skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: OPTIMIZATION OF LONG RURAL FEEDERS USING A GENETIC ALGORITHM

Abstract

This paper describes the optimization of conductor size and the voltage regulator location and magnitude of long rural distribution lines. The optimization minimizes the lifetime cost of the lines, including capital costs and losses while observing voltage drop and operational constraints using a Genetic Algorithm (GA). The GA optimization is applied to a real Single Wire Earth Return (SWER) network in regional Queensland and results are presented.

Authors:
; ;  [1];  [2]
+ Show Author Affiliations
  1. Queensland University of Technology, Brisbane, Queensland (Australia)
  2. Ergon Energy, Toowoomba, Queensland (Australia)
Publication Date:
OSTI Identifier:
21366928
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 1239; Journal Issue: 1; Conference: 3. global conference on power control and optimization, Gold Coast (Australia), 2-4 Feb 2010; Other Information: DOI: 10.1063/1.3459766; (c) 2010 American Institute of Physics
Country of Publication:
United States
Language:
English
Subject:
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; ALGORITHMS; CAPITALIZED COST; ELECTRIC POTENTIAL; LIFETIME; NEURAL NETWORKS; OPTIMIZATION; QUEENSLAND; VOLTAGE DROP; VOLTAGE REGULATORS; AUSTRALASIA; AUSTRALIA; COST; DEVELOPED COUNTRIES; MATHEMATICAL LOGIC

Citation Formats

Wishart, Michael, Ledwich, Gerard, Ghosh, Arindam, and Ivanovich, Grujica. OPTIMIZATION OF LONG RURAL FEEDERS USING A GENETIC ALGORITHM. United States: N. p., 2010. Web. doi:10.1063/1.3459766.
Copy to clipboard
Wishart, Michael, Ledwich, Gerard, Ghosh, Arindam, & Ivanovich, Grujica. OPTIMIZATION OF LONG RURAL FEEDERS USING A GENETIC ALGORITHM. United States. doi:10.1063/1.3459766.
Copy to clipboard
Wishart, Michael, Ledwich, Gerard, Ghosh, Arindam, and Ivanovich, Grujica. Tue . "OPTIMIZATION OF LONG RURAL FEEDERS USING A GENETIC ALGORITHM". United States. doi:10.1063/1.3459766.
Copy to clipboard
@article{osti_21366928,
title = {OPTIMIZATION OF LONG RURAL FEEDERS USING A GENETIC ALGORITHM},
author = {Wishart, Michael and Ledwich, Gerard and Ghosh, Arindam and Ivanovich, Grujica},
abstractNote = {This paper describes the optimization of conductor size and the voltage regulator location and magnitude of long rural distribution lines. The optimization minimizes the lifetime cost of the lines, including capital costs and losses while observing voltage drop and operational constraints using a Genetic Algorithm (GA). The GA optimization is applied to a real Single Wire Earth Return (SWER) network in regional Queensland and results are presented.},
doi = {10.1063/1.3459766},
journal = {AIP Conference Proceedings},
number = 1,
volume = 1239,
place = {United States},
year = {Tue Jun 15 00:00:00 EDT 2010},
month = {Tue Jun 15 00:00:00 EDT 2010}
}
Copy to clipboard
Journal Article:
DOI:  10.1063/1.3459766
Other availability
Find in Google Scholar Find in Google Scholar
Search WorldCat Search WorldCat to find libraries that may hold this journal
Save / Share:
Export Metadata
Save to My Library
You must Sign In or Create an Account in order to save documents to your library.

  • ; - Transactions of the American Nuclear Society
    A parametric analysis has been performed on reactor fuel reloading taking into consideration the arrangement of the fuel assemblies. Neutronics calculations and assembly reactivities are discussed.

  • ; ; - IEEE Transactions on Power Systems
    This paper presents an improved simple genetic algorithm developed for reactive power system planning. The successive linear programming (LP) is used to solve operational optimization sub-problems. New population selection and generation method which makes the use of Benders` cut is presented in this paper. It is desirable to find the optimal solution in few iterations, especially in some test cases where the optimal results are expected to be obtained easily. However, the simple genetic algorithm has failed in finding the solution except through an extensive number of iterations. Different population generation and crossover methods are also tested and discussed. Themore » method has been tested for 6 bus and 30 bus systems to show its effectiveness. Further improvement for the method is discussed.« less

  • ; - Food and Bioprocess Technology
    Abstract In the present study, response surface method (RSM) and genetic algorithm (GA) were used to study the effects of process variables like screw speed, rpm (x1), L/D ratio (x2), barrel temperature ( C; x3), and feed mix moisture content (%; x4), on flow rate of biomass during single-screw extrusion cooking. A second-order regression equation was developed for flow rate in terms of the process variables. The significance of the process variables based on Pareto chart indicated that screw speed and feed mix moisture content had the most influence followed by L/D ratio and barrel temperature on the flow rate.more » RSM analysis indicated that a screw speed>80 rpm, L/D ratio> 12, barrel temperature>80 C, and feed mix moisture content>20% resulted in maximum flow rate. Increase in screw speed and L/D ratio increased the drag flow and also the path of traverse of the feed mix inside the extruder resulting in more shear. The presence of lipids of about 35% in the biomass feed mix might have induced a lubrication effect and has significantly influenced the flow rate. The second-order regression equations were further used as the objective function for optimization using genetic algorithm. A population of 100 and iterations of 100 have successfully led to convergence the optimum. The maximum and minimum flow rates obtained using GA were 13.19 10 7 m3/s (x1=139.08 rpm, x2=15.90, x3=99.56 C, and x4=59.72%) and 0.53 10 7 m3/s (x1=59.65 rpm, x2= 11.93, x3=68.98 C, and x4=20.04%).« less

  • ; - Computer Methods in Applied Mechanics and Engineering
    Abstract not provided.

  • ; ; ; ... - Industrial and Engineering Chemistry Research
    An existing side-fired stream reformer is simulated using a rigorous model with proven reaction kinetics, incorporating aspects of heat transfer in the furnace and diffusion in the catalyst pellet. Thereafter, optimal conditions, which could lead to an improvement in its performance, are obtained. An adaptation of the nondominated sorting genetic algorithm is employed to perform a multiobjective optimization. For a fixed production rate of hydrogen from the unit, the simultaneous minimization of the methane feed rate and the maximization of the flow rate of carbon monoxide in the syngas are chosen as the two objective functions, keeping in mind themore » processing requirements, heat integration, and economics. For the design configuration considered in this study, sets of Pareto-optimal operating conditions are obtained. The results are expected to enable the engineer to gain useful insights into the process and guide him/her in operating the reformer to minimize processing costs and to maximize profits.« less