An optimization method for distribution system configuration based on genetic algorithm

1995 ◽  
Author(s):  
M. Kitayama
Keyword(s):  
Genetic Algorithm ◽  
Distribution System ◽  
Optimization Method ◽  
System Configuration

scholarly journals Embedding quasi-static time series within a genetic algorithm for stochastic optimization: the case of reactive power compensation on distribution systems

2020 ◽  
Vol 7 (2) ◽  
pp. 177-194
Author(s):  
Juan M Lujano-Rojas ◽  
Ghassan Zubi ◽  
Rodolfo Dufo-López ◽  
José L Bernal-Agustín ◽  
José L Atencio-Guerra ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Time Series ◽  
Distribution System ◽  
Distribution Systems ◽  
Reactive Power ◽  
Optimization Method ◽  
Reactive Power Compensation ◽  
Optimal Placement ◽  
Computational Time ◽  
Time Required

Abstract This paper presents a methodology for the optimal placement and sizing of reactive power compensation devices in a distribution system (DS) with distributed generation. Quasi-static time series is embedded in an optimization method based on a genetic algorithm to adequately represent the uncertainty introduced by solar photovoltaic generation and electricity demand and its effect on DS operation. From the analysis of a typical DS, the reactive power compensation rating power results in an increment of 24.9% when compared to the classical genetic algorithm model. However, the incorporation of quasi-static time series analysis entails an increase of 26.8% on the computational time required.

scholarly journals Optimal Placement and Sizing of D-STATCOM in Radial and Meshed Distribution Networks Using a Discrete-Continuous Version of the Genetic Algorithm

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1452
Author(s):  
Cristian Mateo Castiblanco-Pérez ◽  
David Esteban Toro-Rodríguez ◽  
Oscar Danilo Montoya ◽  
Diego Armando Giral-Ramírez
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Programming Model ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Power Balance ◽  
Continuous Version ◽  
Discrete Part

In this paper, we propose a new discrete-continuous codification of the Chu–Beasley genetic algorithm to address the optimal placement and sizing problem of the distribution static compensators (D-STATCOM) in electrical distribution grids. The discrete part of the codification determines the nodes where D-STATCOM will be installed. The continuous part of the codification regulates their sizes. The objective function considered in this study is the minimization of the annual operative costs regarding energy losses and installation investments in D-STATCOM. This objective function is subject to the classical power balance constraints and devices’ capabilities. The proposed discrete-continuous version of the genetic algorithm solves the mixed-integer non-linear programming model that the classical power balance generates. Numerical validations in the 33 test feeder with radial and meshed configurations show that the proposed approach effectively minimizes the annual operating costs of the grid. In addition, the GAMS software compares the results of the proposed optimization method, which allows demonstrating its efficiency and robustness.

Multi-objective optimization of optimal capacitor allocation in radial distribution systems

2020 ◽  
Vol 21 (3) ◽  
Author(s):  
Sayed Mir Shah Danish ◽  
Mikaeel Ahmadi ◽  
Atsushi Yona ◽  
Tomonobu Senjyu ◽  
Narayanan Krishna ◽  
...  
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Reactive Power ◽  
Stability Index ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Size ◽  
Multi Objective Optimization ◽  
Multi Objective

AbstractThe optimal size and location of the compensator in the distribution system play a significant role in minimizing the energy loss and the cost of reactive power compensation. This article introduces an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using multi-objective optimization method. A new objective function different from literature is adapted to enhance the overall system voltage stability index, minimize power loss, and to achieve maximum net yearly savings. However, the capacitor sizes are assumed as discrete known variables, which are to be placed on the buses such that it reduces the losses of the distribution system to a minimum. Load sensitive factor (LSF) has been used to predict the most effective buses as the best place for installing compensator devices. IEEE 34-bus and 118-bus test distribution systems are utilized to validate and demonstrate the applicability of the proposed method. The simulation results obtained are compared with previous methods reported in the literature and found to be encouraging.

scholarly journals Optimization of a 3D-Printed Permanent Magnet Coupling Using Genetic Algorithm and Taguchi Method

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 494
Author(s):  
Ekaterina Andriushchenko ◽  
Ants Kallaste ◽  
Anouar Belahcen ◽  
Toomas Vaimann ◽  
Anton Rassõlkin ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Taguchi Method ◽  
Permanent Magnet ◽  
Optimization Problems ◽  
Optimization Method ◽  
Taguchi Optimization ◽  
Torque Density ◽  
Electromagnetic Devices ◽  
3D Printed ◽  
Manufacturing Techniques

In recent decades, the genetic algorithm (GA) has been extensively used in the design optimization of electromagnetic devices. Despite the great merits possessed by the GA, its processing procedure is highly time-consuming. On the contrary, the widely applied Taguchi optimization method is faster with comparable effectiveness in certain optimization problems. This study explores the abilities of both methods within the optimization of a permanent magnet coupling, where the optimization objectives are the minimization of coupling volume and maximization of transmitted torque. The optimal geometry of the coupling and the obtained characteristics achieved by both methods are nearly identical. The magnetic torque density is enhanced by more than 20%, while the volume is reduced by 17%. Yet, the Taguchi method is found to be more time-efficient and effective within the considered optimization problem. Thanks to the additive manufacturing techniques, the initial design and the sophisticated geometry of the Taguchi optimal designs are precisely fabricated. The performances of the coupling designs are validated using an experimental setup.

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