Journal of Modern Power Systems and Clean Energy

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Home > Archive>Volume 9, Issue 2, 2021 >356-366. DOI:10.35833/MPCE.2019.000150
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Mesoscale Wind Farm Placement via Linear Optimization Constrained by Power System and Techno-economics
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Affiliation:

1.Electrical Engineering Department, Hakkari University, Hakkari, 30000 Turkey;2.Department of Engineering Sciences, Department of Electrical Engineering, Computational and Data-enabled Science and Engineering in Energy Systems, Uppsala University, 751 21 Uppsala, Sweden;3.Department of Mathematics, Florida State University, Tallahassee, FL 32310, USA;4.Electrical Engineering Department, Yildiz Technical University, Istanbul, 34220 Turkey

Fund Project:

This work was supported by TUBITAK Scholarship (No. B.14.2.TBT.0.06.01-214-6041) and Yildiz Technical University Scientific Project Coordination Fund (No. 2012-04-02-DOP04).

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    Abstract:

    The objective of this study is to develop a wind farm placement and investment methodology based on a linear optimization procedure. This problem has a major significance for the investment success for the projects of renewable energy such as wind power. In this study, a mesoscale approach is adopted whereby the wind farm location is investigated in comparison with a microscale approach where the location of each individual turbine is optimized. Specifical study focuses on the placement of a wind farm by economical optimization constrained by the power system, wind resources, and techno-economics. Linear optimization is introduced in this context at the power system which is constrained by wind farm planning.

    表 2 Table 2
    表 6 Table 6
    表 4 Table 4
    图1 Flow chart of methodology.Fig.1
    图2 Flow diagram of economic placement algorithm.Fig.2
    图3 Single-line diagram of the 7-bus system connected to the first transmission line.Fig.3
    图5 Convergence of algorithm optimization.Fig.5
    图6 Representation of busbar-based power plant locations on the map.Fig.6
    表 1 Table 1
    表 8 Table 8
    表 3 Table 3
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History
  • Received:December 02,2019
  • Online: March 22,2021

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