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Forecasting flexibility in electricity demand with price/consumption volume signals

ELECTRIC POWER SYSTEMS RESEARCH 2013年 95卷 200-205页

作者： Gorria, C. Jimeno, J. Laresgoiti, I. Lezaun, M. Ruiz, N. Univ Pais Vasco UPV EHU Dept Appl Math Stat & Operat Res Leioa 48940 Spain Tecnalia Energy Unit Derio 48160 Spain

The introduction of renewable energy sources, particularly wind power, is limited by their dependence on weather conditions and by the difficulty of storing surplus energy for use at times when production is low. One effective way of tackling the energy storage problem is to minimise the need for storage, i.e. to switch from a system based on producing electricity in response to the unpredictable whims of demand to one in which consumption adapts to supply. Demand can be managed indirectly via the sending of price/consumption volume signals. This paper presents a mathematical model for forecasting the aggregated electricity demand of a group of domestic consumers signed up to an incentive-based demand management programme. Under this programme consumers receive signals that offer financial incentives for limiting their volume of consumption at time intervals when system peak demand is forecast. The resulting optimisation model is a mixed-integer linear programming problem implemented in JAVA and solved using free software. This model is applied to a case study in which the objective is to limit consumption by a population of 15932 consumers from 15:00 to 17:45 on a specific summer day. The responses to two different incentive amounts are shown. (c) 2012 Elsevier B.V. All rights reserved.

关键词： Electricity demand Demand management Optimisation mixed-integer linear programming

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A mixed-integer LP model for the reconfiguration of radial electric distribution systems considering distributed generation

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ELECTRIC POWER SYSTEMS RESEARCH 2013年 97卷 51-60页

作者： Franco, John F. Rider, Marcos J. Lavorato, Marina Romero, Ruben Univ Estadual Paulista UNESP FEIS DEE Sao Paulo Brazil

The problem of reconfiguration of distribution systems considering the presence of distributed generation is modeled as a mixed-integer linear programming (MILP) problem in this paper. The demands of the electric distribution system are modeled through linear approximations in terms of real and imaginary parts of the voltage, taking into account typical operating conditions of the electric distribution system. The use of an MILP formulation has the following benefits: (a) a robust mathematical model that is equivalent to the mixed-integer non-linear programming model;(b) an efficient computational behavior with exiting MILP solvers;and (c) guarantees convergence to optimality using classical optimization techniques. Results from one test system and two real systems show the excellent performance of the proposed methodology compared with conventional methods. Crown Copyright (C) 2012 Published by Elsevier B.V. All rights reserved.

关键词： Reconfiguration of electric distribution systems Active power losses reduction Distributed generation mixed-integer linear programming

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A Stochastic Optimization Formulation of Unit Commitment With Reliability Constraints

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IEEE TRANSACTIONS ON SMART GRID 2013年第4期4卷 2200-2208页

作者： Xiong, Peng Jirutitijaroen, Panida Natl Univ Singapore Dept Elect & Comp Engn Singapore 119077 Singapore

This paper proposes a new formulation for a stochastic unit commitment (UC) problem that incorporates two major and common sources of uncertainty in short-term generation scheduling, namely, unavailability of generators and load uncertainty. The objective is to minimize operating cost and expected loss of load cost subject to reliability constraints in terms of loss of load probability. The problem is first formulated as a two-stage recourse model in stochastic programming framework where generator unavailability is expressed by a discrete set of outage scenarios and system demand is set to be a nominal value in power balance equations. Then, load uncertainty is represented as a continuous random variable in loss of load probability constraint, which is approximated by a mixed-integer piecewise linear function and integrated to the second stage problem. As a result, the UC problem has a much smaller dimension as compared to the original two-stage recourse model. The proposed formulation can be solved in a timely manner even though the formulation requires some extra binary decision variables. Although loss of load probability constraint is approximated in the optimization problem, simulation results show that the optimal solutions yield desired reliability performance. Several case studies are conducted to examine the impact of reliability requirements and system uncertainties on UC decisions.

关键词： mixed-integer linear programming reliability stochastic programming uncertainty unit commitment

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Achieving energy self-sufficiency by integrating renewables into companies' supply networks

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ENERGY 2013年 55卷 46-57页

作者： Kiraly, Annamaria Pahor, Bojan Kravanja, Zdravko Perutnina Ptuj Dd SI-2250 Ptuj Slovenia Univ Maribor Fac Chem & Chem Engn SI-2000 Maribor Slovenia

The aim of this contribution was to present the integration of renewables into companies' supply-networks at regional level in order to maximise the self-sufficiencies of their energy supplies. This concerns companies' activities from the use of natural resources to supplying their final products to the customers being interlinked with their regional networks. A MILP model (mixed-integer linear programming) has been developed for the synthesis of companies' supply-networks utilising different types of renewables as sources for the companies' energy supplies, and embedded into the MILP model, previously developed by authors, for the synthesis of regional biomass production and supply networks. The integrated synthesis model was applied to an existing large-scale meat company. The potential renewable energy sources, which are located within companies surrounding region are solar, biomass, organic and animal wastes. The result indicates that by sufficient integration of renewables into companies' supply networks, profitable and yet energy self-sufficient solutions can be obtained. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Companies supply-chain Regional supply-network optimisation Renewables Energy self-sufficiency mixed-integer linear programming

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Network interdiction via a Critical Disruption Path: Branch-and-Price algorithms

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COMPUTERS & OPERATIONS RESEARCH 2013年第11期40卷 2689-2702页

作者： Granata, Donatella Steeger, Gregory Rebennack, Steffen CNR Inst Applicat Calculus Mauro Picone Naples Italy Colorado Sch Mines Div Econ & Business Golden CO 80401 USA

This paper presents an innovative approach to maximally disconnect a given network. More specifically, this work introduces the concept of a Critical Disruption Path, a path between a source and a destination vertex whose deletion minimizes the cardinality of the largest remaining connected component. Network interdiction models seek to optimally disrupt network operations. Existing interdiction models disrupt network operations by removing vertices or edges. We introduce the first problem and formulation that optimally fragments a network via interdicting a path. Areas of study in which this work can be applied include transportation and evacuation networks, surveillance and reconnaissance operations, anti-terrorism activities, drug interdiction, and counter human-trafficking operations. In this paper, we first address the complexity associated with the Critical Disruption Path problem, and then provide a mixed-integer linear programming formulation for finding its optimal solution. Further, we develop a tailored Branch-and-Price algorithm that efficiently solves the Critical Disruption Path problem. We demonstrate the superiority of the developed Branch-and-Price algorithm by comparing the results found via our algorithm with the results found via the monolith formulation. In more than half of the test instances that can be solved by both the monolith and our Branch-and-Price algorithm, we outperform the monolith by two orders of magnitude. (c) 2013 Elsevier Ltd. All rights reserved.

关键词： Network interdiction mixed-integer linear programming NP-completeness Branch-and-Price Cuts

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Hourly Demand Response in Day-Ahead Scheduling Considering Generating Unit Ramping Cost

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IEEE TRANSACTIONS ON POWER SYSTEMS 2013年第3期28卷 2446-2454页

作者： Wu, Hongyu Shahidehpour, Mohammad Khodayar, Mohammad E. IIT Dept Elect & Comp Engn Chicago IL 60616 USA

This paper proposes a day-ahead scheduling model in which the hourly demand response (DR) is considered to reduce the system operation cost and incremental changes in generation dispatch when the ramping cost of thermal generating units is considered as penalty in day-ahead scheduling problem. The power output trajectory of a thermal generating unit is modeled as a piecewise linear function. The day-ahead scheduling is formulated as a mixed-integer quadratically constrained programming (MIQCP) problem with quadratic energy balance constraint, ramping cost, and DR constraints. A Lagrangian relaxation (LR) based method is applied to solve this problem. Numerical tests are conducted on a 6-bus system and the modified IEEE 118-bus system. The results demonstrate the merits of the proposed scheduling model as well as the impact of introducing ramping costs as penalty and DR as incentives in the day-ahead scheduling of power systems.

关键词： Demand response generating unit ramping cost Lagrangian relaxation mixed-integer linear programming security constrained unit commitment

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An Efficient Reformulation of the Multiechelon Stochastic Inventory System with Uncertain Demands

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AICHE JOURNAL 2013年第1期59卷 23-28页

作者： Nyberg, Axel Grossmann, Ignacio E. Westerlund, Tapio Abo Akad Univ Dept Chem Engn Proc Design & Syst Engn Lab Turku Finland Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA Abo Akad Univ Proc Design & Syst Engn Lab Turku Finland

It is shown that by reformulating the three-stage multiechelon inventory system with specific exact linearizations, larger problems can be solved directly with mixed-integer linear programming (MILP) without decomposition. The new formulation is significantly smaller in the number of continuous variables and constraints. An MILP underestimation of the problem can be solved as part of a sequential piecewise approximation scheme to solve the problem within a desired optimality gap.

关键词： optimization mixed-integer linear programming exact linearization supply-chains

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The importance of economies of scale, transport costs and demand patterns in optimising hydrogen fuelling infrastructure: An exploration with SHIPMod (Spatial hydrogen infrastructure planning model)

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2013年第26期38卷 11189-11201页

作者： Agnolucci, Paolo Akgul, Ozlem McDowall, William Papageorgiou, Lazaros G. UCL UCL Inst Sustainable Resources London WC1H 0NN England UCL Ctr Proc Syst Engn London WC1E 7JE England

Hydrogen is widely recognised as an important option for future road transportation, but a widespread infrastructure must be developed if the potential for hydrogen is to be achieved. This paper and related appendices which can be downloaded as Supplementary material present a mixed-integer linear programming model (called SHIPMod) that optimises a hydrogen supply chains for scenarios of hydrogen fuel demand in the UK, including the spatial arrangement of carbon capture and storage infrastructure. In addition to presenting a number of improvements on past practice in the literature, the paper focuses attention on the importance of assumptions regarding hydrogen demand. The paper draws on socio-economic data to develop a spatially detailed scenario of possible hydrogen demand. The paper then shows that assumptions about the level and spatial dispersion of hydrogen demand have a significant impact on costs and on the choice of hydrogen production technologies and distribution mechanisms. Copyright (C) 2013, The Authors. Published by Elsevier Ltd. All rights reserved.

关键词： Hydrogen supply chains mixed-integer linear programming Infrastructure optimisation modelling

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Integrated scheduling and inventory management of an oil products distribution system

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2013年第6期41卷 955-968页

作者： Relvas, Susana Magatao, Suelen N. Boschetto Barbosa-Povoa, Ana Paula F. D. Neves, Flavio, Jr. Univ Tecn Lisboa CEG IST P-1049001 Lisbon Portugal CPGEI Fed Univ Technol Parana BR-80230901 Curitiba Parana Brazil

The oil supply chain is facing new challenges due to emerging issues such as new alternative energy sources, oil sources scarcity, and price variability with high impact on demand and production and profit margins reduction. Additionally, the existence of large, complex and world wide spread businesses implies a complex system to be managed where distribution can be seen as one of the key areas that needs to be efficiently and effectively managed. Different types of distribution modes characterize the oil supply chain where the pipeline mode is one of the most complex to operate when having multiproduct characteristics. This paper addresses the planning of a generic oil derivatives transportation system characterized by a multiproduct pipeline that connects a single refinery to a storage tank farm. Two alternative mixed integer linear programming models (MILP) that aim to attain a set of planning objectives such as fulfilling costumers' demands (which is mandatory) while minimizing the medium flow rate are developed. Additionally, final inventory levels are avoided to be excessively low. A real world scenario of a Portuguese company is used to validate and compare the two alternative MILP models developed in this paper. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Supply chain management Pipeline scheduling mixed-integer linear programming

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A mathematical model and a heuristic approach for periodic material delivery in lean production environment

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2013年第5-8期69卷 977-992页

作者： Kilic, Huseyin Selcuk Durmusoglu, Mehmet Bulent Marmara Univ Dept Ind Engn TR-34722 Istanbul Turkey Istanbul Tech Univ Dept Ind Engn TR-34367 Istanbul Turkey

One of the important design elements for a good production system is material handling. In cases where it is not well-designed, it can be the bottleneck in the system. Moreover, it can cause a lot of wastes such as waiting time, idle time, and excessive transportation and cost. In this study, material handling in lean-based production environments is taken into account. Depending on the lean structure of the production systems such as being pull-based, smooth, and repetitive, delivering the materials to the stations periodically becomes important. At this point, milk-run trains are highly used in real applications since they enable the handling of required amount of materials on a planned basis. With this study, it is aimed to develop a specific model for milk-run trains which travel periodically in the production environment on a predefined route in equal cycle times with the aim of minimizing work-in-process and transportation costs. Since the milk-run trains having equal cycle times start their tours at the same time intervals, it becomes simple to manage them. For this reason, they are used in lean production systems where level scheduling is performed. The developed model is based on mixed-integer linear programming, and since it is difficult to find the optimum solution due to the combinatorial structure of the problem, a novel heuristic approach is developed. A numerical example is provided so as to show the applicability of the mathematical model and the heuristic approach.

关键词： In-plant logistics Milk-run distribution Lean production mixed-integer linear programming Heuristic approach

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