Non-Dominated Sorting-Based Hybrid Optimization Technique for Multi-Objective Hydrothermal Scheduling

Gouthamkumar Nadakuditi, Harish Pulluri (), Preeti Dahiya, K. S. R. Murthy, P. Srinivasa Varma, Mohit Bajaj (), Torki Altameem (), Walid El-Shafai and Mostafa M. Fouda
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Gouthamkumar Nadakuditi: Department of Fire Engineering, National Fire Service College, Ministry of Home Affairs, Government of India, Nagpur 440013, India
Harish Pulluri: Department of Electrical and Electronics Engineering, Anurag University, Hyderabad 500088, India
Preeti Dahiya: Electrical Engineering, Skill Faculty of Engineering and Technology, Shri Vishwakarma Skill University, Gurugram 121102, India
K. S. R. Murthy: NIT, Andhra Pradesh, Tadepallegudem 534101, India
P. Srinivasa Varma: Department of Electrical and Electronics Engineering, Koneru Lakshmaiah Education Foundation, Guntur 522302, India
Mohit Bajaj: Department of Electrical Engineering, Graphic Era (Deemed to be University), Dehradun 248002, India
Torki Altameem: Computer Science Department, Community College, King Saud University, Riyadh 11451, Saudi Arabia
Walid El-Shafai: Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf 32952, Egypt
Mostafa M. Fouda: Department of Electrical and Computer Engineering, College of Science and Engineering, Idaho State University, Pocatello, ID 83209, USA

Energies, 2023, vol. 16, issue 5, 1-25

Abstract: Short-term hydrothermal scheduling problem plays an important role in maintaining a high degree of economy and reliability in power system operational planning. Since electric power generation from fossil fired plants forms a major part of hydrothermal generation mix, therefore their emission contributions cannot be neglected. Hence, multi-objective short term hydrothermal scheduling is formulated as a bi-objective optimization problem by considering (a) minimizing economical power generation cost, (b) minimizing environmental emission pollution, and (c) simultaneously minimizing both the conflicting objective functions. This paper presents a non-dominated sorting disruption-based oppositional gravitational search algorithm (NSDOGSA) to solve multi-objective short-term hydrothermal scheduling (MSHTS) problems and reveals that (i) the short-term hydrothermal scheduling problem is extended to a multi-objective short-term hydrothermal scheduling problem by considering economical production cost (EPC) and environmental pollution (EEP) simultaneously while satisfying various diverse constraints; (ii) by introducing the concept of non-dominated sorting (NS) in gravitational search algorithm (GSA), it can optimize two considered objectives such as EPC and EEP simultaneously and can also obtain a group of conflicting solutions in one trial simulation; (iii) in NSDOGSA, the objective function in terms fitness for mass calculation has been represented by its rank instead of its EPC & EEP values by using the NS approach; (iv) an elite external archive set is defined to keep the NS solutions with the idea of spread indicator; (v) the optimal schedule value is extracted by using fuzzy decision approach; (vi) a consistent handling strategy has been adopted to handle effectively the system constraints; (vii) finally, the NSDOGSA approach is verified on two test systems with valve point loading effects and transmission loss, and (viii) computational discussion show that the NSDOGSA gives improved optimal results in comparison to other existing methods, which qualifies that the NSDOGSA is an effective and competitive optimization approach for solving complex MSHTS problems.

Keywords: non-dominated sorting; gravitational search algorithm; economical/environmental hydrothermal scheduling; fuzzy decision-making; opposition-based learning; disruption operator (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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