Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems

This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.

Logic programming and fuzzy Monte Carlo for distribution network reconfiguration

This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.

Derivative-free optimization and filter methods to solve nonlinear constrained problems

In real optimization problems, usually the analytical expression of the objective function is not known, nor its derivatives, or they are complex. In these cases it becomes essential to use optimization methods where the calculation of the derivatives, or the verification of their existence, is not necessary: the Direct Search Methods or Derivative-free Methods are one solution. When the problem has constraints, penalty functions are often used. Unfortunately the choice of the penalty parameters is, frequently, very difficult, because most strategies for choosing it are heuristics strategies. As an alternative to penalty function appeared the filter methods. A filter algorithm introduces a function that aggregates the constrained violations and constructs a biobjective problem. In this problem the step is accepted if it either reduces the objective function or the constrained violation. This implies that the filter methods are less parameter dependent than a penalty function. In this work, we present a new direct search method, based on simplex methods, for general constrained optimization that combines the features of the simplex method and filter methods. This method does not compute or approximate any derivatives, penalty constants or Lagrange multipliers. The basic idea of simplex filter algorithm is to construct an initial simplex and use the simplex to drive the search. We illustrate the behavior of our algorithm through some examples. The proposed methods were implemented in Java.

Filters method in direct search optimization, new measures to admissibility

Constrained nonlinear optimization problems are usually solved using penalty or barrier methods combined with unconstrained optimization methods. Another alternative used to solve constrained nonlinear optimization problems is the lters method. Filters method, introduced by Fletcher and Ley er in 2002, have been widely used in several areas of constrained nonlinear optimization. These methods treat optimization problem as bi-objective attempts to minimize the objective function and a continuous function that aggregates the constraint violation functions. Audet and Dennis have presented the rst lters method for derivative-free nonlinear programming, based on pattern search methods. Motivated by this work we have de- veloped a new direct search method, based on simplex methods, for general constrained optimization, that combines the features of the simplex method and lters method. This work presents a new variant of these methods which combines the lters method with other direct search methods and are proposed some alternatives to aggregate the constraint violation functions.

A relação entre a preparação para a parentalidade no terceiro trimestre de gravidez e os níveis de atividade física das gestantes

Introdução: A atividade física (AF) parece ter um impacto positivo na saúde física e mental durante a gravidez, nascimento e puerpério, sendo que os programas de preparação para a parentalidade (PPP) poderão ser fundamentais para o seu suporte e estimulação. Objetivos: O objetivo do presente estudo foi avaliar a relação entre a preparação para a parentalidade no 3º trimestre de gravidez e os níveis de AF da gestante. Especificamente pretendeu-se verificar a relação entre as caraterísticas sociodemográficas das gestantes, os níveis de ansiedade e o PPP. Métodos: Efetuou-se um estudo transversal analítico onde se utilizaram duas amostras. Uma constituída por 42 gestantes que frequentaram o PPP no CHTS (GPP) e outra por 41 gestantes do HSJ que não frequentou (GNPP). A cada gestante foi pedido que preenchessem 3 questionários (caraterização sociodemográfica e saúde obstétrica, Questionário de Atividade Física para gestantes-PPAQ e Escala de ansiedade de Zung), administrados, individualmente, por um Fisioterapeuta. Resultados: Não se verificaram diferenças entre os grupos relativamente ao score da AF total (p=0,615), contudo, o GPP apresentou um número superior de gestantes que praticava desporto organizado durante a gravidez (p=0,016) comparativamente ao GNPP. Relativamente à intensidade da AF, verificou-se que o GPP apresentava uma prática maior de AF vigorosa (p=0,023). No que diz respeito ao tipo de AF, o GPP apresentou um número superior de gestantes a praticar AF desportiva (p<0,001) enquanto no GNPP se verificou uma maior AF ocupacional (p=0,002). Relativamente às caraterísticas sociodemográficas verificaram-se diferenças estatisticamente significativas entre os dois grupos relativamente à idade (p<0,001), paridade (p<0,001) e nível educacional (p<0,001). No que respeita aos níveis de ansiedade não se verificaram diferenças estatisticamente significativas entre os grupos (GPP vs GNPP p=0,916). Conclusão: No GPP um maior número de gestantes praticava atividade física desportiva e de intensidade vigorosa. Verificaram-se diferenças entre os dois grupos no que diz respeito à idade, paridade e nível educacional. Não se verificou associação entre o PPP e os níveis de ansiedade durante este período.

Adaptive Penalty and Barrier function based on Fuzzy Logic

Optimization methods have been used in many areas of knowledge, such as Engineering, Statistics, Chemistry, among others, to solve optimization problems. In many cases it is not possible to use derivative methods, due to the characteristics of the problem to be solved and/or its constraints, for example if the involved functions are non-smooth and/or their derivatives are not know. To solve this type of problems a Java based API has been implemented, which includes only derivative-free optimization methods, and that can be used to solve both constrained and unconstrained problems. For solving constrained problems, the classic Penalty and Barrier functions were included in the API. In this paper a new approach to Penalty and Barrier functions, based on Fuzzy Logic, is proposed. Two penalty functions, that impose a progressive penalization to solutions that violate the constraints, are discussed. The implemented functions impose a low penalization when the violation of the constraints is low and a heavy penalty when the violation is high. Numerical results, obtained using twenty-eight test problems, comparing the proposed Fuzzy Logic based functions to six of the classic Penalty and Barrier functions are presented. Considering the achieved results, it can be concluded that the proposed penalty functions besides being very robust also have a very good performance.