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An optimization framework for scheduling of converter aisle operation in a nickel smelting plant

COMPUTERS & CHEMICAL ENGINEERING 2018年 119卷 195-214页

作者： Ewaschuk, Christopher M. Swartz, Christopher L. E. Zhang, Yale McMaster Univ Dept Chem Engn 1280 Main St West Hamilton ON L8S 4L8 Canada Vale Base Met Technol Dev Mississauga ON L5K 1Z9 Canada TMOR Inc 55 Page Cres Burlington ON L7L 7N9 Canada

The scheduling of converter aisle operation in a nickel smelting plant is a complex task with significant ramifications to plant profitability and production. An optimization-based scheduling formulation is developed using a continuous-time paradigm to accurately represent event timings. The formulation accounts for environmental restrictions on sulfur dioxide emissions, using event timing constraints. Flash furnaces are characterized by a continuous inlet flow and intermittent, discrete material removal, which is captured via novel semi-continuous modeling. An innovative sequencing and symmetry-breaking scheme is introduced to exploit identical units operating in parallel. A rolling horizon feature is included to accommodate real-time optimization. Tightening constraints are developed to improve the computational performance. A unique, multi-tiered procedure enhances the practicality of the solution and supports additional operability objectives, without compromising the optimality of the primary objective. The success of the approach is demonstrated via case studies arising from industrial production scenarios. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Scheduling Continuous-time formulation Semi-continuous operation mixed-integer linear programming Nickel smelting Tiered optimization

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A State Transition MIP Formulation for the Unit Commitment Problem

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IEEE TRANSACTIONS ON POWER SYSTEMS 2018年第1期33卷 736-748页

作者： Atakan, Semih Lulli, Guglielmo Sen, Suvrajeet Univ Southern Calif Dept Ind & Syst Engn Los Angeles CA 90007 USA Univ Lancaster Dept Management Sci Lancaster LA1 4YW England

In this paper, we present the state-transition formulation for the unit commitment (UC) problem. This formulation uses new decision variables that capture the state transitions of the generators, instead of their on/off statuses. We show that this new approach produces a formulation which naturally includes valid inequalities, commonly used to strengthen other formulations. We demonstrate the performance of the state-transition formulation and observe that it leads to improved solution times especially in longer time-horizon instances. As an important consequence, the new formulation allows us to solve realistic instances in less than 12 minutes on an ordinary desktop PC, leading to a speed-up of a factor of almost two, in comparison to the nearest contender. Finally, we demonstrate the value of considering longer planning horizons in UC problems.

关键词： mixed-integer linear programming unit commitment

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Scheduling and Pricing of Energy Generation and Storage in Power Systems

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IEEE TRANSACTIONS ON POWER SYSTEMS 2018年第4期33卷 4308-4322页

作者： Khatami, Roohallah Parvania, Masood Khargonekar, Pramod P. Univ Utah Dept Elect & Comp Engn Salt Lake City UT 84108 USA Univ Calif Irvine Dept Elect Engn & Comp Sci Irvine CA 92697 USA

This paper proposes a fundamental model for continuous-time scheduling and marginal pricing of energy generation and storage in day-ahead power systems operation. The paper begins with formulating the economic operation problem of power systems with generating units and energy storage (ES) devices as a continuous-time optimal control problem, where the Lagrange multiplier trajectory associated with the continuous-time power balance constraint is proven to be the marginal price of energy generation and storage. The marginal price is calculated in closed-form, which reveals that in addition to the incremental cost rates of generating units, the marginal price embeds the financial ES charging offers and discharging bids that are defined as incremental charging utility and incremental discharging cost rates. This paper shows that the adjoint function associated with the ES state equation establishes a temporal dependence between the marginal prices during the ES charge and discharge states. A function space-based method is developed to solve the proposed model, which converts the continuous-time problem into a mixed-integer linear programming problem with finite dimensional decision space. The features of the proposed scheduling and pricing models are demonstrated using numerical studies conducted on the IEEE Reliability Test System.

关键词： Continuous-time optimal control energy storage marginal price mixed-integer linear programming

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An integrated approach for the rectangular delineation of management zones and the crop planning problems

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COMPUTERS AND ELECTRONICS IN AGRICULTURE 2019年 164卷 104925-000页

作者： Cid-Garcia, Nestor M. Jorge Ibarra-Rojas, Omar CONACYT CentroGeo Aguascalientes 20313 Mexico Univ Autanoma Nuevo Lean Fac Ciencias Fis Matemat San Nicolas De Los Garza Mexico

This article proposes an integration of the Delineation of Rectangular Management Zones (DRMZ) with the Crop Planning Problem (CPP) in precision agriculture. The first problem consists in partitioning the agricultural fields into chemical and physical management zones satisfying a specific homogeneity level considering the soil properties. These partitions are commonly used to improve agricultural practices such as fertilization, irrigation and pests control, to name a few. The second problem considers the management zones, to determine the best crop for each plot maximizing the profit. We propose an integrated optimization problem determining the decisions of both problems simultaneously. The latter problem is formulated through a non-linear program, and we implement linearization techniques to obtain high-quality solutions with a commercial solver for instances generated at random based on real-data of agricultural activities in Mexico. We compare our integrated method to a sequential approach based on solving the DRMZ that minimizes the number of management zones, and then, finding a solution for the CPP. Numerical results for the integrated method restricted to the number of management zones found by the sequential one show an average increment of 1.77% in the profit compared to the sequential approach, but the average increment can be up to 5.38% when there are no limitations for the number of management zones. Finally, a sensitivity analysis considering variability for the amount of water shows that it may be recommended to define a non-deterministic approach in further research due to the significant changes in the obtained profits.

关键词： Delineation of rectangular management zones Crop planning Integrated optimization approach mixed-integer linear programming

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A Novel Direct Load Control Testbed for Smart Appliances

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ENERGIES 2019年第17期12卷 3336页

作者： Garrido-Zafra, Joaquin Moreno-Munoz, Antonio Gil-de-Castro, Aurora Palacios-Garcia, Emilio J. Moreno-Moreno, Carlos D. Morales-Leal, Tomas Univ Cordoba Elect & Comp Engn Dept E-14071 Cordoba Spain Aalborg Univ Dept Energy Technol DK-9220 Aalborg Denmark Univ Cordoba Elect Engn Dept E-14071 Cordoba Spain

The effort to continuously improve and innovate smart appliances (SA) energy management requires an experimental research and development environment which integrates widely differing tools and resources seamlessly. To this end, this paper proposes a novel Direct Load Control (DLC) testbed, aiming to conveniently support the research community, as well as analyzing and comparing their designs in a laboratory environment. Based on the LabVIEW computing platform, this original testbed enables access to knowledge of major components such as online weather forecasting information, distributed energy resources (e.g., energy storage, solar photovoltaic), dynamic electricity tariff from utilities and demand response (DR) providers together with different mathematical optimization features given by General Algebraic Modelling System (GAMS). This intercommunication is possible thanks to the different applications programming interfaces (API) incorporated into the system and to intermediate agents specially developed for this case. Different basic case studies have been presented to envision the possibilities of this system in the future and more complex scenarios, to actively support the DLC strategies. These measures will offer enough flexibility to minimize the impact on user comfort combined with support for multiple DR programs. Thus, given the successful results, this platform can lead to a solution towards more efficient use of energy in the residential environment.

关键词： demand response direct load control home energy management system mixed-integer linear programming

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Dynamic reconfiguration of three-phase unbalanced distribution networks

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2018年 99卷 1-10页

作者： Zhai, H. F. Yang, M. Chen, B. Kang, N. Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Shandong Peoples R China Argonne Natl Lab Energy Syst Div Argonne IL 60439 USA

The increasing penetration of distributed generations (DGs) and variable loads introduces significant power fluctuations to distribution networks, rendering conventional reconfiguration strategies ineffective. In the context of an active distribution network (ADN), remote control switches can be operated in real time through a centralized control scheme. Therein the distribution network topology can be configured in a flexible and dynamic manner capable of adapting to time-varying load demand and DG output. This paper presents a dynamic reconfiguration approach for a three-phase unbalanced distribution network. The ADN topology is optimized for the look-ahead time periods and is adaptive to the time-varying load demand and DG output while minimizing the daily power loss costs. To improve the calculation efficiency, several linearization methods are introduced to formulate the dynamic reconfiguration as a mixed-integer linear programming problem, which can be effectively solved using off-the-shelf solvers. The effectiveness of the proposed approach is verified by the test results obtained on a modified IEEE 34 node test feeder.

关键词： Distributed generation mixed-integer linear programming Reconfiguration Unbalanced distribution network

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An accelerated extended cutting plane approach with piecewise linear approximations for signomial geometric programming

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JOURNAL OF GLOBAL OPTIMIZATION 2018年第3期70卷 579-599页

作者： Zhan, Yiduo Zheng, Qipeng P. Tseng, Chung-Li Pasiliao, Eduardo L. Univ Cent Florida Dept Ind Engn & Management Syst Orlando FL 32816 USA UNSW UNSW Business Sch Sydney NSW 2052 Australia Air Force Res Lab 101 West Eglin Blvd Eglin AFB FL 32542 USA

This paper presents a global optimization approach for solving signomial geometric programming (SGP) problems. We employ an accelerated extended cutting plane (ECP) approach integrated with piecewise linear (PWL) approximations to solve the global optimization of SGP problems. In this approach, we separate the feasible regions determined by the constraints into convex and nonconvex ones in the logarithmic domain. In the nonconvex feasible regions, the corresponding constraint functions are converted into mixed integer linear constraints using PWL approximations, while the other constraints with convex feasible regions are handled by the ECP method. We also use pre-processed initial cuts and batched cuts to accelerate the proposed algorithm. Numerical results show that the proposed approach can solve the global optimization of SGP problems efficiently and effectively.

关键词： Signomial geometric programming Piecewise linear approximation mixed-integer linear programming Accelerated extended cutting plane

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Intruder alert! Optimization models for solving the mobile robot graph-clear problem

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CONSTRAINTS 2018年第3期23卷 335-354页

作者： Morin, Michael Castro, Margarita P. Booth, Kyle E. C. Tran, Tony T. Liu, Chang Beck, J. Christopher Univ Laval Dept Operat & Decis Support Syst Quebec City PQ Canada Univ Toronto Dept Mech & Ind Engn Toronto ON Canada

We develop optimization approaches to the graph-clear problem, a pursuit-evasion problem where mobile robots must clear a facility of intruders. The objective is to minimize the number of robots required. We contribute new formal results on progressive and contiguous assumptions and their impact on algorithm completeness. We present mixed-integer linear programming and constraint programming models, as well as new heuristic variants for the problem, comparing them to previously proposed heuristics. Our empirical work indicates that our heuristic variants improve on those from the literature, that constraint programming finds better solutions than the heuristics in run-times reasonable for the application, and that mixed-integer linear programming is superior for proving optimality. Given their performance and the appeal of the model-and-solve framework, we conclude that the proposed optimization methods are currently the most suitable for the graph-clear problem.

关键词： Pursuit-evasion Graph-clear problem Constraint programming mixed-integer linear programming Optimization Mobile robotics

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Multiobjective Robust Power System Expansion Planning Considering Generation Units Retirement

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IEEE SYSTEMS JOURNAL 2018年第3期12卷 2664-2675页

作者： Mavalizadeh, Hani Ahmadi, Abdollah Gandoman, Foad Haidari Siano, Pierluigi Shayanfar, Heidar Ali Iran Univ Sci & Technol Ctr Excellence Power Syst Automat & Operat Sch Elect Engn Tehran *** Iran Univ New South Wales Australian Energy Res Inst Sch Elect Engn & Telecommun Sydney NSW 2052 Australia Free Univ Brussels Res Grp MOBI Mobil Logist & Automot Technol Res C B-1050 Brussels Belgium Univ Salerno Dept Ind Engn I-84084 Salerno Italy

This paper presents a mixed-integer linear robust multiobjective model for the expansion planning of an electric power system. An information-gap decision theory-based framework is proposed to take into account the uncertainties in electrical demand and new power system elements prices. The model is intended to increase the power system resistance against the uncertainties caused by forecast errors. The normal boundary intersection method is used to obtain the Pareto front of the multiobjective problem. Since the planning problem is a large-scale problem, the model is kept linear using the Big M linearization technique that is able to significantly decrease the computational burden. The fuel transportation and availability constraints are taken into account. The model also enables the system planner to build new fuel transportation routes whenever it is necessary. The generating units' retirement is also incorporated into the model, and the simulation results are showed to the advantages of incorporating units' retirement in the power system expansion planning model instead of considering it separately. The proposed multiobjective method is applied to the Garver 6-bus, IEEE 24-bus, and IEEE 118-bus test systems, and the results are compared with the well-known epsilon-constraint method.

关键词： Generation expansion planning information-gap decision theory mixed-integer linear programming normal boundary intersection transmission expansion planning

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A new MILP model proposal in feed formulation and using a hybrid-linear binary PSO (H-LBP) approach for alternative solutions

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NEURAL COMPUTING & APPLICATIONS 2018年第2期29卷 537-552页

作者： Sahman, Mehmet Akif Altun, Adem Alparslan Dundar, Abdullah Oktay Selcuk Univ Guneysinir Vocat Sch TR-42490 Konya Turkey Selcuk Univ Fac Technol Dept Comp Engn TR-42075 Konya Turkey Selcuk Univ Akoren Vocat Sch TR-42460 Konya Turkey

Large-scale feed factories may have multiple production and storage facilities. Any production facility uses its own available raw materials while performing feed formulation. However, ensuring a reasonable cost is achieved, and the desired quality criteria are met, may require obtaining a certain amount of raw material from other facilities. Selecting a specific amount of raw materials among many raw materials in different facilities requires many combinations to be tried out. Providing solutions, especially when there is a large amount of the raw material, may be costly and take more time. A new mixed-integer linear programming (MILP) model that specifies the type of material and the amount of the material to be selected from external facilities has been proposed in this study. When deterministic methods like MILP are used, only one solution result is obtained. However, when the decision-maker would like to see alternative results, solution constraints can be mitigated and a solution provided within the same or similar time. A new method named hybrid-linear binary PSO (H-LBP) has been proposed in this study for the problems that the decision-maker had limited time for and for which the solution results were required in a shorter time. Continuous particle swarm optimization, which works as a hybrid with linear programming, has been used in this method. The new model proposed in this study was tested on the mixed feeds for sheep, cattle and rabbit species by using both MILP and the proposed H-LBP methods. Raw materials determined by the model were added to the mixture, and the cost in each of the three species was observed to go down. In addition, different alternative solutions at reasonable cost and similar quality were presented to the producer/decision-maker in a shorter time.

关键词： Binary particle swarm optimization linear programming mixed-integer linear programming Feed mix optimization

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