An effective non-iterative “ λ-logic based” algorithm for economic dispatch of generators with cubic fuel cost function

• Published in: International journal of electrical power & energy systems Vol. 32; no. 5; pp. 539 - 542
• Main Authors: Theerthamalai, Adhinarayanan, Maheswarapu, Sydulu
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.06.2010; Elsevier
• Subjects: Algorithms; Applied sciences; Cost function; Cubic cost function; Dealing; Demand; Economic dispatch (ED); Economics; Electrical engineering. Electrical power engineering; Electrical power engineering; Exact sciences and technology; Fuels; Generators; Incremental fuel cost of ith unit ( dF i/ dP i); Marketing; Miscellaneous; Operation. Load control. Reliability; Power demand ( P D); Power networks and lines; Pre-prepared power demand (PPD); Cubic cost function; Incremental fuel cost of ith unit ( dF i / dP i ); Economic dispatch (ED); Pre-prepared power demand (PPD); Power demand ( P D ); Dispatching problem; Power demand; Incremental fuel cost of ith unit (dF; Optimization method; Iterative method; ); dP; Algorithm; Non linear phenomenon; Time distribution; Computation time; Electrical network; Cost function; Power demand (P; Economic aspect; Economic impact; Non linear effect
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2009.11.002

This paper presents a very fast and effective non-iterative “ λ-logic based” algorithm for economic dispatch (ED) with cubic cost function of thermal units. Representation of generator fuel cost curves by polynomials in real-time economic dispatch is standard practice in the industry and it shows a great influence on the accuracy of the economic dispatch solution. As the proposed approach is a direct or non-iterative method, it does not demand any initial guess values for ED of units for given demand ( P D ). Many of the existing conventional methods fail to impose p-limits at violating units and find difficult in dealing with cubic cost function that reflect nonlinearity of the actual generator response. The proposed method is very efficient for both small and large size of generating units with cubic fuel cost function in the problem and it remarkably reduces the computation time. The proposed algorithm has been tested successfully on three units, five units and 26 units and results are reported in the paper.