Otimização de sistemas de distribuição de energia elétrica radiais usando programação cônica de segunda ordem inteira mista

Pós-graduação em Engenharia Elétrica - FEIS

Transmission network expansion planning considering repowering and reconfiguration

Transmission expansion planning (TEP) is a classic problem in electric power systems. In current optimization models used to approach the TEP problem, new transmission lines and two-winding transformers are commonly used as the only candidate solutions. However, in practice, planners have resorted to non-conventional solutions such as network reconfiguration and/or repowering of existing network assets (lines or transformers). These types of non-conventional solutions are currently not included in the classic mathematical models of the TEP problem. This paper presents the modeling of necessary equations, using linear expressions, in order to include non-conventional candidate solutions in the disjunctive linear model of the TEP problem. The resulting model is a mixed integer linear programming problem, which guarantees convergence to the optimal solution by means of available classical optimization tools. The proposed model is implemented in the AMPL modeling language and is solved using CPLEX optimizer. The Garver test system, IEEE 24-busbar system, and a Colombian system are used to demonstrate that the utilization of non-conventional candidate solutions can reduce investment costs of the TEP problem. (C) 2015 Elsevier Ltd. All rights reserved.

Reconfiguração de sistemas de distribuição de energia elétrica utilizando uma metodologia multipartida

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Resolução do problema de fluxo de potência ótimo pela meta-heurística algoritmo dos fogos de artifício de busca dinâmica com mutação de covariância

Pós-graduação em Engenharia Elétrica - FEIS

Planejamento dinâmico a longo prazo de ativos de sistemas de distribuição de energia elétrica considerando a incorporação de diferentes tipos de elementos adicionais de expansão

Pós-graduação em Engenharia Elétrica - FEIS

Um Modelo de otimização inteira mista na programação de produção de mangueiras hidráulicas

This work deals with a problem of mixed integer optimization model applied to production planning of a real world factory that aims for hydraulic hose production. To optimize production planning, a mathematic model of MILP Mixed Integer Linear Programming, so that, along with the Analytic Hierarchy process method, would be possible to create a hierarchical structure of the most import criteria for production planning, thus finding through a solving software the optimum hose attribution to its respective machine. The hybrid modeling of Analytic Hierarchy Process along with Linear Programming is the focus of this work. The results show that using this method we could unite factory reality and quantitative analysis and had success on improving performance of production planning efficiency regarding product delivery and optimization of the production flow

Um Modelo de otimização inteira mista na programação de produção de mangueiras hidráulicas

This work deals with a problem of mixed integer optimization model applied to production planning of a real world factory that aims for hydraulic hose production. To optimize production planning, a mathematic model of MILP Mixed Integer Linear Programming, so that, along with the Analytic Hierarchy process method, would be possible to create a hierarchical structure of the most import criteria for production planning, thus finding through a solving software the optimum hose attribution to its respective machine. The hybrid modeling of Analytic Hierarchy Process along with Linear Programming is the focus of this work. The results show that using this method we could unite factory reality and quantitative analysis and had success on improving performance of production planning efficiency regarding product delivery and optimization of the production flow

MATHEMATICAL MODELS AND POLYHEDRAL STUDIES FOR INTEGRAL SHEET METAL DESIGN

We deal with the optimization of the production of branched sheet metal products. New forming techniques for sheet metal give rise to a wide variety of possible profiles and possible ways of production. In particular, we show how the problem of producing a given profile geometry can be modeled as a discrete optimization problem. We provide a theoretical analysis of the model in order to improve its solution time. In this context we give the complete convex hull description of some substructures of the underlying polyhedron. Moreover, we introduce a new class of facet-defining inequalities that represent connectivity constraints for the profile and show how these inequalities can be separated in polynomial time. Finally, we present numerical results for various test instances, both real-world and academic examples.

Automotive diesel engine transient operation: modeling, optimization and control

Traditionally, the study of internal combustion engines operation has focused on the steady-state performance. However, the daily driving schedule of automotive engines is inherently related to unsteady conditions. There are various operating conditions experienced by (diesel) engines that can be classified as transient. Besides the variation of the engine operating point, in terms of engine speed and torque, also the warm up phase can be considered as a transient condition. Chapter 2 has to do with this thermal transient condition; more precisely the main issue is the performance of a Selective Catalytic Reduction (SCR) system during cold start and warm up phases of the engine. The proposal of the underlying work is to investigate and identify optimal exhaust line heating strategies, to provide a fast activation of the catalytic reactions on SCR. Chapters 3 and 4 focus the attention on the dynamic behavior of the engine, when considering typical driving conditions. The common approach to dynamic optimization involves the solution of a single optimal-control problem. However, this approach requires the availability of models that are valid throughout the whole engine operating range and actuator ranges. In addition, the result of the optimization is meaningful only if the model is very accurate. Chapter 3 proposes a methodology to circumvent those demanding requirements: an iteration between transient measurements to refine a purpose-built model and a dynamic optimization which is constrained to the model validity region. Moreover all numerical methods required to implement this procedure are presented. Chapter 4 proposes an approach to derive a transient feedforward control system in an automated way. It relies on optimal control theory to solve a dynamic optimization problem for fast transients. From the optimal solutions, the relevant information is extracted and stored in maps spanned by the engine speed and the torque gradient.

Networks, Uncertainty, Applications and a Crusade for Optimality

In this thesis we address a collection of Network Design problems which are strongly motivated by applications from Telecommunications, Logistics and Bioinformatics. In most cases we justify the need of taking into account uncertainty in some of the problem parameters, and different Robust optimization models are used to hedge against it. Mixed integer linear programming formulations along with sophisticated algorithmic frameworks are designed, implemented and rigorously assessed for the majority of the studied problems. The obtained results yield the following observations: (i) relevant real problems can be effectively represented as (discrete) optimization problems within the framework of network design; (ii) uncertainty can be appropriately incorporated into the decision process if a suitable robust optimization model is considered; (iii) optimal, or nearly optimal, solutions can be obtained for large instances if a tailored algorithm, that exploits the structure of the problem, is designed; (iv) a systematic and rigorous experimental analysis allows to understand both, the characteristics of the obtained (robust) solutions and the behavior of the proposed algorithm.

Entwicklung eines Dispositionsleitstandes zur Bestimmung optimaler Torbelegungen in Stückgutspeditionsanlagen

Im operativen Betrieb einer Stückgutspeditionsanlage entscheidet der Betriebslenker bzw. der Disponent in einem ersten Schritt darüber, an welche Tore die Fahrzeuge zur Be- und Entladung andocken sollen. Darüber hinaus muss er für jede Tour ein Zeitfenster ausweisen innerhalb dessen sie das jeweilige Tor belegt. Durch die örtliche und zeitliche Fahrzeug-Tor-Zuordnung wird der für den innerbetrieblichen Umschlagprozess erforderliche Ressourcenaufwand in Form von zu fahrenden Wegstrecken oder aber Gabelstaplerstunden bestimmt. Ein Ziel der Planungsaufgabe ist somit, die Zuordnung der Fahrzeuge an die Tore so vorzunehmen, dass dabei minimale innerbetriebliche Wegstrecken entstehen. Dies führt zu einer minimalen Anzahl an benötigten Umschlagmittelressourcen. Darüber hinaus kann es aber auch zweckmäßig sein, die Fahrzeuge möglichst früh an die Tore anzudocken. Jede Tour verfügt über einen individuellen Fahrplan, der Auskunft über den Ankunftszeitpunkt sowie den Abfahrtszeitpunkt der jeweiligen Tour von der Anlage gibt. Nur innerhalb dieses Zeitfensters darf der Disponent die Tour einem der Tore zuweisen. Geschieht die Zuweisung nicht sofort nach Ankunft in der Anlage, so muss das Fahrzeug auf einer Parkfläche warten. Eine Minimierung der Wartezeiten ist wünschenswert, damit das Gelände der Anlage möglichst nicht durch zuviele Fahrzeuge gleichzeitig belastet wird. Es kann vor allem aber auch im Hinblick auf das Reservieren der Tore für zeitkritische Touren sinnvoll sein, Fahrzeuge möglichst früh abzufertigen. Am Lehrstuhl Verkehrssysteme und -logistik (VSL) der Universität Dortmund wurde die Entscheidungssituation im Rahmen eines Forschungsprojekts bei der Stiftung Industrieforschung in Anlehnung an ein zeitdiskretes Mehrgüterflussproblem mit unsplittable flow Bedingungen modelliert. Die beiden Zielsetzungen wurden dabei in einer eindimensionalen Zielfunktion integriert. Das resultierende Mixed Integer Linear Programm (MILP) wurde programmiert und für mittlere Szenarien durch Eingabe in den Optimization Solver CPlex mit dem dort implementierten exakten Branch-and-Cut Verfahren gelöst. Parallel wurde im Rahmen einer Kooperation zwischen dem Lehrstuhl VSL und dem Unternehmen hafa Docking Systems, einem der weltweit führenden Tor und Rampenhersteller, für die gleiche Planungsaufgabe ein heuristisches Scheduling Verfahren sowie ein Dispositionsleitstand namens LoadDock Navigation entwickelt. Der Dispositionsleitstand dient der optimalen Steuerung der Torbelegungen in logistischen Anlagen. In dem Leitstand wird planerische Intelligenz in Form des heuristischen Schedulingverfahrens, technische Neuerungen in der Rampentechnik in Form von Sensoren und das Expertenwissen des Disponenten in einem Tool verbunden. Das mathematische Modell sowie der Prototyp mit der integrierten Heuristik werden im Rahmen dieses Artikels vorgestellt.

A continuous-time MILP model for short-term scheduling of make-and-pack production processes

In process industries, make-and-pack production is used to produce food and beverages, chemicals, and metal products, among others. This type of production process allows the fabrication of a wide range of products in relatively small amounts using the same equipment. In this article, we consider a real-world production process (cf. Honkomp et al. 2000. The curse of reality – why process scheduling optimization problems are diffcult in practice. Computers & Chemical Engineering, 24, 323–328.) comprising sequence-dependent changeover times, multipurpose storage units with limited capacities, quarantine times, batch splitting, partial equipment connectivity, and transfer times. The planning problem consists of computing a production schedule such that a given demand of packed products is fulfilled, all technological constraints are satisfied, and the production makespan is minimised. None of the models in the literature covers all of the technological constraints that occur in such make-and-pack production processes. To close this gap, we develop an efficient mixed-integer linear programming model that is based on a continuous time domain and general-precedence variables. We propose novel types of symmetry-breaking constraints and a preprocessing procedure to improve the model performance. In an experimental analysis, we show that small- and moderate-sized instances can be solved to optimality within short CPU times.

The Effects of Credit Risk on Dynamic Portfolio Management: A New Computational Approach

The study investigates the role of credit risk in a continuous time stochastic asset allocation model, since the traditional dynamic framework does not provide credit risk flexibility. The general model of the study extends the traditional dynamic efficiency framework by explicitly deriving the optimal value function for the infinite horizon stochastic control problem via a weighted volatility measure of market and credit risk. The model's optimal strategy was then compared to that obtained from a benchmark Markowitz-type dynamic optimization framework to determine which specification adequately reflects the optimal terminal investment returns and strategy under credit and market risks. The paper shows that an investor's optimal terminal return is lower than typically indicated under the traditional mean-variance framework during periods of elevated credit risk. Hence I conclude that, while the traditional dynamic mean-variance approach may indicate the ideal, in the presence of credit-risk it does not accurately reflect the observed optimal returns, terminal wealth and portfolio selection strategies.

Contribution of re-regulation reservoirs considering pumping capability to environmentally friendly hydropower operation

Environmental constraints imposed on hydropoweroperation are usually given in the form of minimum environmental flows and maximum and minimum rates of change of flows, or ramp rates. One solution proposed to mitigate the environmental impact caused by the flows discharged by a hydropower plant while reducing the economic impact of the above-mentioned constraints consists in building a re-regulationreservoir, or afterbay, downstream of the power plant. Adding pumpingcapability between the re-regulationreservoir and the main one could contribute both to reducing the size of the re-regulationreservoir, with the consequent environmental improvement, and to improving the economic feasibility of the project, always fulfilling the environmental constraints imposed to hydropoweroperation. The objective of this paper is studying the contribution of a re-regulationreservoir to fulfilling the environmental constraints while reducing the economic impact of said constraints. For that purpose, a revenue-driven optimization model based on mixed integer linear programming is used. Additionally, the advantages of adding pumpingcapability are analysed. In order to illustrate the applicability of the methodology, a case study based on a real hydropower plant is presented

Red Eléctrica de España uses integer programming for annual salary revisions

In this paper, we present a mixed-integer linear programming model for determining salary-revision matrices for an organization based on that organization?s general strategies. The solution obtained from this model consists of salary increases for each employee; these increases consider the employee?s professional performance, salary level relative to peers within the organization, and professional group. In addition to budget constraints, we modeled other elements typical of compensation systems, such as equity and justice. Red Eléctrica de España (REE), the transmission agent and operator of the Spanish electricity system, used the model to revise its 2010 and 2011 salary policies, and achieved results that were aligned with the company strategy. REE incorporated the model into the salary management module within its information system, and plans to continue to use the model in revisions of the module.