Minimum cost generation unit expansion planning using real coded improved genetic algorithm
Minimum cost generation unit expansion planning using real coded improved genetic algorithm
- Author(s): M.J. Ahila ; S.J. Jawhar ; N.A. Singh
- DOI: 10.1049/ic.2013.0360
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- Author(s): M.J. Ahila 1 ; S.J. Jawhar 2 ; N.A. Singh 3
- Conference: IET Chennai Fourth International Conference on Sustainable Energy and Intelligent Systems (SEISCON 2013)
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Source:
IET Chennai Fourth International Conference on Sustainable Energy and Intelligent Systems (SEISCON 2013),
2013
p.
497 – 503
Affiliations:
1: Electr. Eng. Dept., Gov. Polytech. Coll., Nagercoil, India
2: Arunachala Coll. Eng. for Woman, Manavillai, India
3: Bharat Sanchar Nigam Ltd., Nagercoil, India
2: Arunachala Coll. Eng. for Woman, Manavillai, India
3: Bharat Sanchar Nigam Ltd., Nagercoil, India
- DOI: 10.1049/ic.2013.0360
- ISBN: 978-1-78561-030-1
- Location: Chennai, India
- Conference date: 12-14 Dec. 2013
- Format: PDF
This paper presents a development of Real Coded Improved Genetic Algorithm (RCIGA) and its application to a minimum cost generation unit expansion planning (GUEP) problem. GUEP is a highly constrained non linear system, so it can be solved by any one of the optimization techniques called genetic algorithm. RCIGA is a global optimizer and it provides faster convergence speed and the search space is increased. In this method, the GUEP solution is vectors of real values. RCIGA is used to calculate the combination of units to obtain minimum cost function and meet out the forecasted demand. The RCIGA approach is applied to the test system of five candidate units and fifteen existing units with 7 period of planning.
Inspec keywords: vectors; genetic algorithms; power generation planning; load forecasting; power generation economics
Subjects: Power system planning and layout; Optimisation techniques; Power system management, operation and economics; Algebra; Generating stations and plants
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