Metaheuristic-based Design and optimization of Offshore Wind Farms Collection Systems

Minguijon, Daniel Hermosilla; Pérez-Rúa, Juan-Andrés; Das, Kaushik; Cutululis, Nicolaos Antonio

doi:10.1109/ptc.2019.8810583

Cited by 3 publications

(3 citation statements)

References 12 publications

(20 reference statements)

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“…Hence, heuristic algorithms have been widely applied in solving WTs collection system. Well acknowledged methods are Genetic Algorithm (GA) [9][10], Particle Swarm Optimization (PSO) [11], Simulated Annealing (SA) [12], Ant Colony Optimization (ACO) [13][14], The authors in [14] first determined the location of WT with minimize the wake loss, then proposed an ACO multiple traveling salesman model to minimize the length of cabling.…”

Section: Introductionmentioning

confidence: 99%

GA based algorithms for offshore wind farm collector cable optimization

2022

J. Phys.: Conf. Ser.

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In the capital-intensive offshore wind farm industry, the collector cable optimization problem arises primarily due to electric infrastructure expense contributing high rate of initial investment cost. In this study, a multistage solution was developed for optimal locations, the number of offshore substations (OSSs), and inter-array cable routing determination. In the first, a novel GA method picks up the initial OSSs number and location from the candidate site list, then capacities minimum span tree (CMST) is applied to identify valid cable routings. Finally, optimal OSSs location, quantity, and cable paths are obtained through an iterative process. The results of a library real wind farms case are introduced in paper proves the feasibility of the proposed method and showed this study can apply on real practice for optimal decision in OWF cable design.

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Section: Introductionmentioning

confidence: 99%

GA based algorithms for offshore wind farm collector cable optimization

2022

J. Phys.: Conf. Ser.

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“…The cable layout problem maps to standard computer science problems categorized as NP-Hard (Pérez-Rúa and Cutululis, 2019), implying the lack of efficient methods (polynomial running time algorithms), greatly affecting the tractability for large-scale projects. Proposed methods to approach this problem can be categorized as (1) heuristics (Hou et al, 2016a;Pérez-Rúa et al, 2019a), (2) metaheuristics (Hou et al, 2016b;Minguijón et al, 2019), and (3) global optimization (Fischetti and Pisinger, 2018;Pérez-Rúa et al, 2019b), where mixed integer linear programming (MILP) is the most used formulation. A survey and analysis of these methods can be found in Lumbreras and Ramos (2013) and Pérez-Rúa and Cutululis (2019).…”

Section: Introductionmentioning

confidence: 99%

A framework for simultaneous design of wind turbines and cable layout in offshore wind

Pérez-Rúa¹,

Cutululis

2022

Wind Energ. Sci.

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Abstract. An optimization framework for simultaneous design of wind turbines (WTs) and cable layout for a collection system of offshore wind farms (OWFs) is presented in this paper. The typical approach used in both research and practical design is sequential, with an initial annual energy production (AEP) maximization, followed then by the collection system design. The sequential approach is robust and effective. However it fails to exploit the synergies between optimization blocks. Intuitively, one of the strongest trade-offs is between the WTs and cable layout, as they generally compete; i.e. spreading out WTs mitigates wake losses for larger AEP but also results in longer submarine cables in the collection system and higher costs. The proposed optimization framework implements a gradient-free optimization algorithm to smartly move the WTs within the project area subject to minimum distance constraint, while a fast heuristic algorithm is called in every function evaluation in order to calculate a cost estimation of the cable layout. In a final stage, a refined cable layout design is obtained by iteratively solving a mixed integer linear programme (MILP), modelling all typical engineering constraints of this particular problem. A comprehensive performance analysis of the cost estimation from the fast heuristic algorithm with respect to the exact model is carried out. The applicability of the method is illustrated through a large-scale real-world case study. Results shows that (i) the quality of the cable layout estimation is strongly dependent on the separation between WTs, where dense WT layouts present better performance parameters in terms of error, correlation, and computing time, and (ii) the proposed simultaneous design approach provides up to 6 % of improvement on the quality of fully feasible wind farm designs, and broadly, a statistically significant enhancement is ensured in spite of the stochasticity of the optimization algorithm.

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“…The cable layout problem maps to standard computer science problems categorized as NP-Hard (Pérez-Rúa and Cutululis, 2019), implying the lack of efficient methods (polynomial running time algorithms), greatly affecting the tractability for large-scale projects. Proposed methods to approach this problem can be categorized as: 1) Heuristics (Hou et al, 2016a;Pérez-Rúa et al, 2019a), 2) Metaheuristics (Hou et al, 2016b;Minguijón et al, 2019), and 3) Global optimization (Fischetti and Pisinger, 2018;Pérez-Rúa et al, 2019b), where mixed integer linear programming (MILP) is the most used formulation. A survey and analysis of these methods can be found in (Lumbreras and Ramos, 2013;Pérez-Rúa and Cutululis, 2019).…”

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confidence: 99%

A Framework for Simultaneous Design of Wind Turbines and Cable Layout in Offshore Wind

Pérez-Rúa

Cutululis

2021

Preprint

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Abstract. An optimization framework for simultaneous design of wind turbines (WTs) and cable layout for collection systemof offshore wind farms (OWFs) is presented in this paper. The typical approach used in both research and practical design is sequential, with an initial annual energy production (AEP) maximization, followed then by the collection system design. The sequential approach is robust and effective, however it fails to exploit the synergies between optimization blocks. Intuitively,one of the strongest trade-offs is between the WTs and cable layout, as they generally compete, i.e. spreading out WTs mitigates wake losses for larger AEP, but also results in longer submarine cables in the collection system and higher costs. The proposedo ptimization framework implements a gradient-free optimization algorithm to smartly move the WTs within the project area subject to minimum distance constraint, while a fast heuristic algorithm is called in every function evaluation in order to calculate a cost estimation of the cable layout. In a final stage, a refined cable layout design is obtained by iteratively solving amixed integer linear program (MILP), modelling all typical engineering constraints of this particular problem. A comprehensive performance analysis of the cost estimation from the fast heuristic algorithm with respect to the exact model is carried out.The applicability of the method is illustrated through a large-scale real-world case study. Results shows that: (i) the quality of the cable layout estimation is strongly dependent on the separation between WTs, where dense WTs layouts present better performance parameters in terms of error, correlation and computing time, and (ii) the proposed simultaneous design approach provides up to 6% of improvement on the quality of fully feasible wind farm designs, and broadly, a statistically significant enhancement is ensured in spite of the stochasticity of the optimization algorithm.

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Metaheuristic-based Design and optimization of Offshore Wind Farms Collection Systems

Cited by 3 publications

References 12 publications

GA based algorithms for offshore wind farm collector cable optimization

GA based algorithms for offshore wind farm collector cable optimization

A framework for simultaneous design of wind turbines and cable layout in offshore wind

A Framework for Simultaneous Design of Wind Turbines and Cable Layout in Offshore Wind

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