Abstract

This paper addresses the challenges of economic dispatch (ED) optimization, with a particular focus on incorporating environmental constraints. Previous studies have highlighted the effectiveness of decision tree (DT) architectures in tackling these challenges. Building on this foundation, a novel approach is introduced by integrating fuzzy logic (FL) into unit limit considerations, resulting in the development of a bell-shaped fuzzy logic-based decision tree (FLDT). This innovative method leverages bell-shaped curves for efficient nonlinear assessments of cost and emission level functions, which are particularly advantageous for managing complex thermal power plants with significant nonlinearities. The incorporation of FL enhances the numerical understanding of the process, while the use of bell-shaped functions to smooth power generation boundaries leads to reduced generation costs compared to traditional methods. Furthermore, the model addresses load uncertainty by accounting for imperfect load conditions, providing optimal solutions that balance cost efficiency and uncertainty management. To validate the methodology, it was applied to a 6-unit institute of electrical and electronics engineers (IEEE) evaluation system, demonstrating substantial performance improvements over previous approaches. The study highlights the practical significance and superior performance of the bell-shaped fuzzy decision trees (BSFDT) approach in addressing ED optimization challenges.

Keywords

Economic dispatch, Fuzzy logic, Decision tree, Optimization, Bell-shaped fuzzy decision trees.

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