Spatio-temporal evaluation of electricity price risk considering multiple uncertainties under extreme cold weather

Jianing Lin, Minglei Bao, Ziyang Liang, Maosheng Sang and Yi Ding

Applied Energy, 2022, vol. 328, issue C, No S0306261922013472

Abstract: The increasing frequency of long-lasting price spikes in electricity markets caused by extreme weather has brought unbearable economic burdens to both electricity consumers and retailers, attracting wide attention on price risk evaluation and prevention. However, the precise and comprehensive evaluation of price risks has been hindered by the lack of spatio-temporal feature analysis and multi-uncertainty fusion modeling, including random failures, rapid surges in electricity demands and natural gas prices under extreme cold weather. To address this, a spatio-temporal evaluation model of electricity price risk considering the synthetic effects of multiple uncertainties is proposed based on the universal generating function (UGF) technique. Firstly, the UGF representations of standardized probabilistic models for different uncertainty factors induced by freezing temperatures are developed. On this basis, the market price calculation (MPC) operator is proposed to obtain the probabilistic model of the electricity market by aggregating these UGFs. Moreover, the spatio-temporal price risk indices are proposed to comprehensively evaluate the market risk level. Furthermore, the impact analysis based on sensitivity calculation is introduced to identify the most critical factor from multiple uncertainties. Case studies demonstrate that the extremely high price risks mainly occur during severe icing intervals and locate in the region away from major energy resources. Moreover, the surge in electricity demand is identified as the major factor for extremely high electricity prices. The findings can provide effective references for risk prevention and hedging for market operators and participants.

Keywords: Electricity price risk; Electricity market; Multiple uncertainties; Universal generating function; Probabilistic model; Extreme cold weather (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (5)

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DOI: 10.1016/j.apenergy.2022.120090

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