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Risk assessment and risk-cost optimization of distributed power generation systems considering extreme weather conditions

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  • Rocchetta, R.
  • Li, Y.F.
  • Zio, E.

Abstract

Security and reliability are major concerns for future power systems with distributed generation. A comprehensive evaluation of the risk associated with these systems must consider contingencies under normal environmental conditions and also extreme ones. Environmental conditions can strongly influence the operation and performance of distributed generation systems, not only due to the growing shares of renewable-energy generators installed but also for the environment-related contingencies that can damage or deeply degrade the components of the power grid. In this context, the main novelty of this paper is the development of probabilistic risk assessment and risk-cost optimization framework for distributed power generation systems, that take the effects of extreme weather conditions into account. A Monte Carlo non-sequential algorithm is used for generating both normal and severe weather. The probabilistic risk assessment is embedded within a risk-based, bi-objective optimization to find the optimal size of generators distributed on the power grid that minimize both risks and cost associated with severe weather. An application is shown on a case study adapted from the IEEE 13 nodes test system. By comparing the results considering normal environmental conditions and the results considering the effects of extreme weather, the relevance of the latter clearly emerges.

Suggested Citation

  • Rocchetta, R. & Li, Y.F. & Zio, E., 2015. "Risk assessment and risk-cost optimization of distributed power generation systems considering extreme weather conditions," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 47-61.
    • Handle: RePEc:eee:reensy:v:136:y:2015:i:c:p:47-61
    DOI: 10.1016/j.ress.2014.11.013
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    References listed on IDEAS

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    1. Johansson, Jonas & Hassel, Henrik & Zio, Enrico, 2013. "Reliability and vulnerability analyses of critical infrastructures: Comparing two approaches in the context of power systems," Reliability Engineering and System Safety, Elsevier, vol. 120(C), pages 27-38.
    2. Alarcon-Rodriguez, Arturo & Ault, Graham & Galloway, Stuart, 2010. "Multi-objective planning of distributed energy resources: A review of the state-of-the-art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(5), pages 1353-1366, June.
    3. Niknam, Taher & Taheri, Seyed Iman & Aghaei, Jamshid & Tabatabaei, Sajad & Nayeripour, Majid, 2011. "A modified honey bee mating optimization algorithm for multiobjective placement of renewable energy resources," Applied Energy, Elsevier, vol. 88(12), pages 4817-4830.
    4. Henneaux, Pierre & Labeau, Pierre-Etienne & Maun, Jean-Claude, 2012. "A level-1 probabilistic risk assessment to blackout hazard in transmission power systems," Reliability Engineering and System Safety, Elsevier, vol. 102(C), pages 41-52.
    5. Li, Yan-Fu & Zio, Enrico, 2012. "A multi-state model for the reliability assessment of a distributed generation system via universal generating function," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 28-36.
    6. Li, Yanfu & Zio, Enrico, 2012. "Uncertainty analysis of the adequacy assessment model of a distributed generation system," Renewable Energy, Elsevier, vol. 41(C), pages 235-244.
    7. Volkanovski, Andrija & ÄŒepin, Marko & Mavko, Borut, 2009. "Application of the fault tree analysis for assessment of power system reliability," Reliability Engineering and System Safety, Elsevier, vol. 94(6), pages 1116-1127.
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