Research on Dynamic Risk Assessment Model and Fuzzy Comprehensive Evaluation of New Power Market Considering Carbon-Electricity Coupling Risks
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Abstract
Under the ongoing transition toward low-carbon energy systems, power markets are increasingly exposed to complex risks arising from the deep coupling between carbon policies and electricity market operations. As modern smart grids rely on wide-area sensing, electromagnetic information transmission, and intelligent communication infrastructures to support real-time market coordination, accurate dynamic risk assessment has become essential for maintaining secure and resilient system operation. This study proposes a novel assessment framework integrating dynamic risk identification with fuzzy comprehensive evaluation to quantify carbon-electricity coupling risks. By introducing a time-varying risk conduction coefficient matrix together with an improved entropy weight-sequence relationship combined weighting method, the proposed framework effectively characterizes dynamic risk evolution while balancing objective data and expert knowledge. A dynamic sliding window mechanism captures temporal variations in risk propagation, and triangular fuzzy numbers are employed to address uncertainty in indicator information. Validation using operational data from seven electricity spot pilot markets in China during 2019–2022 demonstrates that the conduction effect of carbon quota price fluctuations on day-ahead settlement risks increases by an average of 37.8% in regions with high renewable energy penetration. Under extreme weather conditions, East China exhibits a 28.6% probability of simultaneous carbon-cost escalation and power supply shortage risks. Compared with conventional assessment methods, the proposed model extends early warning lead time by 2.3 working days and improves warning accuracy by 11.5 percentage points. The proposed framework provides effective decision support for power market participants while offering a scalable methodology for intelligent risk monitoring and coordinated energy management over smart grid communication and electromagnetic information transmission infrastructures.
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