This paper presents a novel approach to multi-area economic dispatch problems with multiple fuel options using a hybrid evolutionary programming method. The objective is to minimize the operation cost of the entire system while satisfying the tie line constraints. In this paper, EP-LMO (Evolutionary Programming with Levenberg-Marquardt Optimization) technique is proposed to solve multi-area economic dispatch problems with multiple fuel options. The EP-LMO is developed in such a way that a simple evolutionary programming (EP) is applied as a base level search to find the direction of the optimal global region. And Levenberg-Marquardt Optimization (LMO) method is used as a fine tuning to determine the optimal solution. The applicability and validity of the proposed approach on multi-area economic dispatch problems are presented in two parts. In Part I, two multi-area bench mark problems without fuel options are considered. In Part II, 10 unit system with both multi-area and multi-fuel options is considered. The proposed approach is compared with the results of Incremental Network Flow Programming, Spatial Dynamic Programming and Evolutionary Programming approaches. The results show that the EP-LMO gives the optimum generation cost than any other methods.
Economic Dispatch, Multi-area, Multiple fuel options, Evolutionary programming, Levenberg-Marquardt Optimization
MANOHARAN, P. S.; KANNAN, P. S.; and RAMANATHAN, V.
"A Novel EP Approach for Multi-area Economic Dispatch with Multiple Fuel Options,"
Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 17:
1, Article 1.
Available at: https://journals.tubitak.gov.tr/elektrik/vol17/iss1/1