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

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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Optimal Methodology for the Grounding Systems Design in Transmission Line Using mixed-integer linear programming

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2010年第2期38卷 115-136页

作者： Khodr, H. M. Inst Elect Engn GECAD Knowledge Engn & Decis Support Res Ctr Grp Invest Engn Conhecimento & Apoio Decisao P-4200072 Oporto Portugal

A novel optimization methodology is proposed for the design of transmission line grounding systems, taking into account technical and economical considerations. The grounding systems design of transmission lines is stated as a mixed-integer linear programming problem, in terms of the construction characteristics, and the particular requirements of the tower grounding schemes at the supports of each different line sections in order to minimize the investment costs subject to the maximum allowed line outage rate due to the lightning activity, excavation volume limits for lowering environmental impact, allowed maximum step voltage, and the limitation of the ground potential rise value. The methodology is tested on a real case consisting of a 230-kV transmission line, 85.4-km long, with 180 towers. Results are presented and compared to the design obtained through conventional tower design approaches with important reductions in the investment costs, encouraging the use and further development of the methodology.

关键词： grounding systems lightning mixed-integer linear programming optimization transmission line

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BALANCING OPTIMIZATION OF ROBOTIC WELDING LINES: MODEL AND CASE STUDY

BALANCING OPTIMIZATION OF ROBOTIC WELDING LINES: MODEL AND C...

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作者： THIAGO CANTOS LOPES FEDERAL UNIVERSITY OF TECHNOLOGY - PARANA

学位级别：硕士

Robotic welding manufacturing lines are production lines common in automobile in- dustries. During a vehicle's production, the vehicle's metal structure must be welded in a single resistant body. This is made by hundreds of spot-welding points, each of which tie locally two or more metal sheets. Efficiently distributing these welding points amongst robots is particularly challenging, taking in account that: not all robots can perform all weld points, robots must move their welding tools between weld points, and robots might interfere with one another if they use the same geometrical space. There are multiple feasible manners to distribute the welding points. However, each of these forms generates different economical results: If a robot performs too many points, it will become a line bottleneck and reduce average throughput. To find the set of operational decisions that yields the best output is the goal of optimization techniques. There are a wide variety of such techniques described in operations research and computer sciences literature: math- ematical models, algorithms, heuristics, meta-heuristics, etc.. In the industrial context, these techniques were adapted to related line balancing problems. However, these adap- tations can only solve the specific variants they were designed to address. While parallels can be drawn between aspects of robotic welding lines and many of such variants, the full combined set of characteristics of the studied lines is not treatable by (or convertible to) any of them. This dissertation develops a framework to optimize such lines, based on mixed-integer linear programing model developed to describe the problem. It also presents a case study to discuss and illustrate possible difficulties and how to overcome them. The presented model was applied to data from the factory's robotic welding lines composed of forty-two robots (divided in thirteen stations), four vehicle models and over seven hundred welding points for each vehicle. The

关键词： mixed-integer linear programming Assembly Line Balancing Problem Robotic Welding Lines Spot Resistance Welding Cycle Time Minimization

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DESIGNING INDUSTRIAL PRODUCTION LAYOUTS: AN APPLICATION ON RDBOTIC WELDING ASSEMBLY LINES

DESIGNING INDUSTRIAL PRODUCTION LAYOUTS: AN APPLICATION ON R...

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作者： ADALBERTO SATO UICIIELS FEDERAL UNIVERSITY OF TECHNOLOGY - PARANA

学位级别：硕士

Spot welding assembly lines are widely present in the automotive manufacturing in- dustry. The procedure of building the vehicle's body employs several robots equipped with spot welding tools. These robots and tools are quite costly, arising the necessity of designing the line consciously, meeting the product demand and reducing expenses at the same time. In this master thesis, the Robotic Assembly Line Design (RALD) problem is proposed and studied based on practical characteristics from an automotive company located in Brazil. A l\/Iixed-lnteger Liner programming (l\/IILP) formulation is developed allowing: station paralleling, (ii) equipment selection, and (iii) multiples robots per workstation. The mathematical model aims at minimising the total cost at the desired production rate, which involves robots, tools and facilities. The proposed model considered dead time during a cycle, space constraints, task assignment restrictions, and parallelism possibilities. Dead time is an unproductive and ﬁxed work-piece handling time included in the capacitated transporter robots' movement time. Computational experiments were performed in order to evidence the parameters' inﬂuence over the optimal line design solu- tion. In addition, practical case studies were conducted with parameters collected from a real-world robotic welding assembly line located on the outskirts of Curitiba-PR. (Brazil), reaching optimality. Compared to strictly serial lines, the model led to great advantages by allowing parallel station in the production system, making it possible to evaluate an expected trade-off between production rate and total cost.

关键词： mixed-integer linear programming Assembly line design problem Robotic welding assembly line Parallel stations Equipment selection Dead time

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INTEGRATING ELECTRIC VEHICLES AS LOAD IN UNIT COMMITMENT

INTEGRATING ELECTRIC VEHICLES AS LOAD IN UNIT COMMITMENT

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作者： Panagiotis Adraktas UNIVERSITY OF PIRAEUS

学位级别：硕士

During the last few years' electric vehicles started to catch more attention. According to environmental policies of major states and unions of states, the number of electric vehicles will be increasing in the next years. In this thesis is studied the problem of unit commitment with high penetration of renewable sources, by presenting different methods for forecasting the renewable production. Furthermore, a model of a flexible load from electric vehicles is integrated into the unit commitment models. The aim of this research is to study the impact of the excessive load on the production side and compare different unit commitment models. It is demonstrated that optimized charging is cheaper than random charging for all the models and allows higher numbers of electric vehicles to be integrated into the electric system. Simulations showed that the cost of energy increased slightly by 1% for the optimized charging profile when using 100% electric vehicles penetration, whereas in the random charging profile the increase was around 15% for the same percentage of electric vehicles penetration.

关键词： unit commitment electric vehicles energy cost mixed-integer linear programming power systems

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PrePack Optimization Problem In Fashion Retail

PrePack Optimization Problem In Fashion Retail

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作者： Maarten Cornelis (Marco) Verheul Vrije University Amsterdam

学位级别：硕士

In this thesis a case in fashion retail is considered. In this case different sizes of clothing items are allocated to packaging that contains all sizes of an item. This type of packaging is known as a PrePack. The amount of PrePacks ordered and the amount of a particular size determine the inventory level in a store. Ordering too many leads to overstocking costs and ordering too little leads to understocking costs. The PrePack Optimization Problems (POP) tries to minimize these costs by determining the products in the PrePack and the orders of the stores. For this problem an integer linear programming heuristic is developed that reduces computing times of the POP compared to other heuristics. This heuristic determines the optimal PrePack per store first and allocates the PrePacks that lead to the lowest costs second. The heuristic was evaluated with product data of a Dutch retailer. The computing times of the instances are below 2 minutes for all instances with an overstock limit less than 4. The heuristic can calculate the problem for instances with a larger overstock limit and a larger set of stores than existing heuristics (Fischetti et al., 2016; Hoskins et al., 2014). Results of the outcomes are analysed with sensitivity analyses to show the managerial implications of changes to the parameters on costs.

关键词： mixed-integer linear programming Packing problems Prepack optimization Fashion retail optimization model

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