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Optimal Operation of Hydropower Reservoir Systems Using Weed Optimization Algorithm

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Abstract

The optimal hydropower operation of reservoir systems is known as a complex nonlinear nonconvex optimization problem. This paper presents the application of invasive weed optimization (IWO) algorithm, which is a novel evolutionary algorithm inspired from colonizing weeds, for optimal operation of hydropower reservoir systems. The IWO algorithm is used to optimally solve the hydropower operation problems for both cases of single reservoir and multi reservoir systems, over short, medium and long term operation periods, and the results are compared with the existing results obtained by the two most commonly used evolutionary algorithms, namely, particle swam optimization (PSO) and genetic algorithm (GA). The results show that the IWO is more efficient and effective than PSO and GA for both single reservoir and multi reservoir hydropower operation problems.

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Authors and Affiliations

  1. Water Management Research Lab, Department of Land, Air and Water Resources, University of California, Davis, CA, USA

    Mohammad Azizipour

  2. School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran

    Vahid Ghalenoei & M. H. Afshar

  3. Department of Land, Air, and Water Resources, University of California, Davis, CA, USA

    S. S. Solis

Authors
  1. Mohammad Azizipour
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  2. Vahid Ghalenoei
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  3. M. H. Afshar
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  4. S. S. Solis
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Correspondence to Mohammad Azizipour.

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Azizipour, M., Ghalenoei, V., Afshar, M.H. et al. Optimal Operation of Hydropower Reservoir Systems Using Weed Optimization Algorithm. Water Resour Manage 30, 3995–4009 (2016). https://doi.org/10.1007/s11269-016-1407-6

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  • DOI: https://doi.org/10.1007/s11269-016-1407-6

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