Risk Analysis and Utility Function-Based Decision-Making Model for Spinning Reserve Allocations

Spinning reserve (SR) is an essential resource for system operators to compensate for unpredictable imbalances between load and generation caused by sudden unit outages and unforeseen fluctuations of load demand and wind power. System operators could face many alternative SR allocations determined b...

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Bibliographic Details
Main Authors: Lun Ye, Jiangang Yao, Xu Ouyang, Xiangqian Zhu, Shengjie Yang
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9335689/
Description
Summary:Spinning reserve (SR) is an essential resource for system operators to compensate for unpredictable imbalances between load and generation caused by sudden unit outages and unforeseen fluctuations of load demand and wind power. System operators could face many alternative SR allocations determined by different methods and decide the optimal one based on the experience and consideration of risks in the power system. Considering the stochastic nature of power system components, this paper proposes a utility function-based decision-making model for SR allocations, which incorporates the whole distribution of social benefits (SBs) of the SR allocation and the risk preferences of decision-makers together. Three different utility functions are established that relate the SBs of SR allocations to risk-seeking, risk-neutral, and risk-averse preferences, respectively. Besides, the risk preference degree is represented by a shape parameter. The risk of different SR allocations is analyzed and the expected utilities, which reflect the relative satisfaction, are used to determine the optimal SR allocation for the operators with various risk preferences. Incorporating both the distribution of SBs and decision-makers' risk preferences makes the final decision for optimal SR allocation more flexible than the decision strategies based only on the expected social benefit or a probabilistic reliability index (such as loss of load probability and expected load not served). The effectiveness is examined using the IEEE-RTS.
ISSN:2169-3536