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Measuring and managing the risk of extensive distribution network outages during extreme events is critical for ensuring system-level energy balance in transmission network operations. However, existing risk measures used in stochastic optimization of power systems are computationally intractable for this problem involving large numbers of discrete random variables. Using a new coherent risk measure, Entropic Value-at-Risk (EVaR), that requires significantly less computational complexity, we propose an EVaR-constrained optimal power flow model that can quantify and manage the outage risk of extensive distribution feeders. The optimization problem with EVaR constraints on discrete random variables is equivalently reformulated as a conic programming model, which allows the problem to leverage the computational efficiency of conic solvers. The superiority of the proposed model is validated on the real-world Puerto Rico transmission grid combined with its large-scale distribution networks.
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Characteristics and Risk of Microgrid Outages from a Complex Systems Point of View
Cordova is a town of approximately 2,000 people located on the southern coast of Alaska. A power grid for a town this size, with a large seasonal fishing economy, is considered a moderate to large sized microgrid in terms of power produced. Understanding the vulnerabilities and risks of failures in such a grid is important for planning and operations. Investigating these characteristics in the context of complex system dynamics is a novel approach. The analysis of Cordova’s microgrid is a case study relevant to a large class of microgrid communities. We analyze the outage data based on size, cause characteristics, and load demand on the system and find long time correlations and power laws in the failure size distributions. Finally we apply a risk metric to give a single numerical value to the risk of an outage occurring during certain time periods and under certain conditions.
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- Award ID(s):
- 1735354
- PAR ID:
- 10310726
- Date Published:
- Journal Name:
- Proceedings of the Hawaii International Conference on System Sciences
- ISSN:
- 0073-1129
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.24251/HICSS.2021.406
