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Lifetime optimization framework for a hybrid renewable energy system based on receding horizon optimization

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  • Forough, Atefeh Behzadi
  • Roshandel, Ramin

Abstract

In this work, a novel convex sequence framework for real-time receding horizon operation optimization of a hybrid renewable energy system integrated with optimal sizing is presented to increase the penetration rate of renewable energy in supplying the demand. The proposed framework optimizes the entire lifetime cost of a system consisting of two main steps which are 1) design & installation and 2) operation as two sequence modules. This framework is applied to a hybrid renewable energy system which includes PV, wind turbine, batteries and a diesel generator. In the operation optimization, receding horizon strategy is used to optimize the operation schedule. Mixed integer convex programming method is applied in order to achieve the optimal operation. The hybrid renewable energy system is installed to actualize the design optimization outputs and to measure the required data for real-time operation optimization. The results show the proposed framework can be applied to facilitate the reliable real-time operation using real optimal input data for taking better advantage of the renewable energy resources. The effect of length of the horizon on optimal scheduling is also investigated. The results indicate that increasing of prediction horizon length enhances the economic performance and increases the share of renewable energy in the hybrid renewable energy system (from 68.5% to 81.4%).

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  • Forough, Atefeh Behzadi & Roshandel, Ramin, 2018. "Lifetime optimization framework for a hybrid renewable energy system based on receding horizon optimization," Energy, Elsevier, vol. 150(C), pages 617-630.
    • Handle: RePEc:eee:energy:v:150:y:2018:i:c:p:617-630
    DOI: 10.1016/j.energy.2018.02.158
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    Cited by:

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    3. Fethi Khlifi & Habib Cherif & Jamel Belhadj, 2021. "Environmental and Economic Optimization and Sizing of a Micro-Grid with Battery Storage for an Industrial Application," Energies, MDPI, vol. 14(18), pages 1-17, September.
    4. Xu, Xiao & Hu, Weihao & Cao, Di & Liu, Wen & Huang, Qi & Hu, Yanting & Chen, Zhe, 2021. "Enhanced design of an offgrid PV-battery-methanation hybrid energy system for power/gas supply," Renewable Energy, Elsevier, vol. 167(C), pages 440-456.
    5. Udeh, Godfrey T. & Michailos, Stavros & Ingham, Derek & Hughes, Kevin J. & Ma, Lin & Pourkashanian, Mohamed, 2022. "A modified rule-based energy management scheme for optimal operation of a hybrid PV-wind-Stirling engine integrated multi-carrier energy system," Applied Energy, Elsevier, vol. 312(C).

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