New modified algorithm: θ-turbulent flow of water-based optimization

• Published in: Environmental science and pollution research international Vol. 30; no. 28; pp. 71726 - 71740
• Main Authors: Naderipour, Amirreza, Davoudkhani, Iraj Faraji, Abdul-Malek, Zulkurnain
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2023; Springer Nature B.V
• Subjects: Algorithms; Alternative energy sources; Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Biogeography; Circular Economy for Global Water Security; Continuity (mathematics); Earth and Environmental Science; Ecotoxicology; Electric power distribution; Electric Power Supplies; Electrical engineering; Electricity distribution; Environment; Environmental Chemistry; Environmental Health; Environmental science; Fluid dynamics; Optics; Optimization; Power; Power control; Reactive power; Shunt capacitors; spiders; Turbulent flow; Waste Water Technology; Water; Water Management; Water Pollution Control; ORPD problem; turbulent flow of water-based optimization; Power systems; TFWO; Control variables; θ-turbulent flow of water-based optimization (θ-TFWO)
• ISSN: 1614-7499; 0944-1344; 1614-7499
• DOI: 10.1007/s11356-021-16072-x

The reactive power control of a power system is discussed under two types of variables: continuous variables (e.g., generator bus voltages) and discrete variables (e.g., transformer taps and the size of switched shunt capacitors). This paper proposes a novel and powerful algorithm, named turbulent flow of water-based optimization (TFWO) as well as a new improved version of this algorithm, called θ -TFWO, for optimal reactive power distribution (ORPD) to reduce losses. The proposed method is applied to two large-scale IEEE 57-bus systems. Furthermore, to demonstrate the competitive performance of the suggested algorithm, its performance was compared to that of several other algorithms, including biogeography-based optimization (BBO), social spider algorithm (SSA), and optics inspired optimization (OIO), in terms of solving the ORPD problem. The results confirmed the robustness and effectiveness of the proposed method as a powerful optimizer applicable to optimal reactive power distribution in power systems.