Zhou, G.; Shi, J.; Chen, B.; Qi, Z.; Wang, L. Risk Assessment of Power Supply Security Considering Optimal Load Shedding in Extreme Precipitation Scenarios. Energies2023, 16, 6660.
Zhou, G.; Shi, J.; Chen, B.; Qi, Z.; Wang, L. Risk Assessment of Power Supply Security Considering Optimal Load Shedding in Extreme Precipitation Scenarios. Energies 2023, 16, 6660.
Zhou, G.; Shi, J.; Chen, B.; Qi, Z.; Wang, L. Risk Assessment of Power Supply Security Considering Optimal Load Shedding in Extreme Precipitation Scenarios. Energies2023, 16, 6660.
Zhou, G.; Shi, J.; Chen, B.; Qi, Z.; Wang, L. Risk Assessment of Power Supply Security Considering Optimal Load Shedding in Extreme Precipitation Scenarios. Energies 2023, 16, 6660.
Abstract
To quantitatively estimate the risk of power system operation under extreme rainfall, a multi-scenario stochastic risk assessment method is proposed. First, a scenario generation scheme considering waterlogged faults of power facilities is constructed based on the storm water management model (SWMM) and the extreme learning machine method. These scenarios will be merged to several typical scenario sets for further processing. The outage of power facilities will induce power flow transfer which may consequently lead to transmission lines’ thermal limit violation. Semi-invariant and Gram-Charlier level expansion methods are adopted to analytically depict the probability density function and cumulative probability function of each line’s power flow. The optimal solution is performed by a particle swarm algorithm to obtain proper load curtailment at each bus, and consequently the violation probability of line thermal violations can be controlled within an allowable range. The volume of load curtailment as well as their importance are considered to quantitatively access the risk of power supply security under extreme precipitation scenarios. The effectiveness of the proposed method is verified in case studies based on the IEEE 24-bus system.
Keywords
Extreme precipitation; load curtailment; power supply security; risk assessment; stochastic power flow
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
