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

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

doi:10.1109/PTC.2019.8810583

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

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

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

An optimization framework for automated design of offshore wind farms collection systems is proposed in this paper. The core of the framework consists of a metaheuristic algorithm, namely a Genetic Algorithm (GA). The GA is designed for searching high-quality feasible solutions in terms of the capital expenditure (CAPEXcs); a subsequent step runs a power flow in order to calculate electrical power losses for estimating the collection systems share on the Levelized Cost of Energy (LCOEcs). Finally, after several executions of the full framework, the feasible solution bringing the cheapest LCOEcs is selected. The main inputs are the coordinate’s location of the wind turbines and the offshore substation (OSS), wind power production time series, and the set of considered cables for the collection system design. The proposed approach offers a full search space exploration for feasible solutions, while taking into account cables capacities and disallowing for cable crossings. The results show that this framework can find feasible solutions improving benchmark methods by 8%.

Original language	English
Title of host publication	Proceedings of the 13th IEEE PowerTech Milano 2019: Leading innovation for energy transition
Number of pages	6
Publisher	IEEE
Publication date	2019
ISBN (Print)	978-1-5386-4723-3
ISBN (Electronic)	978-1-5386-4722-6
DOIs	https://doi.org/10.1109/PTC.2019.8810583
Publication status	Published - 2019
Event	13^th IEEE PowerTech Milano 2019: Leading innovation for energy transition - Bovisa Campus of Politecnico di Milano, Milano, Italy Duration: 23 Jun 2019 → 27 Jun 2019 Conference number: 13 http://ieee-powertech.org/

Conference

Conference	13^th IEEE PowerTech Milano 2019
Number	13
Location	Bovisa Campus of Politecnico di Milano
Country/Territory	Italy
City	Milano
Period	23/06/2019 → 27/06/2019
Other	PowerTech is the anchor conference of the IEEE Power & Energy Society (PES) in Europe
Internet address	http://ieee-powertech.org/

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title = "Metaheuristic-based Design and Optimization of Offshore Wind Farms Collection Systems",

abstract = "An optimization framework for automated design of offshore wind farms collection systems is proposed in this paper. The core of the framework consists of a metaheuristic algorithm, namely a Genetic Algorithm (GA). The GA is designed for searching high-quality feasible solutions in terms of the capital expenditure (CAPEXcs); a subsequent step runs a power flow in order to calculate electrical power losses for estimating the collection systems share on the Levelized Cost of Energy (LCOEcs). Finally, after several executions of the full framework, the feasible solution bringing the cheapest LCOEcs is selected. The main inputs are the coordinate{\textquoteright}s location of the wind turbines and the offshore substation (OSS), wind power production time series, and the set of considered cables for the collection system design. The proposed approach offers a full search space exploration for feasible solutions, while taking into account cables capacities and disallowing for cable crossings. The results show that this framework can find feasible solutions improving benchmark methods by 8%.",

author = "{Hermosilla Minguijon}, Daniel and Juan-Andr{\'e}s P{\'e}rez-R{\'u}a and Kaushik Das and Cutululis, {Nicolaos Antonio}",

year = "2019",

doi = "10.1109/PTC.2019.8810583",

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booktitle = "Proceedings of the 13th IEEE PowerTech Milano 2019: Leading innovation for energy transition",

publisher = "IEEE",

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Metaheuristic-based Design and Optimization of Offshore Wind Farms Collection Systems. / Hermosilla Minguijon, Daniel; Pérez-Rúa, Juan-Andrés ; Das, Kaushik et al.

Proceedings of the 13th IEEE PowerTech Milano 2019: Leading innovation for energy transition. IEEE, 2019.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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T1 - Metaheuristic-based Design and Optimization of Offshore Wind Farms Collection Systems

AU - Hermosilla Minguijon, Daniel

AU - Pérez-Rúa, Juan-Andrés

AU - Das, Kaushik

AU - Cutululis, Nicolaos Antonio

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AB - An optimization framework for automated design of offshore wind farms collection systems is proposed in this paper. The core of the framework consists of a metaheuristic algorithm, namely a Genetic Algorithm (GA). The GA is designed for searching high-quality feasible solutions in terms of the capital expenditure (CAPEXcs); a subsequent step runs a power flow in order to calculate electrical power losses for estimating the collection systems share on the Levelized Cost of Energy (LCOEcs). Finally, after several executions of the full framework, the feasible solution bringing the cheapest LCOEcs is selected. The main inputs are the coordinate’s location of the wind turbines and the offshore substation (OSS), wind power production time series, and the set of considered cables for the collection system design. The proposed approach offers a full search space exploration for feasible solutions, while taking into account cables capacities and disallowing for cable crossings. The results show that this framework can find feasible solutions improving benchmark methods by 8%.

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ER -

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

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