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Security-Constrained Optimal Scheduling of Transmission Outages With Load Curtailment

IEEE TRANSACTIONS ON POWER SYSTEMS 2018年第1期33卷 921-931页

作者： Liu, Jenny Kazemi, Mostafa Motamedi, Amir Zareipour, Hamidreza Rippon, Jim AltaLink Calgary AB T2A 7W7 Canada Univ Shahreza Esfahan *** Iran Alberta Elect Syst Operator Calgary AB T2P 0L4 Canada Univ Calgary Dept Elect & Comp Engn Calgary AB T2N 1N4 Canada

Transmission outage scheduling from a transmission facility owner's (TFO's) perspective in a deregulated electricity market has been one of the lesser explored topics in academia. This paper presents a security-constrained one-step optimal transmission outage scheduling model that can be used by any TFO. The proposed mixed-integer linear programming model incorporates a new load shedding methodology that allows transmission branches to radially connected and in-and-out connected buses to be taken out-of-service under outage and contingency conditions, which further improves its versatility. The proposed model is tested on two networks, a simple four-bus system and the 62-bus AltaLink 500 kV/240 kV backbone system in Alberta.

关键词： Contingency analysis DC power flow deregulatedmarket load curtailment mixed-integer linear programming Transmission outage scheduling

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Quality-Aware Control for Optimizing Meat Supply Chains 18

Quality-Aware Control for Optimizing Meat Supply Chains

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18th European Control Conference (ECC)

作者： Sprong, J. P. Lin, X. Maestre, J. M. Negenborn, R. R. Delft Univ Technol Dept Maritime & Transport Technol Delft Netherlands Univ Seville Dept Ingn Sistemas & Automat Seville Spain

ISBN: (纸本)9783907144008

Controlling food quality and reducing waste is one of the most challenging tasks in the food industry, as it is facing high rates of wastage, leading to negative environmental impact. This research focuses on improving the scheduling and control of the supply chain of Irish lamb meat using real-time quality and temperature information. Temperature controlled reefers and sensor technologies can be used to monitor and set the temperature during transport and storage. In order to minimize waste, while at the same time optimizing cooling and transport costs, a mathematical model is proposed. The model consists of two aspects. The quality aspect considers the shelf life of Irish lamb which is related to temperature. The logistic aspect considers supply chain scheduling. With this model, a strategy is proposed to determine the movements of meat, as well as the temperature setting of cooling equipment. Results of simulation experiments indicate a sustainable approach can reduce or even eliminate waste and decrease operational costs when real-time monitoring and control is used.

关键词： Fresh food logistics meat supply chain shelf life cooling costs quality-aware modeling mixed-integer linear programming

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Adaptive Two-stage Stochastic programming with an Analysis on Capacity Expansion Planning Problem

arXiv

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arXiv 2019年

作者： Basciftci, Beste Ahmed, Shabbir Gebraeel, Nagi Department of Business Analytics Tippie College of Business University of Iowa Iowa CityIA52242 United States H. Milton Stewart School of Industrial and Systems Engineering Georgia Institute of Technology AtlantaGA30332 United States

Problem Definition: Multi-stage stochastic programming is a well-established framework for sequential decision making under uncertainty by seeking policies that can be dynamically adjusted as uncertainty is realized. Often, e.g., due to contractual constraints, such flexible policies are not desirable, and the decision maker may need to commit to a set of actions for a certain number of periods. Two-stage stochastic programming might be better suited to such settings, where first-stage decisions do not adapt to the uncertainty realized. In this paper, we propose a novel alternative approach, named as adaptive two-stage stochastic programming, where each component of the decision policy requiring limited flexibility has its own revision point, a period prior to which the decisions are determined at the beginning of the planning until this revision point, and after which they are revised for adjusting to the uncertainty realized thus far until the end of the planning. We then analyze this approach over the capacity expansion planning problem, that may require limited flexibility over expansion decisions. Methodology/results: We provide a generic mixed-integer programming formulation for the adaptive two-stage stochastic programming problem with finite support, in particular for scenario trees, and show that this problem is NP-hard in general. Next, we focus on the capacity expansion planning problem, and derive bounds on the value of adaptive two-stage programming in comparison to the two-stage and multi-stage approaches in terms of revision points. We propose several heuristic solution algorithms based on this bound analysis. These algorithms either provide approximation guarantees or computational advantages in solving the resulting adaptive two-stage stochastic problem. Managerial implications: We provide insights on the choice of the revision times based on our analytical analysis. We further present an extensive computational study on a generation capacity expans

关键词： mixed-integer linear programming

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Emergency Medical System Design Using Kernel Search

Emergency Medical System Design Using Kernel Search

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IEEE Workshop on Complexity in Engineering (COMPENG)

作者： Janosikova, L'udmila Jankovic, Peter Univ Zilina Fac Management Sci & Informat Univ 1 Zilina 01026 Slovakia

ISBN: (纸本)9781538653388

The paper deals with location of the standby sites of emergency vehicles in a large-scale area. We propose a mathematical programming model that preserves the current number of vehicles and looks for better station location. The optimization criterion is to minimize the average response time. Large problem instances are intractable in a reasonable amount of time and that is why a modification of the kernel search heuristic is proposed to get an approximate solution. A computer simulation model is used to evaluate the current and the proposed system in the Slovak Republic. The model was calibrated using real data on emergency trips.

关键词： facility location multiple-source capacitated p-median problem kernel search mixed-integer linear programming agent-based computer simulation

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Operational optimization of energy systems, 25 years - established and promising use cases 16

Operational optimization of energy systems, 25 years - estab...

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16th International Symposium on District Heating and Cooling (DHC)

作者： Stange, Peter Matthees, Anja Sander, Thomas Tech Univ Dresden Inst Power Engn Chair Bldg Energy Syst & Heat Supply Helmholtzstr 14 D-01069 Dresden Germany

The operation of complex energy systems for the supply of heat and electricity leads to several questions regarding their optimal control, e.g. when to use which generator, when to load or unload energy storages or when to buy or sell energy. Usually it is a complex task to answer these questions with the aim of optimizing a specific objective and respecting all arising physical, technical and economic constraints. Since 25 years we are solving this problem for an energy provider of a medium-sized city with the aim of minimizing the operational costs. For this purpose, an own modelled mixed-integer linear optimization problem (MILP) has to be solved in association to the continuous operation of the energy system. The model includes but is not limited to several combined heat and power generators, heat accumulators, steam generators and auxiliary coolers. In this presentation we will give an outline about the wide range of given conditions that are successfully implemented for this application. Further we show our approach to generate realistic heat demand and power consumption forecasts which are both essential preconditions for obtaining reliable optimization results. In addition to the well established MILP model in this specific use case we will outline some further promising applications of mathematical optimization in the context of energy systems. This includes the more precise modelling of energy storages, the computation of the optimal design of energy systems and the consideration of different or multiple targets in optimization. Moreover, we outline the problem of uncertain boundary conditions due to the growing amount of temporally hard to predict energy production and demand. (C) 2018 The Authors. Published by Elsevier Ltd.

关键词： optimization of operation mixed-integer linear programming energy supply district heating demand forecast

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Battery Optimal Approach to Demand Charge Reduction in Behind-The-Meter Energy Management Systems

Battery Optimal Approach to Demand Charge Reduction in Behin...

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IEEE-Power-and-Energy-Society General Meeting (PESGM)

作者： Vatanparvar, Korosh Sharma, Ratnesh Univ Calif Irvine EECS Dept Irvine CA 92697 USA NEC Labs Amer Inc Energy Dept Irvine CA 92617 USA NEC Labs Amer Inc Energy Management Dept Cupertino CA 95014 USA

ISBN: (纸本)9781538677032

Large monthly demand charge of commercial and industrial entities is a major problem for their economical business. Utilizing a battery by behind-the-meter Energy Management Systems (EMS) has been seen as a solution to demand charge reduction. In state-of-the-art approaches, the EMS maintains sufficient energy for the unexpected large demands and uses the battery to meet them. However, large amount of energy stored in the battery may increase the average battery State of-Charge (SoC) and cause degradation in battery capacity. Therefore, the current approaches of demand charge reduction significantly-shortens the battery lifetime which is not economical. In this paper, we propose a novel battery optimal approach to reduce the monthly demand charges. In our approach, load profile of the previous month is used by daily optimizations to shave daily power demands while considering the battery lifetime model. Evaluated daily demand thresholds and load profile are statistically analyzed to cluster different types of day. Hence, it helps the EMS to find the typical daily load profile and appropriate monthly demand threshold for the entity. The performance of our approach has been analyzed and compared to the state-of-the-arts by experimenting on multiple real-life load profiles and battery configurations. The results show significant reduction of 16% in annual average battery SoC that increases the battery lifetime from 4.1 to 5.6 years while achieving up to 13.4% demand charge reduction.

关键词： Behind-The-Meter Energy Management Battery Demand Charge Optimization Machine Learning mixed-integer linear programming Battery Lifetime

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New Approach for Optimization of Construction and Demolition Waste Management: Application to the Lisbon Metropolitan Area 1

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18th Congress of the Portuguese-Association-of-Operational-Research (APDIO)

作者： de Andrade, Antonio Rebello Gomes, Marta Castilho Duque, Joaquim Univ Lisbon Inst Super Tecn Av Rovisco Pais 1 P-1049001 Lisbon Portugal Univ Lisbon CERIS CESUR Inst Super Tecn Av Rovisco Pais 1 P-1049001 Lisbon Portugal UAER Lab Nacl Energia & Geol Estr Paco do Lumiar 22 Lisbon Portugal

ISBN: (数字)9783319715834

ISBN: (纸本)9783319715834;9783319715827

The growing concern regarding global sustainability is increasingly evident in the construction sector due to the large amounts of waste produced. This work aims to develop a new approach in order to plan an efficient recycling network for Construction and Demolition Waste (CDW). The approach is based on the methodology of Process Systems Engineering (PSE), allowing an appropriate problem systematization and the definition of flows of materials between the network nodes. The developed mixed-integer linear programming (MILP) model is a tool to support CDW management in assessing the recycling network from a regulatory perspective (minimizing the total cost). Various scenarios can be defined and sensitivity analyses performed, making the aforementioned assessment clear regarding location, types and capacities of the new processes to be installed. The model was applied to the 211 parishes that comprise the Lisbon Metropolitan Area (LMA), in Portugal, but due to its generic formulation can be applied elsewhere at regional or national level. Results show a preference for direct deposition in landfills and the fact that high quality recycling processes are not, at present, economically viable for the LMA.

关键词： Construction and demolition waste mixed-integer linear programming Process systems engineering Lisbon metropolitan area

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Applications of train routing selection methods for real-time railway traffic management 21

Applications of train routing selection methods for real-tim...

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21st IEEE International Conference on Intelligent Transportation Systems (ITSC)

作者： Sama, Marcella D'Ariano, Andrea Pacciarelli, Dario Pellegrini, Paola Rodriguez, Joaquin Roma Tre Univ Dept Engn Rome Italy Univ Lille Nord France IFSTTAR COSYS LEOSTESTAS Villeneuve Dascq France

ISBN: (纸本)9781728103235

The real-time railway traffic management problem (rtRTMP) aims to solve time-overlapping conflicting track requests due to traffic disturbances. The size of the problem and the time required to solve it are affected by the number of routing alternatives available to each train. The real-time train routing selection problem (rtTRSP) chooses a feasible routing subset for each train to use as input for the rtRTMP. Recently, a computational analysis has been performed via Ant Colony Optimization and the RECIFE-MILP solver. This paper generalizes such analysis by considering a different rtRTMP model, objective function and solution approach. We adopt the AGLIBRARY solver, which is based an alternative graph model of the problem and minimizes the maximum consecutive delay. The aim is to develop real-time disturbance response strategies and to quantify the advantages of the selection of a subset of routings when using different solvers. We analyze how changes in the rtRTMP model are reflected in the rtTRSP and which modifications are required. The computational analysis is performed on two French infrastructures: the line around the city of Rouen and the Lille terminal station area. The analysis shows that solving the rtTRSP helps both solvers significantly, even if they are based on different models, objectives and algorithms.

关键词： Public Transport Train Rescheduling Ant Colony Optimization mixed-integer linear programming

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A MILP Approach for Filling Station Replenishment Problem with Time Windows in Initiative Distribution 7

A MILP Approach for Filling Station Replenishment Problem wi...

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7th International Conference on Industrial Technology and Management (ICITM)

作者： Zhang, Haoran Liao, Qi Yuan, Meng Wang, Bohong Shen, Yun Liang, Yongtu China Univ Petr Beijing Key Lab Urban Oil & Gas Distribut Technol Beijing Peoples R China

ISBN: (纸本)9781538613290

In this paper, we present a case study on vehicle routing and scheduling problem of filling stations replenishment with time windows in initiative distribution. A mixed-integer linear programming approach is proposed based on discrete-time presentation. By setting the minimal total cost in loading and unloading operations as well as all vehicles' transportation as objective function, and considering the practical issues such as fluctuation in filling station's sales and road congestion, the model is established under the constraints of loading, unloading, rest and standby, vehicle's state, time, filling station, depot and cost. Finally, the method is applied to a real case which has eight filling stations, one depot, one garage and eight vehicles and there are three types of products to be transported in the system. The final results proved better applicability and accuracy of this method.

关键词： vehicle routing and scheduling problem mixed-integer linear programming discrete-time presentation initiative distribution

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SDP Based Unit Commitment Via Moment Relaxation

SDP Based Unit Commitment Via Moment Relaxation

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North American Power Symposium (NAPS)

作者： Li, Yikui Wu, Lei Li, Jie Clarkson Univ Dept Elect & Comp Engn Potsdam NY 13699 USA

ISBN: (纸本)9781538671382

Unit commitment (UC) problems are the most fundamental problems that system operators solve every day in both day-ahead and real-time markets to guarantee secure and economic operation. UC problems are usually formulated as a mixed-integer linear programming (MILP) or a mixed-integer quadratic programming (MIQP) model with binary variables representing ON/OFF statuses of generators, and is solved via Branch and bound (B&B) type algorithms. With the prosperity of applying semidefinite programing (SDP) in the power system field, researchers attempt to solve UC under the SDP framework by relaxing integrality requirements, seeking an optimal solution or a better lower bound than the traditional linear programming (LP) relaxation. This paper uses 2-order moment relaxation technique to reformulate UC problems as an SDP model, which can be solved by an interior point method. Considering significant computational burden by 2-order moment relaxation, a variable reduction strategy and two refined moment relaxation based UC models are further applied. The relationship among the proposed models in terms of their tightness is studied. In addition, a sufficient condition under which a solution is exact is stated. Numerical studies illustrate effect of the proposed models and potential applicability of the proposed models is also discussed.

关键词： Unit commitment Semidefinite programming Moment relaxation mixed-integer linear programming

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