Biogeography-Based Optimization for solution of Optimal Power Flow problem

This Paper presents a Biogeography-Based Optimization (BBO) algorithm to solve Optimal Power Flow (OPF) problems OPF) problems of a power system with generators having quadratic fuel cost characteristics. Different operational constraints such as generator capacity limits, power balance constraint,...

Full description

Saved in:
Bibliographic Details
Published inECTI-CON2010: The 2010 ECTI International Confernce on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology pp. 435 - 439
Main Authors Bhattacharya, Aniruddha, Chattopadhyay, Pranab Kumar
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2010
Subjects
Biogeography
Character generation
Cost function
Fuels
Load flow
Mathematical model
Power generation
Power system modeling
Reactive power control
Voltage control
Online AccessGet full text

Cover

More Information
Summary:This Paper presents a Biogeography-Based Optimization (BBO) algorithm to solve Optimal Power Flow (OPF) problems OPF) problems of a power system with generators having quadratic fuel cost characteristics. Different operational constraints such as generator capacity limits, power balance constraint, line flow limits, bus voltages, transformer tap settings and reactive power compensating device settings have been considered as control variables in the problem formulation. Mathematical models of Biogeography describe how a species arise, migrates from one habitat to another and gets wiped out. The algorithm developed using this concept is known as Biogeography-Based Optimization (BBO). This algorithm searches for the global optimum mainly through two steps: Migration and Mutation. BBO has been implemented on the standard IEEE 30-bus system for two different objectives that reflect fuel cost minimization and voltage profile improvement with the OPF embedded. The superiority of the proposed method over other methods has been demonstrated for these two different objectives. Considering the quality of the solution obtained the proposed method seems to be a promising alternative approach for solving the OPF problems.
ISBN:9781424456062
1424456061