Overall Optimization for Offshore Wind Farm Electrical System

Peng Hou; Weihao Hu; Cong Chen; Zhe Chen

doi:10.1002/we.2077

journal article Dec 05, 2016

Overall Optimization for Offshore Wind Farm Electrical System

Peng Hou

Weihao Hu

Cong Chen

Zhe Chen

Wind Energy Vol. 20 No. 6 pp. 1017-1032 · Wiley

View at Publisher Save 10.1002/we.2077

Abstract

AbstractBased on particle swarm optimization (PSO), an optimization platform for offshore wind farm electrical system (OWFES) is proposed in this paper, where the main components of an offshore wind farm and key technical constraints are considered as input parameters. The offshore wind farm electrical system is optimized in accordance with initial investment by considering three aspects: the number and siting of offshore substations (OS), the cable connection layout of both collection system (CS) and transmission system (TS) as well as the selection of electrical components in terms of voltage level and capacity. Because hundreds of optimization variables, continuous or discrete, are involved in the problem, a mix integer PSO (MIPSO) is required to obtain the solution. The fuzzy C‐means clustering (FCM) algorithm is used to partition the wind farm into several sub regions. The collection system layout in each sub region as well as the connection scheme between offshore substations are optimized by an adaptive PSO‐minimum spanning tree algorithm (APSO‐MST) which has been proposed in a previous work. The simulation results show that the proposed optimization platform can find an optimized layout that save 3.01% total cost compared with the industrial layout, and can be a useful tool for OWFES design and evaluation. Copyright © 2016 John Wiley & Sons, Ltd.

Topics

No keywords indexed for this article. Browse by subject →

References

40

[1]

Chen N (2011)

[2]

Lundberg S (2003)

[3]

ZhaoM ChenZ BlaabjergF.Application of genetic algorithm in electrical system optimization for offshore wind farms.Int. Conf. on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT) Nanjing China 2008.

[4]

Zhao M "Optimisation of electrical system for offshore wind farms via genetic algorithm" Renewable Power Generation, IET (2009)

[5]

Bahirat HJ "Comparison of wind farm topologies for offshore applications" IEEE Power and Energy Society General Meeting (2012)

[6]

10.1007/978-1-349-03521-2

[7]

Press WH

[8]

Devore RA "Some remarks on greedy algorithm" Advances in Computational Mathematics (1996)

[9]

Ling‐LingH NingC HongyueZ YangF.Optimization of large‐scale offshore wind farm electrical collection systems based on improved FCM.International Conference on Sustainable Power Generation and Supply (SUPERGEN 2012) Hangzhou:2012.

[10]

10.1109/tste.2012.2185817

[11]

10.1109/ptc.2013.6652477

[12]

10.1109/jsyst.2011.2163027

[13]

LinglingH YangF XiaomingG.Optimization of electrical connection scheme for large offshore wind farm with genetic algorithm.International Conference on Sustainable Power Generation and Supply 2009. SUPERGEN ‘09;2009;1–4. 10.1109/supergen.2009.5348207

[14]

LiDD HeC FuY.of large offshore wind farm with improved genetic algorithm.2008 IEEE Power and Energy Society General Meeting ‐ Conversion and Delivery of Electrical Energy in the 21st Century;2008;1–6. 10.1109/pes.2008.4596194

[15]

Dahmani O "Optimization of the internal grid of an offshore wind farm using Genetic algorithm" IEEE Grenoble PowerTech (POWERTECH) (2013)

[16]

10.1109/tpwrs.2013.2251014

[17]

10.1109/peci.2011.5740480

[18]

10.1109/tia.2013.2283219

[19]

10.1109/tpwrs.2012.2204906

[20]

HopewellPD Castro‐SayasF BaileyDI.Optimising the design of offshore wind farm collection networks.UPEC ‘06. Proceedings of the 4‐1st International Universities Power Engineering Conference;2006;1;84–88. 10.1109/upec.2006.367720

[21]

10.1109/tpwrs.2012.2204906

[22]

HouP HuW ChenZ.Offshore substation locating in wind farms based on prim algorithm. IEEE Power & Energy Society General Meeting;2015.

[23]

10.1049/iet-rpg.2015.0340

[24]

LundbergS.Performance comparison of wind park configurations Department of Electric Power Engineering Chalmers University of Technology Department of Electric Power Engineering Goteborg Sweden Tech.;2003.

[25]

XLPE submarine cable systems attachment to XLPE Land cable systems‐user's guide. ABB corporation.

[26]

KirkebyH MerzKO.Layout and electrical design of a 1.2 GW wind farm for research on the next generation of offshore wind energy technologies.Sintef Energy Research Trondheim;2014.

[27]

FCM: The fuzzy c-means clustering algorithm

James C. Bezdek, Robert Ehrlich, William Full

Computers & Geosciences 10.1016/0098-3004(84)90020-7

[28]

Particle swarm optimization

J. Kennedy, R. Eberhart

Proceedings of ICNN'95 - International Conference... 10.1109/icnn.1995.488968

[29]

Laskari EC "Particle swarm optimization for integer programming" IEEE Congress on Evolutionary Computation (2002)

[30]

GaingZL Constrained optimal power flow by mixed‐integer particle swarm optimization in Proc. IEEE Power Eng. Soc. General Meeting;2005;243–250.

[31]

ShiY EberhartRC.Empirical study of particle swarm optimization.CEC 99. Proceedings of the 1999 Congress on Evolutionary Computation;1999;3.

[32]

10.1016/j.chaos.2006.09.063

[33]

10.1109/cec.2001.934377

[34]

10.1109/tsmcb.2009.2015956

[35]

10.1016/j.ins.2012.05.020

[36]

BondyJA MurtyUSR Graph theory with applications the Macmilllan Press Ltd 1976. 10.1007/978-1-349-03521-2

[37]

MatsuiT KatoK SakawaM UnoT MatsumotoK.Particle swarm optimization for nonlinear integer programming problems.Proceedings of the International Multi Conference of Engineers and Computer Scientists 2008;2008;II.

[38]

ThomsenF Anholt offshore wind farm Dong Energy Available:www.anholtoffshorewindfarm.com.

[39]

New dimension. Available:www.siemens.com/wind.

[40]

10.1109/tste.2015.2429912

Cited By

39

Optimized design of collector topology for offshore wind farm based on ant colony optimization with multiple travelling salesman problem

Ramu SRIKAKULAPU, Vinatha U · 2018

Journal of Modern Power Systems and...

Metrics

39

Citations

40

References

Details

Published: Dec 05, 2016
Vol/Issue: 20(6)
Pages: 1017-1032
License: View

Authors

P

Peng Hou

Department of Energy Technology Aalborg University Aalborg Denmark

W

Weihao Hu

Department of Energy Technology Aalborg University Aalborg Denmark

C

Cong Chen

Department of Energy Technology Aalborg University Aalborg Denmark

Z

Zhe Chen

Department of Energy Technology Aalborg University Aalborg Denmark

Cite This Article

Peng Hou, Weihao Hu, Cong Chen, et al. (2016). Overall Optimization for Offshore Wind Farm Electrical System. Wind Energy, 20(6), 1017-1032. https://doi.org/10.1002/we.2077

Overall Optimization for Offshore Wind Farm Electrical System

You May Also Like