wide large-scale energy and water cogeneration planning model for Kuwait is formulated as a multi-period mixed integer linear programming problem and solved to minimize the net present value over the time period of 2013-2050. Five different plant technology options were considered for desalination and cogeneration including Oil & Multi Stage Flash, Natural Gas & Multi-Effect Distillation, Natural Gas & Reverse Osmosis, Solar Energy & Multi-Effect Distillation, and Solar Energy & Reverse Osmosis. Both water and energy usage in Kuwait and data from existing plants were utilized in providing the parameters and forecasts necessary for solution of the mathematical programming model. The model provides technology choice and associated capacity decisions for existing plants, new plants at green sites, and existing plant capacity expansions as well as their timing to meet the demands.

关键词： Cogeneration mixed integer linear programming Capacity expansion Desalination

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A mixed integer linear programming approach to schedule the operating room

A mixed integer linear programming approach to schedule the ...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： F. MAAROUFI H. CAMUS O. KORBAA MARS équipe OSS ENSI Manouba Manouba Tunisia LAGIS équipe OSL Ecole Centrale de Lille Villeneuve d'Ascq France MARS équipe OSS ISITCom Hamam Sousse Sousse Tunisia

ISBN: (纸本)9781509018987

the problem studied in this paper is to allocate and to sequence the elective operation on operating rooms (ORs). We develop a mixed integer linear programming (MILP) model to solve this problem. Decisions in this model include the allocation of operations to material resources and human resources, the starting time of them and the starting time for each surgeon. To show the efficiency of this model, we decide to compare it with a constraints programming (CP) approach. The performance of these models is tested using a benchmark of the literature. The results indicate the efficiency of the MILP model compared with the CP model in terms of computational time.

关键词： constraint programming health care operating rooms mixed integer linear programming

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The Planning of Distribution Network Containing Distributed Generators Based on mixed integer linear programming 5

The Planning of Distribution Network Containing Distributed ...

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5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT)

作者： Shi, Jinyue Qiao, Ying Wang, Yingrui Wen, Junqiang Tong, Jingjing Zhang, Jianhua North China Elect Power Univ Sch Elect & Elect Engn Beijing Peoples R China

ISBN: (纸本)9781467371063

currently, the methods for solving the planning of distribution network (DN) are meta-heuristic algorithms whose computational efficiency is low and the results are not accurate. Therefore, this paper uses the advanced mixed integer linear programming (MILP) technology to model the multi-conductor DN planning containing the allocation of distributed generator (DG). Firstly, replace power flow calculation with an equivalent cone programming, then remove the product terms of binary and continuous variables, and finally use polyhedral models which are linear to approximate the planning model. In addition, as the siting and sizing of DG are added to the network planning, the situation that part of the loads are supplied by the DG separately perhaps appear thus leading to the appearance of loops. So the spanning tree (ST) constraints are introduced to the model to ensure the radiation of the DN. Finally, 23-node distribution system is used to simulate the above-mentioned model, and the results show the effectiveness and efficiency of the proposed model.

关键词： distributed generator mixed integer linear programming distribution network planning multi-conductor planning spanning tree constraints

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Smart Residential Energy Scheduling Utilizing Two Stage mixed integer linear programming

Smart Residential Energy Scheduling Utilizing Two Stage Mixe...

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North American Power Symposium (NAPS)

作者： Amini, M. H. Frye, Justin Ilic, Marija D. Karabasoglu, O. Carnegie Mellon Univ Dept Elect & Comp Engn Pittsburgh PA 15213 USA Sun Yat Sen Univ Carnegie Mellon Univ Joint Inst Pittsburgh PA USA Delft Univ Technol Fac Technol Policy & Management Delft Netherlands Shunde Int SYSU CMU Joint Res Inst Shunde Guangdong Peoples R China

ISBN: (纸本)9781467373890

In this paper, we design and evaluate the feasibility of a system which minimizes residential electricity cost of individual homes by shifting demand over a daily forecast price cycle. Ideally, our system will accept use-time preferences from consumers and optimize their appliances' operation around those given patterns. However, using the system to recommend optimum use-times to consumers is also possible by accepting ideal use preferences from an external load manager and computing the cost savings of these preferences relative to the cost of the consumer's current use patterns. We implement the optimization problem in two stages by using mixed integer linear programming (MILP). In the first stage, we obtain the optimum scheduling for appliances to be connected to the outlet;the output of this stage only shows the hours that we can use the appliance and does not reflect the actual consumption hours of each appliance. In the second stage, we model the random behavior of users via Monte Carlo simulation by running the appliances within the times they receive power, specified in the first stage. Finally, we evaluate the effectiveness of the proposed model in terms of cost savings by considering three appliances and four pricing schemes.

关键词： Monte Carlo methods domestic appliances integer programming linear programming pricing MILP Monte Carlo simulation optimum scheduling pricing scheme residential electricity cost minimization smart residential energy scheduling two stage mixed integer linear programming Home appliances Load management Mathematical model Optimization Pricing Real-time systems Schedules Appliances Monte Carlo technique Pricing load management real-time systems integer programming linear programming Mathematical Model Consumers mixed integer linear programming cost analysis double-stage

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mixed integer linear programming model for integrating cell formation, group layout and group scheduling

Mixed integer linear programming model for integrating cell ...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Sherif A. Fahmy Department of Industrial Engineering Cairo University Giza Egypt

Cellular manufacturing systems (CMS) are production systems that typically comprise a number of manufacturing cells served by a centralized material handling system. Designing such systems includes three major decisions; cell formation (CF), group layout (GL), and group scheduling (GS). Traditionally, these three decisions have been dealt with separately, which has usually lead to less than optimal system performance. In this paper, a new mixed integer linear programming (MILP) model is proposed for the integrated CF, GL and GS problem, to efficiently design and operate CMSs. The model solves the integrated problem, taking into consideration intercellular and intracellular transportation times to determine the optimal cell formation, layout of machines and schedule of parts on the machines, simultaneously. Sequence-dependent set up times are also considered in the model. The performance of the model is tested by solving problems previously introduced in the literature considering two objectives; minimizing the makespan or minimizing the mean flow time in the system. The results show that the proposed model is efficient in solving small to medium-sized problems.

关键词： Mathematical model Layout Transportation Job shop scheduling Manufacturing mixed integer linear programming

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mixed integer linear programming Models for Selecting Ground-Level Ozone Control Strategies

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ENVIRONMENTAL MODELING & ASSESSMENT 2014年第6期19卷 503-514页

作者： Hsu, Wei-Che Rosenberger, Jay M. Sule, Neelesh V. Sattler, Melanie L. Chen, Victoria C. P. Univ Texas Arlington Dept Ind & Mfg Syst Engn Arlington TX 76019 USA Providence Engn & Environm Grp Irving TX 75038 USA Univ Texas Arlington Dept Civil Engn Arlington TX 76019 USA

The traditional strategy for ground-level ozone control is to apply emission reductions across the board throughout certain time periods and locations. In this paper, we study various mixed integer linear programming (MILP) models that seek to select targeted control strategies for the Dallas Fort-Worth (DFW) region to reduce emissions, in order to achieve the State Implementation Plan (SIP) requirements with minimum cost. Statistics and optimization methods are used to determine a potential set of cost-effective control strategies for reducing ozone. These targeted control strategies are specified for different types of emission sources in various time periods and locations. Three MILP models, a static model, a sequential model, and a dynamic model, are studied in this research. These different MILP models allow decision makers to study how the targeted control strategies change under different circumstances. Meanwhile, two types of auxiliary variables are considered as supplemental control strategies in the optimization if the current set of control strategies is unable to reduce ozone to complywith the 8-h ozone standard. Results fromthe differentmodels can provide decisionmakers with information concerning how the effectiveness of the control strategies varies with daily emission patterns and meteorology.

关键词： mixed integer linear programming Control strategies Auxiliary variables Ground-level ozone

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linear or mixed integer programming in long-term energy systems modeling - A comparative analysis for a local expanding heating system

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ENERGY 2023年 283卷

作者： Vilen, Karl Ahlgren, Erik O. Chalmers Univ Technol Dept Space Earth & Environm Div Energy Technol SE-41396 Gothenburg Sweden

Most computer models used in energy systems optimization modeling studies are formulated using linear equations. However, since linear formulations do not always well reflect real-world conditions, they may not always be adequate as policy and support tools. This is particularly the case for local system studies attempting to represent technologies at the individual scale, as in the case for local heating system modeling. Thus, the aim of this paper is to investigate differences in the resulting heating solutions and model solution times for a local expanding heating system. Three different investment cost structures for individual and district heating solutions for the heating of new housing are investigated using linear and mixed integer linear programming. The results show that the use of district heating is higher for the cost structures that use mixed integer linear programming than it is for the linear cost structures. This result is attributed mainly to the fact that individual air-to-water heat pumps benefit from the linear equation formulation due to its high coefficient of performance during summertime. This finding is important to consider when modeling local energy systems. The solution time is, however, significantly shorter for the linear formulations than for the mixed integer linear formulations.

关键词： Housing District heating Local energy system modeling TIMES mixed integer linear programming linear programming

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Model Predictive Control of Central Chiller Plant With Thermal Energy Storage Via Dynamic programming and mixed-integer linear programming

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2015年第2期12卷 565-579页

作者： Deng, Kun Sun, Yu Li, Sisi Lu, Yan Brouwer, Jack Mehta, Prashant G. Zhou, MengChu Chakraborty, Amit Univ Illinois Dept Mech Sci & Engn Urbana IL 61801 USA Siemens Corp Corp Technol Princeton NJ 08540 USA New Jersey Inst Technol Dept Elect & Comp Engn Newark NJ 07102 USA King Abdulaziz Univ Dept Elect & Comp Engn Jeddah 21413 Saudi Arabia NIST Gaithersburg MD 20899 USA Univ Calif Irvine Dept Mech & Aerosp Engn Irvine CA 92697 USA

This work considers the optimal scheduling problem for a campus central plant equipped with a bank of multiple electrical chillers and a thermal energy storage (TES). Typically, the chillers are operated in ON/OFF modes to charge TES and supply chilled water to satisfy the campus cooling demands. A bilinear model is established to describe the system dynamics of the central plant. A model predictive control (MPC) problem is formulated to obtain optimal set-points to satisfy the campus cooling demands and minimize daily electricity cost. At each time step, the MPC problem is represented as a large-scale mixed-integer nonlinear programming problem. We propose a heuristic algorithm to obtain suboptimal solutions for it via dynamic programming (DP) and mixed integer linear programming (MILP). The system dynamics is linearized along the simulated trajectories of the system. The optimal TES operation profile is obtained by solving a DP problem at every horizon, and the optimal chiller operations are obtained by solving an MILP problem at every time step with a fixed TES operation profile. Simulation results show desired performance and computational tractability of the proposed algorithm. Note to Practitioners-This work was motivated by the supervisory control need for a campus central plant. Plant operators have to decide a scheduling strategy to mix and match various chillers with a thermal energy storage to satisfy the campus cooling demands, while minimizing the operation cost. This work mathematically characterizes the system dynamics of a campus central plant and establishes a linear model to predict campus cooling load. It proposes a model predictive control (MPC) strategy to optimally schedule the campus central plant based on plant system dynamics and predicted campus cooling load. A heuristic algorithm is proposed to obtain suboptimal solutions for the MPC problem. The effectiveness and efficiency of the proposed approach are well demonstrated for the central pl

关键词： Central chiller plant dynamic programming heuristic algorithm mixed integer linear programming model predictive control supervisory control thermal energy storage

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