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North American Power Symposium (NAPS)

作者： Huang, Shengjun Dinavahi, Venkata Univ Alberta Dept Elect & Comp Engn Edmonton AB Canada Natl Univ Def Technol Coll Informat Syst & Management Changsha Hunan Peoples R China

ISBN: (纸本)9781538626993

Reliability management is of great importance for the secure and sufficient operation of power systems, thus the n-K-G-K-L contingency constrained unit commitment (CCUC) problem is determined for investigation in this paper. In order to reveal the capability of different methods on the solution of CCUC, both explicit and implicit decomposition frameworks have been investigated, as well as their inner feedback strategies, such as Benders decomposition and column-and-constraint generation (CCG) algorithm. In addition, sensitivity analysis, multi-cut strategy, and parallel implementation have also been analyzed and discussed. The comparison between nine explicit and implicit methods - all of them are deterministic with different configurations and the global optimal can be guaranteed in a finite number of iterations - is carried out on the IEEE 24-bus system, resulting in several interesting conclusions. Finally, the IEEE 118-bus test system is employed to explore the potential on the large-scale instance.

关键词： Benders decomposition contingency constrained unit commitment mixed-integer linear programming robust optimization

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Improving maritime inventory routing: application to a Brazilian petroleum case

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MARITIME POLICY & MANAGEMENT 2017年第1期44卷 42-61页

作者： dos Santos Diz, Gustavo Souto Oliveira, Fabricio Hamacher, Silvio Petrobras SA Logist Dept Rio De Janeiro Brazil Pontific Catholic Univ Dept Ind Engn BR-22451900 Rio De Janeiro Brazil

The crude oil offloading and supply problem (COSP) is a type of operation maritime inventory routing (MIR) problem encountered by petroleum companies. In COSP, the company not only is responsible for the ship scheduling to carry the crude oil from production sites to discharge ports but also must maintain inventory levels at both ports (production and consumption) between safety operational bounds to avoid disruptions in its crude oil production and/or refining processes. We show how to improve significantly the decision-making process in a Brazilian petroleum company using a mixed-integer linear programming (MILP) model to represent COSP. Comparison tests with a current ship-scheduling method adopted in the company indicated that the use of the MILP model increased the transportation efficiency and reduced costs by 20% on average. In addition to the quantitative gains, the use of a MILP model to solve COSP has succeeded when encountering real-life events, such as variation in production or consumption rates, berth unavailability, and changes in the storage capacities at ports.

关键词： Maritime inventory routing mixed-integer linear programming fixed charge network flow formulation ship scheduling

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Development of MILP Model for Integrated Aircraft Maintenance Scheduling and Multi-Period Parking Layout Planning Problems 4

Development of MILP Model for Integrated Aircraft Maintenanc...

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4th International Conference on Industrial Engineering and Applications (ICIEA)

作者： Qin, Yichen Chan, Felix T. S. Chung, S. H. Qu, T. Jinan Univ Sch Elect & Informat Engn Zhuhai Campus Zhuhai 519070 Peoples R China Hong Kong Polytech Univ Dept Ind & Syst Engn Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781509067756

In this paper, two closely related problems commonly observed in aircraft hangar maintenance companies are studied: the aircraft hangar maintenance scheduling problem and the parking stand planning problem. Recently, in order to reduce operating costs in airline companies, outsourcing aircraft heavy maintenance activities to a third-party maintenance company has been gaining greater traction. In a real operation environment, aircraft with different arrival times and specific maintenance requirements from airline companies are received by an aircraft maintenance company. Hence, a maintenance schedule and a series of aircraft parking plans have to be carefully arranged to minimize the total delay over a multi-period planning horizon. However, conventional manual planning usually causes maintenance delays due to inadequate parking planning that induces blockages between arriving, departing and parked aircraft in the process of aircraft roll in and roll out operations. To deal with the inefficiency of manual planning, a mixed-integer linear programming (MILP) model that integrates maintenance scheduling and parking layout planning is proposed. To our knowledge, this is the first work to deal with the aircraft maintenance scheduling problem incorporating non-overlapping constraints between aircraft in the hangar, and is the main contribution of this research.

关键词： aircraft maintenance scheduling parking layout planning mixed-integer linear programming non-overlapping constraints

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Strategic Optimization of Offshore Wind Farm Installation 1

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8th International Conference on Computational Logistics (ICCL)

作者： Backe, Stian Haugland, Dag Norwegian Univ Sci & Technol Dept Ind Econ & Technol Management Trondheim Norway Univ Bergen Dept Informat Bergen Norway

ISBN: (数字)9783319684963

ISBN: (纸本)9783319684963;9783319684956

This work describes logistical planning of offshore wind farm (OWF) installation through linear programming. A mixed-integer linear programming (MILP) model is developed to analyze cost-effective port and vessel strategies for offshore installation operations. The model seeks to minimize total costs through strategic decisions, that is decisions on port and vessel fleet and mix. Different vessels, ports and weather restrictions over a fixed time horizon are considered in the model. Several deterministic test cases with historic weather data are implemented in AMPL, and run with the CPLEX solver. The results provide valuable insight into economic impact of strategic decisions. Numerical experiments on instances indicate that decision aid could be more reliable if large OWFs are considered in fractionated parts, alternatively by developing heuristics.

关键词： offshore wind installation mixed-integer linear programming fleet optimization

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Capacity Firming of Intermittent Generation by Dispersed Energy Storage

Capacity Firming of Intermittent Generation by Dispersed Ene...

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Australasian Universities Power Engineering Conference (AUPEC)

作者： Pantos, Milos Riaz, Shariq Chapman, Archie C. Verbic, Gregor Univ Ljubljana Lab Power Syst Fac Elect Engn SI-1000 Ljubljana Slovenia Univ Sydney Sch Elect & Informat Engn Sydney NSW Australia

ISBN: (纸本)9781538626474

The paper addresses the question of capacity firming of renewable energy sources as an effective tool for mitigating the volatility of their generation. The existing approaches propose an integration of these sources with some flexible production as a back-up support, flexible demand or energy storage systems at point of common coupling in order to provide some degree of firmness to the production. However, this research makes step further towards the idea to provide an adequate support with dispersed energy storage capacities at the distribution level owned by numerous prosumers (not excluding consumers and virtual power plants), where the batteries are primarily deployed for the needs of the prosumers (maximization of self-consumption) and the remaining capacities are available to the intermittent generation for capacity firming. In the proposed bi-level optimization model, the lower-level problem is embedded into the upper-level problem applying the optimality Karush-Kuhn-Tucker conditions. The problem is solved by mixed-integer linear programming and the solution is tested and verified on a case study with one wind generator and up to 30,000 prosumers.

关键词： Capacity firming dispersed energy storage intermittent generation Karush-Kuhn-Tucker conditions mixed-integer linear programming prosumers

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Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming

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RENEWABLE ENERGY 2010年第1期35卷 151-156页

作者： Morais, Hugo Kadar, Peter Faria, Pedro Vale, Zita A. Khodr, H. M. Polytech Inst Porto ISEP GECAD Knowledge Engn & Decis Support Res Ctr Elect Engn P-4200072 Oporto Portugal Budapest Univ Technol & Econ H-1111 Budapest Hungary

In the energy management of the isolated operation of small power system, the economic scheduling of the generation units is a crucial problem. Applying right timing can maximize the performance of the supply. The optimal operation of a wind turbine, a solar unit, a fuel cell and a storage battery is searched by a mixed-integer linear programming implemented in General Algebraic Modeling Systems (GAMS). A Virtual Power Producer (VPP) can optimal operate the generation units, assured the good functioning of equipment, including the maintenance, operation cost and the generation measurement and control. A central control at system allows a VPP to manage the optimal generation and their load control. The application of methodology to a real case study in Budapest Tech, demonstrates the effectiveness of this method to solve the optimal isolated dispatch of the DC micro-grid renewable energy park. The problem has been converged in 0.09 s and 30 iterations. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： mixed-integer linear programming Renewable energy park Scheduling Virtual power producer

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Stochastic Optimization for the Daily Joint Operation of Wind/PV and Energy Storage 8th

Stochastic Optimization for the Daily Joint Operation of Win...

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8th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS)

作者： Gomes, Isaias L. R. Pousinho, Hugo M. I. Melicio, Rui Mendes, Vitor M. F. Univ Evora Escola Ciencias & Tecnol Dept Fis Evora Portugal Univ Lisbon IDMEC Inst Super Tecn Lisbon Portugal Inst Super Engn Lisboa Lisbon Portugal

ISBN: (纸本)9783319560779

This paper deals with the problem of optimal bidding in a day-ahead market of electricity for a power producer having joint operation of wind with photovoltaic power systems and storage of energy. Uncertainty, not only on electricity market prices, but also on wind and photovoltaic powers, has to be faced in order to achieve optimal bidding. The problem is viewed as a sort of a two-stage stochastic optimization problem formulated by mix-integer linear programming. A case study with data from the Iberian Peninsula is presented and a comparison between joint and disjoint operations is discussed, allowing concluding that the joint operation attenuates the economic impact of disjoint operation volatility.

关键词： Day-ahead electricity market Energy storage mixed-integer linear programming Stochastic optimization Wind with PV powers

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An Assignment-Based Continuous-Time MILP Model for the Resource-Constrained Project Scheduling Problem

An Assignment-Based Continuous-Time MILP Model for the Resou...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEE IEEM)

作者： Rihm, Tom Trautmann, Norbert Univ Bern Dept Business Adm Schuetzenmattstr 14 CH-3012 Bern Switzerland

ISBN: (纸本)9781538609484

The widely studied resource-constrained project scheduling problem consists of determining the start times for a set of precedence-related project activities requiring time and scarce resources during execution such that the total project duration is minimized. In the literature, in addition to a large variety of specific solution approaches, various mixed-integer linear programming (MILP) models have been proposed for this problem. We present a novel MILP model that is based on explicit assignment and sequencing variables;we enhance the performance of the model by eliminating some symmetric solutions from the search space and by modifying the sequencing constraints for pairs of activities that cannot be processed in parallel. Our computational results for four standard test sets from the literature indicate that this novel model outperforms two state-of-the-art models, particularly when resources are very scarce.

关键词： mixed-integer linear programming Operations Research Project Management Resource-Constrained Project Scheduling

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Maritime Inventory Routing: a practical assessment and robust optimization approach

Maritime Inventory Routing: a practical assessment and robus...

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作者： Gustavo Souto dos Santos Diz Pontificia Universidade Catolica do Rio de Janeiro

学位级别：博士

Maritime inventory routing (MIR) problem is an academic name for a practical logistic problem that represents the routing or scheduling of vessels to carry product(s) between ports. Meanwhile, the product(s) inventory levels in these ports must remain between operational bounds during the entire planning horizon. This thesis focus on how to support decision on a real-life MIR problem faced by a Brazilian petroleum company. To do so, we structure a set of tests to compare different formulation from literature and identify which is more adherent to real problem. Due to computational complexity of the problem, we present an heuristic approach that provides reasonably good solutions when compared to deterministic mixed integer linear programming (MILP) formulations and reduces considerably the computational time of solving real-life instances. However, uncertainty events have great impact in the ship scheduling planning. Therefore, we propose a robust optimization approach that considers uncertainty in the time spent at ports in each ship visit. Our approach is able to determine the probability of infeasibility and the impact in the objective function for each level of robustness, helping to measure the uncertain aversion of the decision maker. Our experiments identified that, for a certain instance, varying the level of robustness one may reduce the probability of infeasibility from 87% (of deterministic solution) to 2% and it represents an increase in the transportation costs of about 13%.

关键词： maritime inventory routing mixed-integer linear programming valid inequalities relax-and-fix fix-and-optimize robust optimization

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Strategic energy planning under uncertainty

Strategic energy planning under uncertainty

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作者： Stefano MORET ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE

学位级别：博士

Various countries and communities are defining or rethinking their energy strategy driven by con- cerns for climate change and security of energy supply. Energy models, often based on optimization, can support this decision-making process. In the current energy planning practice, most models are deterministic, i. e. they do not consider uncertainty and rely on long-term forecasts for important parameters. However, over the long time horizons of energy planning, forecasts often prove to be inaccurate, which can lead to overcapacity and underutilization of the installed technologies. Although this shows the need of considering uncertainty in energy planning, uncertainty is to date seldom integrated in energy models. The main barriers to a wider penetration of uncertainty are i) the complexity and computational expense of energy models; ii) the issue of quantifying input un- certainties and determining their nature; iii) the selection of appropriate methods for incorporating uncertainties in energy models. To overcome these limitations, this thesis answers the following research question How does uncertainty impact strategic energy planning and how can we facilitate the integration of uncertainty in the energy modeling practice? with four novel methodological contributions. First, a mixed-integer linear programming modeling framework for large-scale energy systems is presented. Given the energy demand, the efficiency and cost of energy conversion technologies, the availability and cost of resources, the model identifies the optimal investment and operation strategies to meet the demand and minimize the total annual cost or greenhouse gas emissions. The concise formulation and low computational time make it suitable for uncertainty applications. Second, a method is introduced to characterize input uncertainties in energy planning models. Third, the adoption of a two-stage global sensitivity analysis approach is proposed to deal with the large number of uncertain paramet

关键词： Strategic energy planning uncertainty national energy systems energy modeling mixed-integer linear programming uncertainty characterization global sensitivity analysis robust optimization Switzerland geothermal energy

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