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

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 f...

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Vydáno v:Environmental science and pollution research international Ročník 30; číslo 28; s. 71726 - 71740
Hlavní autoři: Naderipour, Amirreza, Davoudkhani, Iraj Faraji, Abdul-Malek, Zulkurnain
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2023
Springer Nature B.V
Témata:
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
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Shrnutí: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.
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ISSN:1614-7499
0944-1344
1614-7499
DOI:10.1007/s11356-021-16072-x