Regime-Conditioned Reserve Calibration and Hydrogen Flexibility for Virtual Power Plant Scheduling

High-renewable virtual power plants (VPPs) exhibit asymmetric operational risks stemming from net-load forecast errors: positive errors require upward reserve capacity, while negative errors can cause grid export saturation and renewable curtailment. This paper proposes RC-CVaR-H2, a linear rolling-horizon framework combining regime-conditioned day-block conformal reserve floors, empirical conditional value-at-risk (CVaR), carried resource states and flexible electrolysis. A nested matched comparison separates reserve calibration from surplus absorption under common inputs. The framework is evaluated on a two-year Inner Mongolia synthetic benchmark with 2016 out-of-sample hourly tests. Relative to empirical CVaR, regime-conformal CVaR raises dispatch-reserve coverage from 88.99% to 92.71% and reduces upward shortfall by 60.66%. Relative to pooled conformal CVaR, regime conditioning reduces shortfall by 38.27% with 3.1% more mean reserve. The paired daily reduction is 1.838 MWh, with a 95% interval from 0.940 to 2.777 MWh. At the fixed 35 MW export cap, hydrogen flexibility lowers curtailment from 233.40 to 71.43 MWh, or 69.40%, with unchanged headroom-based reliability metrics. Both effects retain their direction across five generated realizations. The full method costs 9.40% less than deterministic day-ahead scheduling, mainly through rolling updates, and each 4 h update takes 5.52 ms. These results quantify complementary calibration and absorption effects within the disclosed synthetic forecasts, fixed parameters and aggregate resource model.

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Publication Details

Journal
Energies
Published
2026-09-25
DOI
https://doi.org/10.3390/en19194554
Primary Topic
Smart Grid Energy Management
Type
article
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article

Regime-Conditioned Reserve Calibration and Hydrogen Flexibility for Virtual Power Plant Scheduling

Yu Song, Mingyue Jiang, Leilei Wang, Na Li et al.
Energies
Smart Grid Energy Management
article

Regime-Conditioned Reserve Calibration and Hydrogen Flexibility for Virtual Power Plant Scheduling

Yu Song, Mingyue Jiang, Leilei Wang, Na Li, Wei Cheng
article en

Abstract

High-renewable virtual power plants (VPPs) exhibit asymmetric operational risks stemming from net-load forecast errors: positive errors require upward reserve capacity, while negative errors can cause grid export saturation and renewable curtailment. This paper proposes RC-CVaR-H2, a linear rolling-horizon framework combining regime-conditioned day-block conformal reserve floors, empirical conditional value-at-risk (CVaR), carried resource states and flexible electrolysis. A nested matched comparison separates reserve calibration from surplus absorption under common inputs. The framework is evaluated on a two-year Inner Mongolia synthetic benchmark with 2016 out-of-sample hourly tests. Relative to empirical CVaR, regime-conformal CVaR raises dispatch-reserve coverage from 88.99% to 92.71% and reduces upward shortfall by 60.66%. Relative to pooled conformal CVaR, regime conditioning reduces shortfall by 38.27% with 3.1% more mean reserve. The paired daily reduction is 1.838 MWh, with a 95% interval from 0.940 to 2.777 MWh. At the fixed 35 MW export cap, hydrogen flexibility lowers curtailment from 233.40 to 71.43 MWh, or 69.40%, with unchanged headroom-based reliability metrics. Both effects retain their direction across five generated realizations. The full method costs 9.40% less than deterministic day-ahead scheduling, mainly through rolling updates, and each 4 h update takes 5.52 ms. These results quantify complementary calibration and absorption effects within the disclosed synthetic forecasts, fixed parameters and aggregate resource model.

EnergiesVol. 19(19)
Tianjin University of Technology (CN), Inner Mongolia Electric Power (China) (CN), China General Nuclear Power Corporation (China) (CN), PowerChina (China) (CN)
Openalex Percentile: Top 21%
Smart Grid Energy Management
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