Optimal reactive power dispatch using stochastic chance-constrained programming

Deterministic Optimal Reactive Power Dispatch problem has been extensively studied, such that the demand power and the availability of shunt reactive power compensators are known and fixed. Give this background, a two-stage stochastic optimization model is first formulated under the presumption that the load demand can be modeled as specified random parameters. A second stochastic chance-constrained model is presented considering uncertainty on the demand and the equivalent availability of shunt reactive power compensators. Simulations on six-bus and 30-bus test systems are used to illustrate the validity and essential features of the proposed models. This simulations shows that the proposed models can prevent to the power system operator about of the deficit of reactive power in the power system and suggest that shunt reactive sourses must be dispatched against the unavailability of any reactive source. © 2012 IEEE.

Optimal conductor size selection and reconductoring in radial distribution systems using a mixed-integer LP approach

This paper presents a mixed-integer linear programming model to solve the conductor size selection and reconductoring problem in radial distribution systems. In the proposed model, the steady-state operation of the radial distribution system is modeled through linear expressions. The use of a mixed-integer linear model guarantees convergence to optimality using existing optimization software. The proposed model and a heuristic are used to obtain the Pareto front of the conductor size selection and reconductoring problem considering two different objective functions. The results of one test system and two real distribution systems are presented in order to show the accuracy as well as the efficiency of the proposed solution technique. © 1969-2012 IEEE.

A mixed-integer LP model for the optimal allocation of voltage regulators and capacitors in radial distribution systems

This paper presents a mixed-integer linear programming model to solve the problem of allocating voltage regulators and fixed or switched capacitors (VRCs) in radial distribution systems. The use of a mixed-integer linear model guarantees convergence to optimality using existing optimization software. In the proposed model, the steady-state operation of the radial distribution system is modeled through linear expressions. The results of one test system and one real distribution system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique. An heuristic to obtain the Pareto front for the multiobjective VRCs allocation problem is also presented. © 2012 Elsevier Ltd. All rights reserved.

A mixed-integer linear programming approach for optimal type, size and allocation of distributed generation in radial distribution systems

This paper presents a mixed-integer linear programming approach to solving the problem of optimal type, size and allocation of distributed generators (DGs) in radial distribution systems. In the proposed formulation, (a) the steady-state operation of the radial distribution system, considering different load levels, is modeled through linear expressions; (b) different types of DGs are represented by their capability curves; (c) the short-circuit current capacity of the circuits is modeled through linear expressions; and (d) different topologies of the radial distribution system are considered. The objective function minimizes the annualized investment and operation costs. The use of a mixed-integer linear formulation guarantees convergence to optimality using existing optimization software. The results of one test system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique.© 2012 Elsevier B.V. All rights reserved.

Penalty-based nonlinear solver for optimal reactive power dispatch with discrete controls

The optimal reactive dispatch problem is a nonlinear programming problem containing continuous and discrete control variables. Owing to the difficulty caused by discrete variables, this problem is usually solved assuming all variables as continuous variables, therefore the original discrete variables are rounded off to the closest discrete value. This approach may provide solutions far from optimal or even unfeasible solutions. This paper presents an efficient handling of discrete variables by penalty function so that the problem becomes continuous and differentiable. Simulations with the IEEE test systems were performed showing the efficiency of the proposed approach. © 1969-2012 IEEE.

Optimal charging of electric vehicles considering constraints of the medium voltage distribution network

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Planejamento de reativos em sistemas de energia elétrica através de um algoritmo de Branch-and-Bound não linear

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Avaliação do nível de concordância do teste imunocromatográfico OptiMAL-IT® e a gota espessa no diagnóstico da malária, no município de Mazagão-AP, Brasil

O diagnóstico precoce e o tratamento adequado dos casos de malária é a principal estratégia para o controle da doença. Várias alternativas para o diagnóstico microscópico tradicional foram propostas nos últimos anos, os testes imunocromatográficos que capturam antígenos alvos dos parasitos da malária estão sendo propostos, como o teste OptiMAL-IT® que detecta a desidrogenase lática do Plasmodium sp.. O estudo teve como objetivo a avaliação do nível de concordância entre o teste imunocromatográfico (OptiMAL-IT®) e a gota espessa para o diagnóstico da malária no Município de Mazagão – Amapá. Foram analisados 413 indivíduos com sintomatologia de malária, que procuraram o serviço da Unidade Mista de Saúde de Mazagão, com idade entre 01-68 anos. Os resultados do teste OptiMAL-IT® foram comparados com os resultados obtidos (das amostras) através da gota espessa corada pelo Giemsa. Dos 413 pacientes suspeitos de apresentarem malária, 317(76.8%) eram positivos através da GE e 311 (75.3%) eram positivos pelo TDR. Das lâminas de GE positivas, foram encontrados 27.4% de P. falciparum e 72.6% de P. vivax. O teste OptiMAL-IT® detectou 27.7% de P. falciparum e 72.3% de P. vivax. A sensibilidade obtida com o TDR para o P. falciparum foi de 97.7% e para o P. vivax foi de 98.2%, a sensibilidade global do TDR foi de 98.1% e a especificidade global e para ambas as espécies foi de 100%. Foram encontrados valores preditivos positivos e negativos de 100% e 94.1%, respectivamente. O teste OptiMAL-IT®, teve uma alta concordância com a GE, foi específico e eficiente, podendo ser usado no diagnóstico de malária nas situações onde a microscopia não está disponível.

A test of the utility of DNA barcoding in the radiation of the freshwater stingray genus Potamotrygon (Potamotrygonidae, Myliobatiformes)

DNA barcoding is a recently proposed global standard in taxonomy based on DNA sequences. The two main goals of DNA barcoding methodology are assignment of specimens to a species and discovery of new species. There are two main underlying assumptions: i) reciprocal monophyly of species, and ii) intraspecific divergence is always less than interspecific divergence. Here we present a phylogenetic analysis of the family Potamotrygonidae based on mitochondrial cytochrome c oxidase I gene, sampling 10 out of the 18 to 20 valid species including two non-described species. Potamotrygonidae systematics is still not fully resolved with several still-to-be-described species while some other species are difficult to delimit due to overlap in morphological characters and because of sharing a complex color patterns. Our results suggest that the family passed through a process of rapid speciation and that the species Potamotrygon motoro, P. scobina, and P. orbignyi share haplotypes extensively. Our results suggest that systems of identification of specimens based on DNA sequences, together with morphological and/or ecological characters, can aid taxonomic studies, but delimitation of new species based on threshold values of genetic distances are overly simplistic and misleading.

Filippov's selection theorem and the existence of solutions for optimal control problems in time scales

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Effect of Resin Cement Type on the Microtensile Bond Strength to Lithium Disilicate Ceramic and Dentin Using Different Test Assemblies

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Disturbance detection for optimal database storage in electrical distribution systems using artificial immune systems with negative selection

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Optimal Reactive Power Planning Using Risk Analysis

In this paper, the optimal reactive power planning problem under risk is presented. The classical mixed-integer nonlinear model for reactive power planning is expanded into two stage stochastic model considering risk. This new model considers uncertainty on the demand load. The risk is quantified by a factor introduced into the objective function and is identified as the variance of the random variables. Finally numerical results illustrate the performance of the proposed model, that is applied to IEEE 30-bus test system to determine optimal amount and location for reactive power expansion.

An unequivocal normalization-based paradigm to solve dynamic economic and emission active-reactive OPF (optimal power flow)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

An Optimal Control Framework for Resources Management in Agriculture

An optimal control framework to support the management and control of resources in a wide range of problems arising in agriculture is discussed. Lessons extracted from past research on the weed control problem and a survey of a vast body of pertinent literature led to the specification of key requirements to be met by a suitable optimization framework. The proposed layered control structure—including planning, coordination, and execution layers—relies on a set of nested optimization processes of which an “infinite horizon” Model Predictive Control scheme plays a key role in planning and coordination. Some challenges and recent results on the Pontryagin Maximum Principle for infinite horizon optimal control are also discussed.