924 resultados para Operation and expansion planning
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In this paper, a hybrid heuristic methodology that employs fuzzy logic for solving the AC transmission network expansion planning (AC-TEP) problem is presented. An enhanced constructive heuristic algorithm aimed at obtaining a significant quality solution for such complicated problems considering contingency is proposed. In order to indicate the severity of the contingency, 2 performance indices, namely the line flow performance index and voltage performance index, are calculated. An interior point method is applied as a nonlinear programming solver to handle such nonconvex optimization problems, while the objective function includes the costs of the new transmission lines as well as the real power losses. The performance of the proposed method is examined by applying it to the well-known Garver system for different cases. The simulation studies and result analysis demonstrate that the proposed method provides a promising way to find an optimal plan. Obtaining the best quality solution shows the capability and the viability of the proposed algorithm in AC-TEP. © Tübi̇tak..
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This study presents a new methodology based on risk/investment to solve transmission network expansion planning (TNEP) problem with multiple future scenarios. Three mathematical models related to TNEP problems considering multiple future generation and load scenarios are also presented. These models will provide planners with a meaningful risk assessment that enable them to determine the necessary funding for transmission lines at a permissible risk level. The results using test and real systems show that the proposed method presents better solutions compared with scenario analysis method. ©The Institution of Engineering and Technology 2013.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The hydroelectric power plant Hidroltuango represents a major expansion for the Colombian electrical system (with a total capacity of 2400 MW). This paper analyzes the possible interconnections and investments involved in connecting Hidroltuango, in order to strengthen the Colombian national transmission system. A Mixed Binary Linear Programming (MBLP) model was used to solve the Multistage Transmission Network Expansion Planning (MTEP) problem of the Colombian electrical system, taking the N-1 safety criterion into account. The N-1 safety criterion indicates that the transmission system must be expanded so that the system will continue to operate properly if an outage in a system element (within a pre-defined set of contingencies) occurs. The use of a MBLP model guaranteed the convergence with existing classical optimization methods and the optimal solution for the MTEP using commercial solvers. Multiple scenarios for generation and demand were used to consider uncertainties within these parameters. The model was implemented using the algebraic modeling language AMPL and solved using the commercial solver CPLEX. The proposed model was then applied to the Colombian electrical system using the planning horizon of 2018-2025. (C) 2014 Elsevier B.V. All rights reserved.
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The transmission expansion planning problem in modern power systems is a large-scale, mixed-integer, nonlinear and non-convex problem. this paper presents a new mathematical model and a constructive heuristic algorithm (CHA) for solving transmission expansion planning problem under new environment of electricity restructuring. CHA finds an acceptable solution in an iterative process, where in each step a circuit is chosen using a sensitivity index and added to the system. The proposed model consider multiple generation scenarios therefore the methodology finds high quality solution in which it allows the power system operate adequacy in an environment with multiple generators scenarios. Case studies and simulation results using test systems show possibility of using Constructive heuristic algorithm in an open access system.
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This paper presents a mixed-integer convex-optimization-based approach for optimum investment reactive power sources in transmission systems. Unlike some convex-optimization techniques for the reactive power planning solution, in the proposed approach the taps settings of under-load tap-changing of transformers are modeled as a mixed-integer linear set equations. Are also considered the continuous and discrete variables for the existing and new capacitive and reactive power sources. The problem is solved for three significant demand scenarios (low demand, average demand and peak demand). Numerical results are presented for the CIGRE-32 electric power system.
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BACKGROUND: Newborns with hypoplastic left heart syndrome (HLHS) or right heart syndrome or other malformations with a single ventricle physiology and associated hypoplasia of the great arteries continue to be a challenge in terms of survival. The vast majority of these forms of congenital heart defects relate to abnormal morphogenesis during early intrauterine development and can be diagnosed accurately by fetal echocardiography. Early knowledge of these conditions not only permits a better understanding of the progression of these malformations but encourages some researchers to explore new minimally invasive therapeutic options with a view to early pre- and postnatal cardiac palliation. DATA SOURCES: PubMed database was searched with terms of "congenital heart defects", "fetal echocardiography" and "neonatal cardiac surgery". RESULTS: At present, early prenatal detection has been applied for monitoring pregnancy to avoid intrauterine cardiac decompensation. In principle, the majority of congenital heart defects can be diagnosed by prenatal echocardiography and the detection rate is 85%-95% at tertiary perinatal centers. The majority, particularly of complex congenital lesions, show a steadily progressive course including subsequent secondary phenomena such as arrhythmias or myocardial insufficiency. So prenatal treatment of an abnormal fetus is an area of perinatal medicine that is undergoing a very dynamic development. Early postnatal treatment is established for some time, and prenatal intervention or palliation is at its best experimental stage in individual cases. CONCLUSION: The upcoming expansion of fetal cardiac intervention to ameliorate critically progressive fetal lesions intensifies the need to address issues about the adequacy of technological assessment and patient selection as well as the morbidity of those who undergo these procedures.
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The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. ^ For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver.^ The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. ^ The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.^
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The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver. The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.
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PURPOSE: To report an uncommon case of osteochondroma affecting the mandibular condyle of a young patient and to illustrate the important contributions of different imaging resources to the diagnosis and treatment planning of this lesion. CASE DESCRIPTION: A 24-year-old female patient with the chief complaint of an increasing facial asymmetry and pain in the left pre-auricular region, revealing a reduced mouth opening, mandibular deviation and posterior cross-bite over a period of 18 months. Panoramic radiography revealed an enlargement of the left condyle, whereas computed tomography (CT) sections and three-dimensional CT showed a well-defined bone growth arising from condylar neck. The scintigraphy exam showed an abnormal osteogenic activity in the left temporomandibular joint. The condyle was surgically removed and after 18 months follow-up the panoramic radiography and CT scans showed no signs of recurrence. CONCLUSION: Although osteochondroma is a benign bone tumor that rarely arises in cranial and maxillofacial region, it should be considered in the differential diagnosis of slow-growing masses of the temporomandibular area and the use of different imaging exams significantly contribute to the correct diagnosis and treatment planning of this pathological condition.
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A heuristic algorithm that employs fuzzy logic is proposed to the power system transmission expansion planning problem. The algorithm is based on the divide to conquer strategy, which is controlled by the fuzzy system. The algorithm provides high quality solutions with the use of fuzzy decision making, which is based on nondeterministic criteria to guide the search. The fuzzy system provides a self-adjusting mechanism that eliminates the manual adjustment of parameters to each system being solved. (C) 2010 Elsevier B.V. All rights reserved.
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Osny Ferreira-Junior, Luciana Dorigatti de Avila, Marcelo Bonifacio da Silva Sampieri, Eduardo Dias-Ribeiro, Weiliang Chen, Song Fan. Impacted Lower Third Molar Fused with a Supernumerary Tooth-Diagnosis and Treatment Planning Using Cone-Beam Computed Tomography. International Journal of Oral Science, 1(4): 224-228, 2009 This paper reported a case of fusion between an impacted third molar and a supernumerary tooth, in which a surgical intervention was carried out, with the objective of removing the dental elements. The panoramic radiography was complemented by the Donovan`s radiographic technique; but because of the proximity of the dental element to the mandibular ramus, it was not possible to have a final fusion diagnosis. Hence, the Cone-Beam Computed Tomography-which provides precise three-dimensional information-was used to determinate the fusion diagnosis and also to help in the surgical planning. In this case report we observed that the periapical, occlusal and panoramic were not able to show details which could only be examined through the cone-beam computed tomography.