Battery Health-Aware Dynamic Flexibility Management for Hybrid AC/DC Distribution Networks (code and data)

Research Release — v1.0.2

This release provides the research code, numerical datasets, and figures accompanying the study "Battery Health-Aware Dynamic Flexibility Management for Hybrid AC/DC Distribution Networks."

What changed in v1.0.2

This is a manuscript-title and documentation alignment update for submission to the Journal of Energy Storage. The repository title, citation metadata (CITATION.cff, version 1.0.2), and citation instructions now use the revised study title, and the Zenodo concept DOI is listed in the README. No source code, datasets, figures, model parameters, or numerical results have changed with respect to v1.0.1.

About the framework

The battery health-aware Dynamic Flexibility Management (DFM) framework computes, at every supervisory interval, a time-varying charge/discharge flexibility envelope that integrates energy availability, state of health, a daily degradation allowance, directional probabilistic uncertainty reserves, and AC/DC network deliverability. The envelope is imposed as an operating constraint of a rolling-horizon mixed-integer linear programming (MILP) energy management system.

The implementation is evaluated on the hybrid CIGRE low-voltage benchmark (Topology-3), extended with battery energy storage, photovoltaic generation, and wind power.

Release Contents

• Python implementation of the DFM framework and energy management system.
• Simulation configurations and numerical datasets.
• Conventional and degradation-aware benchmark strategies.
• Ablation, sensitivity, and Monte Carlo analyses.
• Research figures and supporting visualization materials.
• Documentation and instructions for reproducibility.

Across 100 Monte Carlo realizations, DFM reduces renewable curtailment by 87.9%, battery health consumption by 29.7%, and energy cost by 2.3% relative to the degradation-aware benchmark, while reducing the incidence of network-constraint violations from 70% to 33%.

Archive

Zenodo concept DOI (all versions): https://doi.org/10.5281/zenodo.24088866 Previous version v1.0.1: https://doi.org/10.5281/zenodo.24106846