Planejamento de médio e longo prazo de sistemas de distribuição de energia elétrica com geradores distribuídos (GDs) considerando custos de confiabilidade, operação e expansão

Pós-graduação em Engenharia Elétrica - FEIS

Planejamento da expansão do sistema de transmissão de energia elétrica utilizando controladores FACTS

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modelos de programação inteira mista para a alocação ótima de bancos de capacitores em sistemas de distribuição de energia elétrica radias

Pós-graduação em Engenharia Elétrica - FEIS

Algoritmo genético especializado aplicado ao planejamento da expansão de sistemas de distribuição de energia elétrica

Pós-graduação em Engenharia Elétrica - FEIS

Reconfiguração de sistemas de distribuição utilizando metaheurísticas e critérios de confiabilidade

In an ever more competitive environment, power distribution companies must satisfy two conflicting objectives: minimizing investment costs and the satisfaction of reliability targets. The network reconfiguration of a distribution system is a technique that well adapts to this new deregulated environment for it allows improvement of reliability indices only opening and closing switches, without the onus involved in acquiring new equipment. Due to combinatorial explosion problem characteristic, in the solution are employed metaheuristics methods, which converge to optimal or quasi-optimal solutions, but with a high computational effort. As the main objective of this work is to find the best configuration(s) of the distribution system with the best levels of reliability, the objective function used in the metaheuristics is to minimize the LOLC - Loss Of Load Cost, which is associated with both, number and duration of electric power interruptions. Several metaheuristics techniques are tested, and the tabu search has proven to be most appropriate to solve the proposed problem. To characterize computationally the problem of the switches reconfiguring was developed a vector model (with integers) of the representation of the switches, where each normally open switch is associated with a group of normally closed switches. In this model simplifications have been introduced to reduce computational time and restrictions were made to exclude solutions that do not supply energy to any load point of the system. To check violation of the voltage and loading criteria a study of power flow for the ten best solutions is performed. Also for the ten best solutions a reliability evaluation using Monte Carlo sequential simulation is performed, where it is possible to obtain the probability distributions of the indices and thus calculate the risk of paying penalty due to not meeting the goals. Finally, the methodology is applied in a real Brazilian distribution network, and the results are discussed.

A Multi-Stage Stochastic Non-Linear Model for Reactive Power Planning Under Contingencies

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

Alocação ótima de equipamentos SVC e TCSC na rede de transmissão de energia elétrica

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.

Investment recovery period in electric motor of higher efficiency in pumping for irrigation

Neste trabalho, ajustou-se um modelo matemático para quantificar o efeito do rendimento do motor elétrico sobre os custos de um sistema de bombeamento para irrigação na estrutura tarifária de energia elétrica convencional e horo-sazonal verde, bem como calcular o tempo de recuperação do capital investido no equipamento de maior rendimento. em seguida, o mesmo foi aplicado a um sistema de irrigação tipo pivô central em duas opções de rendimento do motor elétrico: 92,6% (linha padrão) e 94,3% (linha alto rendimento), sendo que o custo de aquisição do primeiro correspondeu a 70% do segundo. A potência do motor elétrico era de 100 cv. Os resultados mostraram que o modelo permitiu avaliar se um motor de alto rendimento era viável economicamente em relação ao motor-padrão em cada estrutura tarifária. Nas duas estruturas tarifárias, o motor de alto rendimento não foi viável. Na tarifa horo-sazonal verde, somente seria viável se seu rendimento fosse 4,46% superior ao do motor-padrão. Na tarifa convencional, somente seria viável se o ganho de rendimento superasse 2,71%.

Using ecological thresholds to evaluate the costs and benefits of set-asides in a biodiversity hotspot

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Multicollinearity and financial constraint in investment decisions: a bayesian generalized ridge regression

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.