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Short-circuit-constrained transmission expansion planning with bus splitting flexibility

IET GENERATION TRANSMISSION & DISTRIBUTION 2018年第1期12卷 217-226页

作者： Gharibpour, Hassan Aminifar, Farrokh Bashi, Mazaher Haji Univ Tehran Sch Elect & Comp Engn Tehran 14395515 Iran Isfahan Univ Technol Sch Elect & Comp Engn Esfahan 84156 Iran

Incorporation of the short-circuit level constraints in the transmission expansion planning (TEP) has a direct impact on the final solution. Conventionally, in TEP models, a substation is tackled as a single node where are all transmission lines, power transformers, and generating units are connected to each other. However, bus splitting is a common option in most substations that divides the connected elements into two groups. Doing so, bus splitting can alter the flow path impedances and accordingly manage the short-circuit levels. Here, the short-circuit level constraints are modelled in terms of conventional TEP and bus splitting decision variables. The modelling process is very complex and some non-linear terms appear in the models. To have a tractable model in real-world problems, the non-linearities are converted to linear equivalents making the final TEP model conforming the mixed-integer linear programming format. The performance of the proposed model is examined on the 24-bus reliability test system. The results show that incorporation of the bus splitting option in the TEP problem decreases the total cost of the optimal expansion plan.

关键词： power transmission planning power transformers substations integer programming linear programming power transmission lines short-circuit-constrained transmission expansion planning bus splitting flexibility TEP models transmission lines power transformers generating units substations flow path impedances short-circuit level constraints bus splitting decision variables nonlinear terms mixed-integer linear programming 24-bus reliability test system

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Linepack planning models for gas transmission network under uncertainty

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2018年第2期268卷 688-702页

作者： Trung Hieu Tran French, Simon Ashman, Rhys Kent, Edward Univ Warwick Dept Stat Coventry CV4 7AL W Midlands England Natl Grid House Warwick Technol Pk Warwick CV34 6DA England

Open market transient behaviours create challenges for National Grid, the UK gas transmission network operator, in meeting limits on pressure and linepack, i.e. the quantity of gas in the network. In this paper, four mixed-integer linear programming models are proposed for the optimal linepack planning to compensate for the fluctuation of gas demand. The first model minimises total deviation between planned and targeted linepacks such that all the customer's demand and other network constraints are satisfied. The second model determines actions, including timings, to minimise total cost for resolving the gas deficit. We then extend this to a third model to deal with the periodical supply shortfall in the gas transmission network, and a fourth model to investigate the impact of compressor failure on the linepack management. The efficiency of these models is investigated and validated using real case study data. Experimental results show that our models can produce the optimal linepack plans under certain scenarios that current tools at National Grid cannot achieve. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Gas network Linepack planning mixed-integer linear programming Supply shortfall Compressor failure

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

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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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Capacitated path-aggregation constraint model for arc disruption in networks

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2018年 109卷 225-238页

作者： Karakose, Gokhan McGarvey, Ronald G. Univ Missouri Dept Ind & Mfg Syst Engn Columbia MO 65211 USA Univ Missouri Harry S Truman Sch Publ Affairs Columbia MO 65211 USA

Path-aggregation constraint (PAC) models can be used to represent flows across networks with specific origin-destination demand pairs without requiring explicit enumeration of all potential paths, greatly reducing the computational burden needed analyze a network's performance in the event of arc disruptions. This paper presents new PAC models for examining arc disruptions on networks, providing the first known models to extend such PACs to capacitated arcs. Extensive computational testing demonstrates that these novel arc-capacitated models do not significantly increase computational burden beyond that required by arc-uncapacitated models, while avoiding the suboptimal performance achieved when uncapacitated models are applied to arc capacitated networks.

关键词： Network disruption models Network flow models mixed-integer linear programming

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Towards integrated multi-modal municipal energy systems: An actor-oriented optimization approach

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APPLIED ENERGY 2018年 228卷 2009-2023页

作者： Scheller, Fabian Burgenmeister, Balthasar Kondziella, Hendrik Kuhne, Stefan Reichelt, David G. Bruckner, Thomas Univ Leipzig IIRM Leipzig Germany IWB Basel Switzerland Univ Comp Ctr URZ Leipzig Germany Inst Appl Informat InfAI Leipzig Germany

Against the backdrop of a changing political, economic and ecological environment, energy utilities are facing several challenges in many countries. Due to an increasing decentralization of energy systems, the conventional business could be undermined. Yet the reliable integration of small-scale renewable technologies and associated system transformations could represent an opportunity as well. Municipal energy utilities might play a decisive role regarding successful transition. For better decision-making, they need to investigate under which conditions certain novel business cases can become a sustainable part of their future strategy. The development of the strategy is a challenging task which needs to consider different conditions as business portfolio, the customer base, the regulatory framework as well as the market environment. Integrated Multi-Modal Energy System (IMMES) models are able to capture necessary interactions. This research introduces a model-driven decision support system called Integrated Resource Planning and Optimization (IRPopt). Major aim is to provide managerial guidance by simulating the impact of business models considering various market actors. The mixed integer linear programming approach exhibits a novel formal interface between supply and demand side which merges technical and commercial aspects. This is achieved by explicit modeling of municipal market actors on one layer and state-of-the-art technology components on another layer as well as resource flow relations and service agreements mechanism among and between the different layers. While this optimization framework provides a dynamic and flexible policy-oriented, technology-based and actor-related assessment of multi-sectoral business cases, the encapsulation in a generic software system supports the facilitation. Based on the actor oriented dispatch strategy, flexibility potential of community energy storage systems is provided to demonstrate a real application.

关键词： Actor-oriented optimization Integrated multi-modal energy system mixed-integer linear programming Model-driven decision systems Energy utility business portfolio planning

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Evasion-Robust Classification on Binary Domains

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ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA 2018年第4期12卷 1–32页

作者： Li, Bo Vorobeychik, Yevgeniy Univ Calif Berkeley Berkeley CA 94720 USA Vanderbilt Univ 221 Kirkland Hall Nashville TN 37235 USA 5221 Panama Ave Richmond CA 94804 USA 401 Bowling Ave 7 Nashville TN 37212 USA

The success of classification learning has led to numerous attempts to apply it in adversarial settings such as spam and malware detection. The core challenge in this class of applications is that adversaries are not static, but make a deliberate effort to evade the classifiers. We investigate both the problem of modeling the objectives of such adversaries, as well as the algorithmic problem of accounting for rational, objective-driven adversaries. We first present a general approach based on mixed-integer linear programming (MILP) with constraint generation. This approach is the first to compute an optimal solution to adversarial loss minimization for two general classes of adversarial evasion models in the context of binary feature spaces. To further improve scalability and significantly generalize the scope of the MILP-based method, we propose a principled iterative retraining framework, which can be used with arbitrary classifiers and essentially arbitrary attack models. We show that the retraining approach, when it converges, minimizes an upper bound on adversarial loss. Extensive experiments demonstrate that the mixed-integer programming approach significantly outperforms several state-of-the-art adversarial learning alternatives. Moreover, the retraining framework performs nearly as well, but scales significantly better. Finally, we show that our approach is robust to misspecifications of the adversarial model.

关键词： Design Algorithms Performance Adversarial classification classifier evasion robust learning mixed-integer linear programming adversarial examples

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Designing and solving a reverse logistics network for polyethylene terephthalate bottles

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JOURNAL OF CLEANER PRODUCTION 2018年 195卷 605-617页

作者： Paydar, Mohammad Mandi Olfati, Marjan Babol Noshirvani Univ Technol Dept Ind Engn Babol Sar Iran Iran Univ Sci & Technol Dept Ind Engn Tehran Iran

In recent years, factors such as lack of valuable resources, economic importance, environmental concerns and increased customers' awareness caused the researchers to consider the design of a reverse logistics network. In this study, the process of collecting and remanufacturing polyethylene terephthalate bottles was considered. A mixed-integer linear programming model for a reverse logistics network was designed. A real case study of polyethylene terephthalate bottles was implemented in one of the northern cities of Iran to show the applicability of the model. The objective function was to minimize the total costs. In the current network model, new collection centers and remanufacturing centers can be opened. Also, the optimal number and location of the facilities along with the flow between them were determined. The obtained results clearly demonstrated that the proposed model is efficient and applicable. Moreover, this paper provided effective and reliable managerial implication solutions for decision makers of polyethylene terephthalate bottle reverse logistics network. Two meta-heuristic algorithms, namely the genetic algorithm and imperialist competitive algorithm, were applied to solve large-scale problems. The efficiency of the two proposed algorithms and the optimum solution of the LINGO software were compared in terms of the CPU time and objective function value. To achieve reliable results from these algorithms, parameter setting was utilized by the Taguchi method. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Reverse logistics Genetic algorithms Imperialist competitive algorithm Polyethylene terephthalate bottle mixed-integer linear programming

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Optimal Meeting Scheduling in Smart Commercial Building for Energy Cost Reduction

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IEEE TRANSACTIONS ON SMART GRID 2018年第4期9卷 3060-3069页

作者： Chai, Bo Costa, Alberto Ahipasaoglu, Selin Damla Yuen, Chau Yang, Zaiyue State Grid Corp China Global Energy Interconnect Res Inst Beijing 102209 Peoples R China Natl Univ Singapore Singapore Singapore Swiss Fed Inst Technol Future Resilient Syst Singapore Singapore Singapore Univ Technol & Design Singapore 138682 Singapore Zhejiang Univ State Key Lab Ind Control Technol Hangzhou 310027 Zhejiang Peoples R China

In this paper, we consider the optimal meeting scheduling problem in a commercial building over a fixed period of time, with the objectives of minimizing the cost of energy consumption by the air-conditioning system and possibly achieving more balanced power distribution. By considering a set of realistic factors, including the eligible time slots of attendees and energy consumption characteristics of meeting rooms, this problem is formulated as a constrained mixed-integer linear program, which then can be solved by an optimization solver, e.g., CPLEX. However, because the computation complexity increases dramatically with the problem size, a fast heuristic algorithm is proposed. The numerical simulations verify that the heuristic algorithm produces a near-optimal result.

关键词： Smart grid demand response management meeting scheduling mixed-integer linear programming score ranking

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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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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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