Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-03-04T19:04:18Z No. of bitstreams: 1 felipegomesduque.pdf: 1280593 bytes, checksum: 1f3d9c0ec3a41fa23d8f1844be3efc5c (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-04-24T01:56:12Z (GMT) No. of bitstreams: 1 felipegomesduque.pdf: 1280593 bytes, checksum: 1f3d9c0ec3a41fa23d8f1844be3efc5c (MD5) / Made available in DSpace on 2016-04-24T01:56:12Z (GMT). No. of bitstreams: 1 felipegomesduque.pdf: 1280593 bytes, checksum: 1f3d9c0ec3a41fa23d8f1844be3efc5c (MD5) Previous issue date: 2016-07-19 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Este trabalho apresenta um algoritmo baseado na técnica de otimização bio-inspirada denominada Monkey Search (MS) para alocação ótima de bancos de capacitores em sistemas de distribuição. O método proposto apresenta modificações e aprimoramentos da técnica MS para representar de forma adequada às características e restrições do problema de alocação de capacitores resultando em um novo algoritmo denominado Modified Monkey Search (MMS). O programa desenvolvido em MATLAB é utilizado para teste em diversos sistemas de distribuição. Os resultados obtidos apontam para um algoritmo com boa eficiência computacional. / This paper presents an algorithm based on bio-inspired optimization technique called Monkey Search (MS) for optimal allocation of capacitors in distribution systems. The proposed method presents modifications and enhancements of the MS technique to represent the characteristics and constraints of the problem related with capacitor allocation resulting in a new algorithm called Modified Monkey Search (MMS). The program developed in MATLAB is used to test multiple distribution systems. The results point to a computational efficient algorithm.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-09-21T17:53:15Z No. of bitstreams: 1 cristianogomescasagrande.pdf: 637689 bytes, checksum: 8110c0aa199d98fa3f68855ccb257b82 (MD5) / Approved for entry into archive by Diamantino Mayra (mayra.diamantino@ufjf.edu.br) on 2016-09-26T20:27:35Z (GMT) No. of bitstreams: 1 cristianogomescasagrande.pdf: 637689 bytes, checksum: 8110c0aa199d98fa3f68855ccb257b82 (MD5) / Made available in DSpace on 2016-09-26T20:27:35Z (GMT). No. of bitstreams: 1 cristianogomescasagrande.pdf: 637689 bytes, checksum: 8110c0aa199d98fa3f68855ccb257b82 (MD5) Previous issue date: 2010-08-13 / A necessidade de redução do custo associado à operação dos sistemas de distribuição de energia elétrica tem se tornado cada vez mais imperativa no cenário do setor energético. Uma das principais alternativas para resolver este problema é a minimização de perdas de potência ativa nos alimentadores de distribuição. A fim de reduzir as perdas, algumas práticas têm sido adotadas, como a alocação de capacitores em pontos estratégicos do sistema, bem como o ajuste de tapes de transformadores e reconfiguração de redes de distribuição. A solução de problemas desse tipo envolve complexos algoritmos de otimização não linear inteira mista. Nesse contexto, este trabalho apresenta uma técnica especializada baseada na meta-heurística colônia de formigas para solucionar o problema de minimização de perdas nos sistemas de distribuição de energia elétrica através da alocação ótima de capacitores combinada ao ajuste de tapes, além de considerar restrições de violação de tensão. O algoritmo desenvolvido propõe modificações na estrutura básica do problema, a fim de obter resultados melhores. A metodologia proposta é aplicada a sistemas encontrados na literatura e resultados são comparados com outros métodos. / The reduce the cost associated with the operation of electric power distribution systems has become increasingly imperative in the setting of the energy sector. One of the main alternatives to solve this problem is to minimize power losses in distribution feeders. In order to reduce losses, some practices have been adopted, such as the allocation of capacitors at strategic points in the system as well as LTC adjustment and reconfiguration of distribution networks. The solution of such problems involves complex algorithms for nonlinear mixed integer optimization. Therefore, this paper presents a specialized technique based on meta-heuristic ant colony optimization to solve the problem of minimizing losses in electric power distribution systems through the optimal capacitor placement combined with the LTC adjustment, and consider constraints voltage violation. This algorithm proposes changes to the basic structure of the problem in order to obtain better results. The proposed methodology is applied to systems found in the literature and results are compared with other methods.

This research presents a Hybrid Particle Swarm Optimization with Bat Algorithm (HPSOBA) based approach to solve Optimal Reactive Power Dispatch (ORPD) problem. The primary objective of this project is minimization of the active power transmission losses by optimally setting the control variables within their limits and at the same time making sure that the equality and inequality constraints are not violated. Particle Swarm Optimization (PSO) and Bat Algorithm (BA) algorithms which are nature-inspired algorithms have become potential options to solving very difficult optimization problems like ORPD. Although PSO requires high computational time, it converges quickly; while BA requires less computational time and has the ability of switching automatically from exploration to exploitation when the optimality is imminent. This research integrated the respective advantages of PSO and BA algorithms to form a hybrid tool denoted as HPSOBA algorithm. HPSOBA combines the fast convergence ability of PSO with the less computation time ability of BA algorithm to get a better optimal solution by incorporating the BA’s frequency into the PSO velocity equation in order to control the pace. The HPSOBA, PSO and BA algorithms were implemented using MATLAB programming language and tested on three (3) benchmark test functions (Griewank, Rastrigin and Schwefel) and on IEEE 30- and 118-bus test systems to solve for ORPD without DG unit. A modified IEEE 30-bus test system was further used to validate the proposed hybrid algorithm to solve for optimal placement of DG unit for active power transmission line loss minimization. By comparison, HPSOBA algorithm results proved to be superior to those of the PSO and BA methods. In order to check if there will be a further improvement on the performance of the HPSOBA, the HPSOBA was further modified by embedding three new modifications to form a modified Hybrid approach denoted as MHPSOBA. This MHPSOBA was validated using IEEE 30-bus test system to solve ORPD problem and the results show that the HPSOBA algorithm outperforms the modified version (MHPSOBA). / Electrical and Mining Engineering / M. Tech. (Electrical Engineering)