Skip to main content
SpringerLink
Log in

Positioning of Wind Turbine in a Wind Farm for Optimum Generation of Power Using Genetic Algorithm for Multiple Direction

  • Conference paper
  • First Online:
Intelligent Manufacturing and Energy Sustainability

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 213))

  • 1024 Accesses

Abstract

The objective of wind farm layout optimization (WFLO) is to maximize the power generation with less cost. This paper proposes a program based on genetic algorithm for positioning turbines in a wind farm and studies the effect of wind direction on WFLO. Wind speed is measured at 28 locations in two southern states in India. GIS approach is used to identify the ideal location for a wind farm. Two different scenarios are taken for study; the first is constant wind speed with single direction and the second is constant wind speed with multiple wind directions. A wind farm of 2 km × 2 km is divided into grids of 10 × 10; each grid can have one or no turbine. The wind data of the past three years is taken for the optimization problem. The best solution would accommodate 19 turbines which can generate an average power of 183.55 MW with maximum 343.15 MW in November and a minimum 29.8 MW in May. A case study of wind farm layout optimization along with economical aspect is done in India.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. K. Anwar, S. Deshmukh, S. Mustafa Rizvi, Feasibility and sensitivity analysis of a hybrid photovoltaic/wind/biogas/fuel-cell/diesel/battery system for off-grid rural electrification using homer. J. Energy Resour. Technol. 142(6), 1–12 (2020)

    Article  Google Scholar 

  2. G. Bekele, G. Tadesse, Feasibility study of small hydro/PV/wind hybrid system for off-grid rural electrification in Ethiopia. Appl. Energy 97, 5–15 (2012)

    Article  Google Scholar 

  3. K. Anwar, S. Deshmukh, Parametric study for the prediction of wind energy potential over the southern part of India using neural network and geographic information system approach. Proc. Inst. Mech. Eng. Part A J. Power Energy 234(1), 96–109 (2020)

    Article  Google Scholar 

  4. M. Abbes, M. Allagui, Centralized control strategy for energy maximization of large array wind turbines. Sustain. Cities Soc. 25, 82–89 (2016)

    Article  Google Scholar 

  5. S.D.O. Turner, D.A. Romero, P.Y. Zhang, C.H. Amon, T.C.Y. Chan, A new mathematical programming approach to optimize wind farm layouts. Renew. Energy 63, 674–680 (2014)

    Article  Google Scholar 

  6. F.G. Montoya, F. Manzano-Agugliaro, S. López-Márquez, Q. Hernández-Escobedo, C. Gil, Wind turbine selection for wind farm layout using multi-objective evolutionary algorithms. Expert Syst. Appl. 41(15), 6585–6595 (2014)

    Article  Google Scholar 

  7. X. Gao, H. Yang, L. Lin, P. Koo, Wind turbine layout optimization using multi-population genetic algorithm and a case study in Hong Kong offshore. J. Wind Eng. Ind. Aerodyn. 139, 89–99 (2015)

    Article  Google Scholar 

  8. L. Parada, C. Herrera, P. Flores, V. Parada, Wind farm layout optimization using a Gaussian-based wake model. Renew. Energy 107, 531–541 (2017)

    Article  Google Scholar 

  9. J.S. González, A.G. Gonzalez Rodriguez, J.C. Mora, J.R. Santos, M.B. Payan, Optimization of wind farm turbines layout using an evolutive algorithm. Renew. Energy 35(8), 1671–1681 (2010)

    Article  Google Scholar 

  10. I. Katic, J. Højstrup, N.O. Jensen, A simple model for cluster efficiency, in EWEC’86. Proceedings, vol. 1 (1987), pp. 407–410

    Google Scholar 

  11. N.O. Jensen, A note on wind generator interaction. Report 87-550-0971-9 (1983)

    Google Scholar 

  12. J.F. Herbert-Acero, O. Probst, P.-E. Réthoré, G.C. Larsen, K.K. Castillo-Villar, A review of methodological approaches for the design and optimization of wind farms. Energies 7(11), 6930–7016 (2014)

    Article  Google Scholar 

  13. H.S. Huang, Distributed genetic algorithm for optimization of wind farm annual profits, in 2007 International Conference on Intelligent Systems Applications to Power Systems, Nov 2007, pp. 1–6

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, BITS Pilani—Hyderabad Campus, Hyderabad, Telangana, 500078, India

    Khalid Anwar & Sandip Deshmukh

Authors
  1. Khalid Anwar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sandip Deshmukh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Khalid Anwar .

Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, Malla Reddy College Engineering and Technology, Secunderabad, Telangana, India

    A.N.R. Reddy

  2. Department of Mechanical Engineering, Indian Institute of Technology Bombay, Mumbai, India

    Deepak Marla

  3. Department of Informatics and Computer Techniques, Siberian State University of Science and Technology, Krasnoyarsk, Russia

    Margarita N. Favorskaya

  4. School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India

    Suresh Chandra Satapathy

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Anwar, K., Deshmukh, S. (2021). Positioning of Wind Turbine in a Wind Farm for Optimum Generation of Power Using Genetic Algorithm for Multiple Direction. In: Reddy, A., Marla, D., Favorskaya, M.N., Satapathy, S.C. (eds) Intelligent Manufacturing and Energy Sustainability. Smart Innovation, Systems and Technologies, vol 213. Springer, Singapore. https://doi.org/10.1007/978-981-33-4443-3_74

Download citation

  • DOI: https://doi.org/10.1007/978-981-33-4443-3_74

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-33-4442-6

  • Online ISBN: 978-981-33-4443-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation