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Optimal power flow with transmission cost solution under bilateral and multilateral transactions

Optimal power flow with transmission cost solution under bilateral and multilateral transactions Abstract In a deregulated electricity market, it is important to dispatch the generation in an economical manner and to ensure security under different operating conditions. In this study evolutionary computation based solution for optimal power flow is attempted. Social welfare optimization is taken as the objective function, which includes generation cost, transmission cost and consumer benefit function. Transmission cost is calculated using Bialek’s power flow tracing method. Severity index is applied as a constraint to measure the security. The objective function is calculated for pre and post contingency periods. Real power generations, real power loads and transformer tap settings are selected as control variables. Different bilateral and multilateral conditions are considered for analysis. A Human Group Optimization algorithm is used to find the solution of the problem. The IEEE 30 bus system is taken as a test system. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Archives of Electrical Engineering de Gruyter

Optimal power flow with transmission cost solution under bilateral and multilateral transactions

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Publisher
de Gruyter
Copyright
Copyright © 2014 by the
ISSN
1427-4221
eISSN
2300-2506
DOI
10.2478/aee-2014-0018
Publisher site
See Article on Publisher Site

Abstract

Abstract In a deregulated electricity market, it is important to dispatch the generation in an economical manner and to ensure security under different operating conditions. In this study evolutionary computation based solution for optimal power flow is attempted. Social welfare optimization is taken as the objective function, which includes generation cost, transmission cost and consumer benefit function. Transmission cost is calculated using Bialek’s power flow tracing method. Severity index is applied as a constraint to measure the security. The objective function is calculated for pre and post contingency periods. Real power generations, real power loads and transformer tap settings are selected as control variables. Different bilateral and multilateral conditions are considered for analysis. A Human Group Optimization algorithm is used to find the solution of the problem. The IEEE 30 bus system is taken as a test system.

Journal

Archives of Electrical Engineeringde Gruyter

Published: Jun 1, 2014

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