Version 1
: Received: 30 August 2024 / Approved: 30 August 2024 / Online: 2 September 2024 (11:13:42 CEST)
How to cite:
Shi, J.; Qin, J.; Li, H.; LI, Z.; GE, Y.; LIU, B. Probabilistic Power and Energy Balance Risk Scheduling Method Based on Distributed Robust Optimization. Preprints2024, 2024082269. https://doi.org/10.20944/preprints202408.2269.v1
Shi, J.; Qin, J.; Li, H.; LI, Z.; GE, Y.; LIU, B. Probabilistic Power and Energy Balance Risk Scheduling Method Based on Distributed Robust Optimization. Preprints 2024, 2024082269. https://doi.org/10.20944/preprints202408.2269.v1
Shi, J.; Qin, J.; Li, H.; LI, Z.; GE, Y.; LIU, B. Probabilistic Power and Energy Balance Risk Scheduling Method Based on Distributed Robust Optimization. Preprints2024, 2024082269. https://doi.org/10.20944/preprints202408.2269.v1
APA Style
Shi, J., Qin, J., Li, H., LI, Z., GE, Y., & LIU, B. (2024). Probabilistic Power and Energy Balance Risk Scheduling Method Based on Distributed Robust Optimization. Preprints. https://doi.org/10.20944/preprints202408.2269.v1
Chicago/Turabian Style
Shi, J., Yi GE and Boliang LIU. 2024 "Probabilistic Power and Energy Balance Risk Scheduling Method Based on Distributed Robust Optimization" Preprints. https://doi.org/10.20944/preprints202408.2269.v1
Abstract
The volatility and uncertainty associated with the high proportion of wind and PV output in the new power system significantly impact power and energy balance, making it challenging to accurately assess the risks related to renewable energy abandonment and supply guarante. Therefore, a probabilistic power and energy balance risk analysis method based on distributed robust optimization is proposed. Firstly, the affine factor and the flexible ramp reserve capacity of thermal power are combined to establish a probabilistic index, which serves to characterize the risk associated with power and energy balance. Drawing upon the principles of conditional value at risk theory, the risk indexes of load shedding power and curtailment power under a certain confidence probability are proposed. Secondly, the probability distribution fuzzy sets of uncertain variables are constructed using the distributionally robust method to measure the Wasserstein distance between different probability distributions. Finally, aiming at minimizing the operation cost of thermal power, the risk cost of power abandonment and the risk cost of load shedding, a distributed robust optimal scheduling model based on flexible ramp reserve of thermal power is established.
Keywords
electric power and energy balance; distributionally robust optimization; probabilistic index; affine factor; flexible climbing reserve
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.
