Cultured differential computation algorithm for optimal contracted capacity of power consumer with self-owned generating units

Hong-Tzer Yang, Pai Chun Peng, Shr Ching Guo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Contracted capacity setting is a discrete and nonlinear optimization problem in consideration of expenditure on the electricity from the utility and cost of the self-owned generating units (SOGUs) at the same time. This paper proposes the cultured differential computation algorithm (CDCA) to solve this problem. The cultural algorithm (CA) used in the CDCA extracts and saves the domain knowledge or problem properties during the evolution process. The differential computation of the CDCA provides fast converging characteristics in searching the optimal solution through operations of mutation, crossover, and selection operations which are efficient and different from the existing generic algorithm (GA). To verify feasibility of the proposed method, the paper employs the real data obtained from a large optoelectronics factory in Taiwan. In comparison with the existing optimization methods, the proposed CDCA approach has superior results as revealed in the numerical results in terms of the computation time needed and the quality of solution obtained.

Original languageEnglish
Title of host publication16th Power Systems Computation Conference, PSCC 2008
PublisherPower Systems Computation Conference ( PSCC )
ISBN (Electronic)9780947649289
Publication statusPublished - 2008
Event16th Power Systems Computation Conference, PSCC 2008 - Glasgow, United Kingdom
Duration: 2008 Jul 142008 Jul 18

Other

Other16th Power Systems Computation Conference, PSCC 2008
CountryUnited Kingdom
CityGlasgow
Period08-07-1408-07-18

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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