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DOE OSTI · 1855974

Thermal Overloading Risk Mitigation With a Semi-Analytical Probabilistic Model on Branch Current

Hong, Tianqi·Zhao, Dongbo·Zhang, Yichen·Yao, Rui·Qiu, Feng
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Abstract

A semi-analytical formulation is presented in this paper for the probability computation of branch current in multiphase systems. The developed formula is derived based on the linear power flow model in rectangular coordinates. The system uncertainty injections can be renewable energy resources or loads and are modeled using a Gaussian mixture model (GMM). The developed formula can be used to compute the line current violation probability as well as integrate into optimal power flow problem as chance-constraint relaxation. Here, the proposed formula is first compared with the Matlab embedded numerical integration function to show its performance. Besides, the semi-analytical formula is validated and compared with the Monte Carlo simulation method using the IEEE 123-bus system, EPRI Ckt5, and Ckt7 systems.

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24 POWER TRANSMISSION AND DISTRIBUTIONline current probabilitylinear power flowoverloadingprobabilistic power flowwildfire risk mitigation

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Hong, Tianqi, Zhao, Dongbo, Zhang, Yichen, Yao, Rui, Qiu, Feng. 2020-12-31. Thermal Overloading Risk Mitigation With a Semi-Analytical Probabilistic Model on Branch Current. https://doi.org/10.1109/tpwrs.2020.3048302

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