EVOLUTIONARY PROGRAMMING BASED ECONOMIC DISPATCH WITH LINE FLOW CONSTRAINTS

Abstract

International Journal of Computational Engineering ScienceVol. 05, No. 01, pp. 81-89 (2004) No AccessEVOLUTIONARY PROGRAMMING BASED ECONOMIC DISPATCH WITH LINE FLOW CONSTRAINTSP. SOMASUNDARAM, K. KUPPUSAMY, and R. P. KUMUDINI DEVIP. SOMASUNDARAMSchool of Electrical and Electronics Engineering, Anna University, Chennai, Tamil Nadu 600 025, India Search for more papers by this author , K. KUPPUSAMYSchool of Electrical and Electronics Engineering, Anna University, Chennai, Tamil Nadu 600 025, India Search for more papers by this author , and R. P. KUMUDINI DEVISchool of Electrical and Electronics Engineering, Anna University, Chennai, Tamil Nadu 600 025, India Search for more papers by this author https://doi.org/10.1142/S1465876304002277Cited by:1 PreviousNext AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail AbstractThis paper presents an efficient, simple and new method for solving Economic Dispatch (ED) problem with line flow constraints through the application of Evolutionary Programming (EP). The controllable system quantities in the base-case state are optimized to minimize some defined objective function subject to the base-case operating constraints. A 10-bus system is taken for investigation. The ED results obtained using EP are compared with those obtained using quadratic programming. The investigations reveal that the proposed algorithm is relatively simple, reliable, efficient and suitable for on-line applications.Keywords:Power System OptimizationEconomic DispatchEvolutionary ProgrammingLine Flow Constraints References B. H. Chowdhury and S. Rahman, IEEE Transaction on power systems 5(4), 1248 (1990). Crossref, Google Scholar Nanda, L. Hari and M. L. Kothari, IEE Proceedings-C 141(1), 1 (1994). Google ScholarJ. Nandaet al., IEE Proceedings-C 139(1), 39 (1992). Google ScholarJ. Y. Fan and L. Zhang, IEEE Transactions on Power Systems 13(2), 320 (1998). Crossref, Google ScholarP. K. Hota, R. Chakrabarti and P. K. Chattopadhyay, Institute of Engineers (India) Journal-EL 81, 21 (2000). Google ScholarJ. Nanda and R. Badri Narayanan, Electrical Power and Energy Systems 24, 723 (2002). Crossref, Google Scholar D. B. Fogel , Evoluationary Computation: Toward a New Philosophy of Machine Intelligence ( IEEE Press , USA , 1995 ) . Google ScholarL. L. Lai and J. T. Ma, IEEE Transactions on Power Systems 12(1), 198 (1997). Crossref, Google ScholarH. T. Yang, P. C. Yang and C. L. Huang, IEEE Transactions on Power Systems 11(1), 112 (1996). Crossref, Google ScholarK. P. Wong and J. Yuryevich, IEEE Transactions on Power Systems 13(2), 301 (1998). Google ScholarT. Jayabarathi, G. Sadasivam and V. Ramachandran, Electric Power Systems Research 52, 261 (1999). Crossref, Google ScholarT. Jayabarathi and G. Sadasivam, European Transaction on Electrical Power 10(3), 167 (2000). Crossref, Google ScholarP. Attaviriyanupapet al., IEEE Transactions on Power Systems 17(2), 411 (2002). Crossref, Google Scholar FiguresReferencesRelatedDetailsCited By 1FDR PSO-based Transient Stability Constrained Optimal Power Flow Solution for Deregulated Power IndustryM. Anitha, S. Subramanian and R. Gnanadass28 Aug 2007 | Electric Power Components and Systems, Vol. 35, No. 11 Recommended Vol. 05, No. 01 Metrics History KeywordsPower System OptimizationEconomic DispatchEvolutionary ProgrammingLine Flow ConstraintsPDF download