TY - JOUR
T1 - Co-optimisation of wind farm micro-siting and cabling layouts
AU - Al Shereiqi, A.
AU - Mohandes, B.
AU - Al-Hinai, A.
AU - Bakhtvar, M.
AU - Al-Abri, R.
AU - El Moursi, M. S.
AU - Albadi, M.
N1 - Funding Information:
The authors would like to acknowledge the support of the Sultan Qaboos University, Oman Rural Areas Electricity Company, and HMTF project code (SR/ENG/ECE/17/01).
Publisher Copyright:
© 2021 The Authors. IET Renewable Power Generation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology
PY - 2021/3/22
Y1 - 2021/3/22
N2 - Wind farm layout optimisation (WFLO) is carried out in this study considering the wake effect, and cabling connections and losses. The wind farm micro-siting optimisation problem is formulated with the aid of Jensen's wake model. Cabling between the wind turbines and the point of common coupling is an important aspect of the wind farm design as it affects the capital investment as well as income over the lifetime of the wind farm. The cabling layout must satisfy the connection of the wind turbines to the point of common coupling in such a way that the total cable length is reduced while reliability is maintained. Introducing the cabling layout optimisation to the WFLO, further complicates the optimisation problem. An integrated tool is developed to optimise the wind farm layout and cabling simultaneously. The main contribution of this work is the development of an integrated tool that maximizes the energy production of the wind farm via optimal allocation of wind turbines with optimal cable routing. This tool considers the capital cost of wind turbines and cabling, wind farm power production, and power losses in the cabling over the lifetime of the wind farm. The proposed co-optimisation problem is solved using genetic algorithm. The decision variables are the wind farm layout, cable paths and sizes, and the location of the point of common coupling within the land perimeter. A case study incorporating a multi-speed and multi-direction wind profile is carried out to demonstrate the applicability of the proposed approach. Moreover, the proposed methodology is compared to the separate optimisation method where the WFLO and cabling optimisation are solved sequentially with two separate steps. It is shown that the co-optimisation method is superior in terms of cable power losses, overall wind farm cost, and compactness (land use).
AB - Wind farm layout optimisation (WFLO) is carried out in this study considering the wake effect, and cabling connections and losses. The wind farm micro-siting optimisation problem is formulated with the aid of Jensen's wake model. Cabling between the wind turbines and the point of common coupling is an important aspect of the wind farm design as it affects the capital investment as well as income over the lifetime of the wind farm. The cabling layout must satisfy the connection of the wind turbines to the point of common coupling in such a way that the total cable length is reduced while reliability is maintained. Introducing the cabling layout optimisation to the WFLO, further complicates the optimisation problem. An integrated tool is developed to optimise the wind farm layout and cabling simultaneously. The main contribution of this work is the development of an integrated tool that maximizes the energy production of the wind farm via optimal allocation of wind turbines with optimal cable routing. This tool considers the capital cost of wind turbines and cabling, wind farm power production, and power losses in the cabling over the lifetime of the wind farm. The proposed co-optimisation problem is solved using genetic algorithm. The decision variables are the wind farm layout, cable paths and sizes, and the location of the point of common coupling within the land perimeter. A case study incorporating a multi-speed and multi-direction wind profile is carried out to demonstrate the applicability of the proposed approach. Moreover, the proposed methodology is compared to the separate optimisation method where the WFLO and cabling optimisation are solved sequentially with two separate steps. It is shown that the co-optimisation method is superior in terms of cable power losses, overall wind farm cost, and compactness (land use).
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U2 - 10.1049/rpg2.12154
DO - 10.1049/rpg2.12154
M3 - Article
AN - SCOPUS:85102827118
SN - 1752-1416
VL - 15
SP - 1848
EP - 1860
JO - IET Renewable Power Generation
JF - IET Renewable Power Generation
IS - 8
ER -