Layout Optimization of a Tidal Current Turbine Array Based on Quantum Discrete Particle Swarm Algorithm

This article focuses on the optimization of the layout of a tidal current turbine array (TCTA) using the Quantum Discrete Particle Swarm (QDPS) algorithm. The objective of the optimization is to balance the maximum energy output and minimum levelized cost of energy (LCOE). The optimization model pro...

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Vydané v:	Journal of marine science and engineering Ročník 11; číslo 10; s. 1994
Hlavní autori:	Wu, Yanan, Wu, He, Kang, Hooi-Siang, Li, He
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.10.2023
Predmet:	Algorithms Analysis Arrays Creeks & streams Efficiency Electric power production Energy Energy output Experiments Force and energy Genetic algorithms Layouts levelized cost of energy Modelling Ocean currents Ocean models Optimization algorithms Optimization models Partial differential equations quantum discrete particle swarm Spring tides tidal current turbine array Tidal currents tidal energy Tidal models Turbine engines Turbines Wakes Waterways Wind farms United Kingdom China
ISSN:	2077-1312, 2077-1312
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Abstract	This article focuses on the optimization of the layout of a tidal current turbine array (TCTA) using the Quantum Discrete Particle Swarm (QDPS) algorithm. The objective of the optimization is to balance the maximum energy output and minimum levelized cost of energy (LCOE). The optimization model proposed in this paper was constructed by combining a computational tidal model and the QDPS algorithm, which incorporate several advancements, including modeling of underwater terrain, obtaining tidal current field using high-fidelity ocean model, considering turbine properties, formulating partial influence of wakes on turbines, accounting for interactions between multiple wakes, modeling of safe operating distance, developing an LCOE model, and computing the sea space utilization area of a tidal farm. The proposed method was applied to optimize the layout of TCTA in a real waterway, which employed maximum tidal current fields during flooding and ebbing periods of spring tides as input for safety reasons. The results indicate that compared to a regular staggered layout, the total power generation improved by 19% and 16%, and the LCOE reduced by 12% and 15%, respectively, when the concluded optimized layout was utilized. Sea area decreased by 24% when LCOE was minimum. Overall, the proposed method has a better performance and can support the set selection as well as turbines placements of tidal current farms.
AbstractList	This article focuses on the optimization of the layout of a tidal current turbine array (TCTA) using the Quantum Discrete Particle Swarm (QDPS) algorithm. The objective of the optimization is to balance the maximum energy output and minimum levelized cost of energy (LCOE). The optimization model proposed in this paper was constructed by combining a computational tidal model and the QDPS algorithm, which incorporate several advancements, including modeling of underwater terrain, obtaining tidal current field using high-fidelity ocean model, considering turbine properties, formulating partial influence of wakes on turbines, accounting for interactions between multiple wakes, modeling of safe operating distance, developing an LCOE model, and computing the sea space utilization area of a tidal farm. The proposed method was applied to optimize the layout of TCTA in a real waterway, which employed maximum tidal current fields during flooding and ebbing periods of spring tides as input for safety reasons. The results indicate that compared to a regular staggered layout, the total power generation improved by 19% and 16%, and the LCOE reduced by 12% and 15%, respectively, when the concluded optimized layout was utilized. Sea area decreased by 24% when LCOE was minimum. Overall, the proposed method has a better performance and can support the set selection as well as turbines placements of tidal current farms.
Audience	Academic
Author	Kang, Hooi-Siang Li, He Wu, He Wu, Yanan
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SubjectTerms	Algorithms Analysis Arrays Creeks & streams Efficiency Electric power production Energy Energy output Experiments Force and energy Genetic algorithms Layouts levelized cost of energy Modelling Ocean currents Ocean models Optimization algorithms Optimization models Partial differential equations quantum discrete particle swarm Spring tides tidal current turbine array Tidal currents tidal energy Tidal models Turbine engines Turbines Wakes Waterways Wind farms
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Title	Layout Optimization of a Tidal Current Turbine Array Based on Quantum Discrete Particle Swarm Algorithm
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