Optimal switch allocation for automatic load transfer in distribution substations

This work proposes a methodology for optimized allocation of switches for automatic load transfer in distribution systems in order to improve the reliability indexes by restoring such systems which present voltage classes of 23 to 35 kV and radial topology. The automatic switches must be allocated on the system in order to transfer load remotely among the sources at the substations. The problem of switch allocation is formulated as nonlinear constrained mixed integer programming model subject to a set of economical and physical constraints. A dedicated Tabu Search (TS) algorithm is proposed to solve this model. The proposed methodology is tested for a large real-life distribution system. © 2011 IEEE.

Planejamento de redes de distribuição de energia elétrica de média e baixa tensão

Pós-graduação em Engenharia Elétrica - FEIS

Comparison of Reactive Power Support in Distribution Networks Provided by Capacitor Banks and Distributed Generators

This paper presents a comparison of reactive power support in distribution networks provided by switched Capacitor Banks (CBs) and Distributed Generators (DGs). Regarding switched CBs, a Tabu Search metaheuristic algorithm is developed to determine their optimal operation with the objective of reducing the power losses in the lines on the system, while meeting network constraints. on the other hand, the optimal operation of DGs is analyzed through an evolutionary Multi-Objective (MO) programming approach. The objectives of such approach are the minimization of power losses and operation cost of the DGs. The comparison of the reactive power support provided by switched CBs and DGs is carried out using a modified IEEE 34 bus distribution test system.

An improved tabu-based vector optimal algorithm for design optimizations of electromagnetic devices

This paper introduces an improved tabu-based vector optimal algorithm for multiobjective optimal designs of electromagnetic devices. The improvements include a division of the entire search process, a new method for fitness assignment, a novel scheme for the generation and selection of neighborhood solutions, and so forth. Numerical results on a mathematical function and an engineering multiobjective design problem demonstrate that the proposed method can produce virtually the exact Pareto front, in both parameter and objective spaces, even though the iteration number used by it is only about 70% of that required by its ancestor.

Alocação otimizada de bancos de capacitores em sistemas de distribuição de energia elétrica através de metaheurísticas multiobjetivo

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

Algoritmos busca tabu paralelos aplicados ao planejamento da expansão da transmissão de energia elétrica

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Planejamento e projeto de circuitos secundários de distribuição de energia elétrica por meio de algoritmo busca tabu

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Um algoritmo de busca tabu para problemas de localização não capacitados

In this work, a tabu search algorithm for solving uncapacitated location problems is presented. The uncapacitated location problem is a classic problem of localization and occurs in many practical situations. The problem consists in determining in a network, at the minimum possible cost, the better localization, in a network, for the installation of facilities in order to attend the customers' associated demands, at the minimum possible cost. One admits that there exists a cost associated with the opening of a facility and a cost of attendance of each customer by any open facilities. In the particular case of the uncapacitated location problem there is no capacity limitation to attend the customers’ demands. There are some parameters in the algorithm that influence the solution’s quality. These parameters were tested and optimal values for them were obtained. The results show that the proposed algorithm is able to find the optimal solution for all small tested problems keeping the compromise between solution’s quality and computational time. However, to solve bigger problems, the structure of the algorithm must be changed in its structure. The implemented algorithm is integrated to a computational platform for solution of logistic problems

Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation

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

Planning and Projects of Secondary Electric Power Distribution Systems

This paper proposes a methodology to achieve integrated planning and projects for secondary distribution circuits. The planning model is formulated as a mixed integer nonlinear programming problem (MINLP). In order to resolve this problem, a tabu search (TS) algorithm is used, with a neighborhood structure developed to explore the physical characteristics of specific geographies included in the planning and expansion of secondary networks, thus obtaining effective solutions as well as low operating costs and investments. The project stage of secondary circuits consists of calculating the mechanical efforts to determine the support structures of the primary and secondary distribution systems and determining the types of structures that should be used in the system according to topological and electrical parameters of the network and, therefore, accurately assessing the costs involved in the construction and/or reform of secondary systems. A constructive heuristic based on information of the electrical and topological conditions between the medium voltage and low voltage systems is used to connect the primary systems and secondary circuits. The results obtained from planning and design simulations of a real secondary system of electric energy distribution are presented.

Comparative studies on non-convex optimization methods for transmission network expansion planning

We have investigated and extensively tested three families of non-convex optimization approaches for solving the transmission network expansion planning problem: simulated annealing (SA), genetic algorithms (GA), and tabu search algorithms (TS). The paper compares the main features of the three approaches and presents an integrated view of these methodologies. A hybrid approach is then proposed which presents performances which are far better than the ones obtained with any of these approaches individually. Results obtained in tests performed with large scale real-life networks are summarized.

Optimal capacitor placement in radial distribution networks

The capacitor placement (replacement) problem for radial distribution networks determines capacitor types, sizes, locations and control schemes. Optimal capacitor placement is a hard combinatorial problem that can be formulated as a mixed integer nonlinear program. Since this is a NP complete problem (Non Polynomial time) the solution approach uses a combinatorial search algorithm. The paper proposes a hybrid method drawn upon the Tabu Search approach, extended with features taken from other combinatorial approaches such as genetic algorithms and simulated annealing, and from practical heuristic approaches. The proposed method has been tested in a range of networks available in the literature with superior results regarding both quality and cost of solutions.

Comparative studies on non-convex optimization methods for transmission network expansion planning

We have investigated and extensively tested three families of non-convex optimization approaches for solving the transmission network expansion planning problem: simulated annealing (SA), genetic algorithms (GA), and tabu search algorithms (TS). The paper compares the main features of the three approaches and presents an integrated view of these methodologies. A hybrid approach is then proposed which presents performances which are far better than the ones obtained with any of these approaches individually. Results obtained in tests performed with large scale real-life networks are summarized.

Identifying multiple interacting bad data in power system state estimation

This paper presents an intelligent search strategy for the conforming bad data errors identification in the generalized power system state estimation, by using the tabu search meta heuristic. The main objective is to detect critical errors involving both analog and topology errors. These errors are represented by conforming errors, whose nature affects measurements that actually do not present bad data and also the conventional bad data identification strategies based on the normalized residual methods. ©2005 IEEE.

Genetic algorithm of chu and beasley for static and multistage transmission expansion planning

In this paper the genetic algorithm of Chu and Beasley (GACB) is applied to solve the static and multistage transmission expansion planning problem. The characteristics of the GACB, and some modifications that were done, to efficiently solve the problem described above are also presented. Results using some known systems show that the GACB is very efficient. To validate the GACB, we compare the results achieved using it with the results using other meta-heuristics like tabu-search, simulated annealing, extended genetic algorithm and hibrid algorithms. © 2006 IEEE.