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Hybrid Power Generation System Design Optimization Based on a Markovian Reliability Analysis Approach

[+] Author Affiliations
Shen Lu, Harrison M. Kim

University of Illinois at Urbana-Champaign, Urbana, IL

Paper No. DETC2011-48607, pp. 1201-1211; 11 pages
doi:10.1115/DETC2011-48607
From:
  • ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 5: 37th Design Automation Conference, Parts A and B
  • Washington, DC, USA, August 28–31, 2011
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5482-2
  • Copyright © 2011 by ASME

abstract

The optimal design of hybrid power generation systems (HPGS) can significantly improve the economic and technical performance of power supply. Due to the intermittent nature of renewable energy sources, as well as the application of energy storage techniques, the efficacy and efficiency of reliability assessment have become vital for successful HPGS design optimization. This paper proposes a sizing optimization method for HPGS based on a Markovian approach for long term reliability assessment. A multi-scenario formulation is considered to minimize the system cost while guaranteeing acceptable reliability across all the representative scenarios. The presented reliability analysis approach employs a Markov chain to model the state of charge of the energy storage based on probabilistic resource and load models. With this treatment, the loss of load probability of the HPGS can be tracked with relatively low computation, making it suitable for optimization applications. The effectiveness of the reliability analysis approach is tested through a comparison with Monte Carlo simulation; then the optimization approach is demonstrated with a numerical case study.

Copyright © 2011 by ASME

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