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Modeling an electric power microgrid by model predictive control for analyzing its characteristics from reliability, controllability and topological perspectives

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  • Fangyuan Han
  • Enrico Zio

Abstract

Microgrids can be a key solution for integrating renewable and distributed energy resources. This article analyzes microgrids’ characteristics adopting model predictive control. We study the microgrid performance under two operation modes: grid-connected and stand-alone. For each mode, we consider different faulty scenarios, and by dynamic simulations, we investigate the importance of the microgrid components from different perspectives: topological, reliability and controllability. This analysis enables evaluation of the microgrid performance and quantification of the importance of each component with respect to the different perspectives considered. The findings provide information for the design and operation of a microgrid, seeking the right balance of multiple characteristics.

Suggested Citation

  • Fangyuan Han & Enrico Zio, 2018. "Modeling an electric power microgrid by model predictive control for analyzing its characteristics from reliability, controllability and topological perspectives," Journal of Risk and Reliability, , vol. 232(2), pages 216-224, April.
    • Handle: RePEc:sae:risrel:v:232:y:2018:i:2:p:216-224
    DOI: 10.1177/1748006X17744382
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    1. J. M. Ottino, 2004. "Engineering complex systems," Nature, Nature, vol. 427(6973), pages 399-399, January.
    2. Weidlich, Anke & Veit, Daniel, 2008. "A critical survey of agent-based wholesale electricity market models," Energy Economics, Elsevier, vol. 30(4), pages 1728-1759, July.
    3. Prodan, Ionela & Zio, Enrico & Stoican, Florin, 2015. "Fault tolerant predictive control design for reliable microgrid energy management under uncertainties," Energy, Elsevier, vol. 91(C), pages 20-34.
    4. Zio, E. & Golea, L.R., 2012. "Analyzing the topological, electrical and reliability characteristics of a power transmission system for identifying its critical elements," Reliability Engineering and System Safety, Elsevier, vol. 101(C), pages 67-74.
    5. Yang-Yu Liu & Jean-Jacques Slotine & Albert-László Barabási, 2011. "Controllability of complex networks," Nature, Nature, vol. 473(7346), pages 167-173, May.
    6. Bakolas, Efstathios & Saleh, Joseph H., 2011. "Augmenting defense-in-depth with the concepts of observability and diagnosability from Control Theory and Discrete Event Systems," Reliability Engineering and System Safety, Elsevier, vol. 96(1), pages 184-193.
    7. Zio, Enrico, 2016. "Challenges in the vulnerability and risk analysis of critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 137-150.
    8. Li, Jian & Dueñas-Osorio, Leonardo & Chen, Changkun & Shi, Congling, 2016. "Connectivity reliability and topological controllability of infrastructure networks: A comparative assessment," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 24-33.
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