Specialized genetic algorithm for transmission network expansion planning considering reliability
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Institute of Electrical and Electronics Engineers (IEEE)
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Resumo
This paper presents a methodology to solve the transmission network expansion planning problem (TNEP) considering reliability and uncertainty in the demand. The proposed methodology provides an optimal expansion plan that allows the power system to operate adequately with an acceptable level of reliability and in an enviroment with uncertainness. The reliability criterion limits the expected value of the reliability index (LOLE - Loss Of Load Expectation) of the expanded system. The reliability is evaluated for the transmission system using an analytical technique based in enumeration. The mathematical model is solved, in a efficient way, using a specialized genetic algorithm of Chu-Beasley modified. Detailed results from an illustrative example are presented and discussed. © 2009 IEEE.
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Genetic algorithm , Mixed-integer non linear programming , Reliability , Transmission expansion planning , Analytical techniques , Expansion plans , Expected values , Illustrative examples , Loss of load expectation , Power systems , Reliability criterion , Reliability Index , Transmission network expansion planning , Transmission systems , Dynamic programming , Electric power transmission , Electric power transmission networks , Genetic algorithms , Integer programming , Intelligent systems , Linearization , Mathematical models , Optimization
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2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09.
