Computational modeling demonstrates that coordinated urban virtual power plants reduce grid imbalance energy, highlighting internal flexibility benefits for smart energy communities.
Key Points
To develop a standardized non-parametric index and adaptive scheduling algorithm to evaluate how peer-to-peer flexibility in urban virtual power plants mitigates forecast errors before grid settlement.
Formulated the Community Imbalance Neutralisation Index (CINI) within a scalable matrix architecture alongside an adaptive day-ahead scheduling algorithm (Eforecast).
Evaluated the framework on an annual synthetic benchmark dataset consisting of 35,040 15-minute intervals representing a Central European residential cluster with solar photovoltaics, battery storage, and electric vehicle charging.
Active coordination decreased annual grid-facing imbalance energy from 188.73 MWh to 143.88 MWh, raising the annual CINI score from 57.22% to 67.39% (+10.17 percentage points).
Identified a 'Winter Flexibility Paradox' with maximum relative mitigation in December (+13.88 percentage points), while flexibility scaling to 40 kW yielded a CINI of 91.22% before reaching saturation.