"A high-performance social spider optimization algorithm for optimal power flow solution with single objective optimization", a published research in the premier specialized journal
The research entitled "A high-performance social spider optimization algorithm for optimal power flow solution with single objective optimization", was published in Energy Journal (ISSN: 0360-5442), by Elsevier Publishing, The Netherlands with an Impact Factor (IF) of 5,537 (according to Journal Citation Reports, Clarivate, USA); and H-index of 158 (according to Scimago, SJR, Spain) in the ISI list. Energy is ranked as the premier specialized journal of the narrow specialization of Civil and Structural Engineering (SJR) according to the internationally published ranking system of Ton Duc Thang University (TDTU).
Energy Journal according to the ranking system of SJR (Scimago)
The sole author of this research is Dr. Nguyen Trung Thang, Head of Power System Optimization Research Group (PSO), Faculty of Electrical and Electronics Engineering. He has published over 32 research papers in prestigious ISI journals. This is the result of a long and elaborate research process, as the articles published on Energy, which has very high requirements for novelty and pioneering.
Dr. Nguyen Trung Thang, Head of Power System Optimization Research Group (PSO) Faculty of Electrical and Electronics Engineering, TDTU
This study proposed a high-performance Social Spider algorithm (HPSSA) to independently optimize electricity generation fuel cost, power loss, polluted emission, voltage deviation, and L index for transmission power networks. The performance of the proposed HPSSA method is evaluated by testing on three IEEE systems with 30, 57, and 118 buses. As a result, the proposed method has advantages over its conventional method such as simpler application, the fewer number of control parameters, spend less time tuning control parameter values, faster convergence to optimal solutions, and more stable searchability. In addition, the proposed method's results are also compared to other existing methods and the indications are that the proposed method can find better optimal solutions, use a lower number of generated solutions, and faster convergence. The proposed method can be a good method for applications in other fields or other problems in power systems.
The photo of the article on Energy
Reference: Thang Trung Nguyen; A high performance social spider optimization algorithm for optimal power flow solution with single objective optimization; Energy, Volume 171, 15th March 2019, Pages 218-240.