Open AccessSequential heuristic optimisation of a real offshore wind farm site considering turbine placement and cable layout
Author(s) -
Peter Taylor,
David CamposGaona,
Hong Yue,
Olimpo AnayaLara,
Chen Jia,
C Ng
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1669/1/012024
Subject(s) - offshore wind power , turbine , revenue , integer programming , wind power , heuristic , computer science , work (physics) , process (computing) , cost of electricity by source , marine engineering , reliability engineering , power (physics) , engineering , electricity generation , electrical engineering , business , mechanical engineering , accounting , algorithm , artificial intelligence , operating system , physics , quantum mechanics
Competition within the energy generation industry provides an incentive for developers to build offshore wind farms with a low levelised cost of energy. Therefore, there is a need for design optimisation to reduce costs and increase energy capture. A sequential approach to optimise turbine placement and cable layout is presented, using a heuristic k-opt algorithm and mixed-integer linear programming respectively. Energy storage is considered as a means to further improve the cable selection process. A case study is carried out on the Lillgrund offshore wind farm and the resulting layout improves energy capture by 6%. Cable costs are increased but the electrical losses are reduced such that there is an overall saving over the project lifetime of 20%. Energy storage as a means to peak shave the power seen by a cable in order to reduce electrical losses or de-rate a cable section was found to be impractically large and not profitable. Future work will consider secondary revenue streams to remedy this.