Mine blast algorithm for environmental economic load dispatch with valve loading effect

• Published in: Neural computing & applications 2018-07, Vol.30 (1), p.261-270
• Main Authors: Ali, E. S., Abd Elazim, S. M.
• Format: Article
• Language: English
• Subjects: Algorithms; Artificial Intelligence; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Computing time; Data Mining and Knowledge Discovery; Economics; Electric power generation; Environmental impact; Image Processing and Computer Vision; Industrial plant emissions; Optimization; Original Article; Pollutants; Power dispatch; Power plants; Probability and Statistics in Computer Science
• ISSN: 0941-0643; 1433-3058
• DOI: 10.1007/s00521-016-2650-8

Economic load dispatch (ELD) is the process of allocating the required load between the available generation units such that the cost of operation is minimized. The ELD problem is formulated as a nonlinear constrained optimization problem with both equality and inequality constraints. The dual-objective combined economic emission dispatch (CEED) problem is considering the environmental impacts that accumulated from emission of gaseous pollutants of fossil-fueled power plants. In this paper, an implementation of mine blast algorithm (MBA) to solve ELD and CEED problems in power systems is discussed. Results obtained by the proposed MBA are compared with other optimization algorithms for various power systems. The results introduced in this paper show that the proposed MBA outlasts other techniques in terms of total cost and computational time.