Combined heat and power economic dispatch by mesh adaptive direct search algorithm

Authors:
Seyyed Soheil Sadat Hosseini;Ali Jafarnejad;Amir Hossein Behrooz;Amir Hossein Gandomi
Affiliations:
College of Electrical Engineering, Tafresh University, Tafresh, Iran;Department of Construction Management & Engineering, Islamic Azad University, Science and Research Branch, Tehran, Iran;Faculty of Management and Accounting, Allameh Tabatabai University, Tehran, Iran;College of Civil Engineering, Tafresh University, Tafresh, Iran and The Highest Prestige Scientific and Professional National Foundation, National Elites Foundation, Tehran, Iran
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Corrigendum: Comment on "Combined heat and power economic dispatch by mesh adaptive direct search algorithm" by Sadat Hosseini et al. [Expert Syst. Appl. 38 (2011) 6556-6564]

Expert Systems with Applications: An International Journal

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Abstract

The optimal utilization of multiple combined heat and power (CHP) systems is a complex problem. Therefore, efficient methods are required to solve it. In this paper, a recent optimization technique, namely mesh adaptive direct search (MADS) is implemented to solve the combined heat and power economic dispatch (CHPED) problem with bounded feasible operating region. Three test cases taken from the literature are used to evaluate the exploring ability of MADS. Latin hypercube sampling (LHS), particle swarm optimization (PSO) and design and analysis of computer experiments (DACE) surrogate algorithms are used as powerful SEARCH strategies in the MADS algorithm to improve its effectiveness. The numerical results demonstrate that the utilized MADS-LHS, MADS-PSO, MADS-DACE algorithms have acceptable performance when applied to the CHPED problems. The results obtained using the MADS-DACE algorithm are considerably better than or as well as the best known solutions reported previously in the literature. In addition to the superior performance, MADS-DACE provides significant savings of computational effort.