Yifeng Liu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Yifeng Liu has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Junjie Yang
School of Electric Information Engineering, Shanghai Dianji University, Shanghai, China
1 shared publication - Xin Liu
State Grid Shanghai Economic Research Institute, Shanghai 200120, China
1 shared publication - Yongsheng Cao
Shanghai Dianji University
1 shared publication
Latest Publications
- Open Access
- 14 July 2026
- Published by MDPI AG in Fractal and Fractional
- Vol. 10 (7) , 478
Fractional-Order Memory-Enhanced Transformer-CVaR Scheduling for Renewable Energy Systems Across Coupled Electricity and Carbon Markets
Renewable energy producers in coupled electricity and carbon markets face multi-dimensional uncertainties with cross-domain correlations. This paper proposes T-CMRS, an integrated forecasting optimization system for wind-solar-storage portfolios enhanced by fractional-order memory-aware uncertainty characterization. T-CMRS comprises (1) a transformer-based probabilistic forecasting engine capturing long-range temporal dependencies; (2) a fractional-order uncertainty modeling module employing Caputo derivatives to capture memory effects in price dynamics; and (3) a CVaR-based risk-averse optimization module reformulated as a linear program. Case studies on modified IEEE systems demonstrate that T-CMRS achieved 8.7% higher average daily profit than deterministic methods with 33.3% lower volatility, 15% VaR improvement over stochastic programming, and 12.3% scenario generation error reduction via fractional-order modeling. Scalability analysis confirms tractable computation for 500-bus systems, verifying applicability to large-scale deployments.
- 14 July 2026
- Published by MDPI AG in Fractal and Fractional
- Vol. 10 (7) , 478
Open AccessFractional-Order Memory-Enhanced Transformer-CVaR Scheduling for Renewable Energy Systems Across Coupled Electricity and Carbon Markets
Renewable energy producers in coupled electricity and carbon markets face multi-dimensional uncertainties with cross-domain correlations. This paper proposes T-CMRS, an integrated forecasting optimization system for wind-solar-storage portfolios enhanced by fractional-order memory-aware uncertainty characterization. T-CMRS comprises (1) a transformer-based probabilistic forecasting engine capturing long-range temporal dependencies; (2) a fractional-order uncertainty modeling module employing Caputo derivatives to capture memory effects in price dynamics; and (3) a CVaR-based risk-averse optimization module reformulated as a linear program. Case studies on modified IEEE systems demonstrate that T-CMRS achieved 8.7% higher average daily profit than deterministic methods with 33.3% lower volatility, 15% VaR improvement over stochastic programming, and 12.3% scenario generation error reduction via fractional-order modeling. Scalability analysis confirms tractable computation for 500-bus systems, verifying applicability to large-scale deployments.