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D-SCEOS v1.0.0 — Published article reproducibility release

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@kovariati kovariati released this 21 Aug 12:43
v1.0.0
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This is the canonical D-SCEOS v1.0.0 code and reproducibility release associated with the peer-reviewed journal article:

Preferred citation

Kovari, A. (2026). Swarm-inspired peer-to-peer control for resource-aware flexibility sharing in cyber–physical energy systems. Energy Conversion and Management: X, 31, 102212. https://doi.org/10.1016/j.ecmx.2026.102212

Available online: 18 August 2026
Issue date: September 2026
Publisher: Elsevier
ISSN: 2590-1745
Article number: 102212
DOI: https://doi.org/10.1016/j.ecmx.2026.102212
ScienceDirect: https://www.sciencedirect.com/science/article/pii/S2590174526006951

The journal article is published open access under CC BY 4.0. Repository source code is licensed separately under MIT.

If D-SCEOS, its implementation, experimental protocol, comparator suite, numerical results, or released reproducibility artefacts are used or discussed in scientific work, please cite the journal article above.

About D-SCEOS

D-SCEOS is a swarm-inspired, gateway-injected peer-to-peer control framework for resource-aware flexibility sharing in cyber–physical energy systems. The released implementation covers distributed energy resources and virtual-power-plant scenarios, graph-local coordination, dynamic aggregate and target estimation, capacity-normalized utilization sharing, and local CLF/HOCBF-QCQP operating-envelope handling.

The associated study evaluates distributed control, peer-to-peer flexibility sharing, dynamic average consensus, control Lyapunov functions, high-order control barrier functions, safe control, distributed optimization, multi-agent coordination, energy storage, and virtual-power-plant flexibility.

Included in v1.0.0

  • D-SCEOS controller and local CLF/HOCBF-QCQP implementation
  • design-matched DPG-HOCBF, DPD-HOCBF, and PD comparator code
  • technology-representative VPP scenarios and seven-regime stress ladder
  • equal-effort comparator protocol
  • paired Monte Carlo and robust-inference workflows
  • component ablation and parameter/sampling-time sensitivity analyses
  • communication-overlay, gateway, and agent-loss diagnostics
  • centralized-reference KKT/allocation checks
  • independent conic-solver cross-checks
  • fail-closed validation and 33 regression/source-integrity tests
  • machine-readable citation and article metadata
  • AI-readable project and citation information

Published numerical artefacts

The complete generated numerical artefact set associated with the published validation is provided separately from the Git source history:

SHA-256 of the numerical archive:

4fb221a6ce9e59153119dd1efde4108d8ac43e53cc0978110b3cda7aee5ec9f5

The archive contains full trajectories and per-step metrics for the 18 primary N=15/N=60 scenario-controller runs, seed-level Monte Carlo outputs, equal-effort comparator results, sensitivity and component-ablation studies, topology and communication diagnostics, solver cross-checks, scalability results, a machine-readable manifest, and per-file SHA-256 checksums.

Large generated trajectories are intentionally not duplicated in Git history. The source code, experiment definitions, tests, and rerun workflows are provided by the v1.0.0 Git tag.

Reproduce

python -m pytest -q
python run_all.py --cold
python validate_results.py

See REPRODUCTION_LEVELS.md and README_RUNNING.md for the available reproduction levels, generated artefacts, and validation workflow.

Research and indexing terms

Cyber–physical energy systems (CPES); distributed control; peer-to-peer control; distributed energy resources (DER); virtual power plants (VPP); flexibility sharing; resource-aware control; smart grids; energy storage; multi-agent systems; swarm-inspired control; dynamic average consensus; distributed optimization; control Lyapunov functions (CLF); control barrier functions; high-order control barrier functions (HOCBF); safe control; demand response; reproducible energy-systems simulation.

Canonical links

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