This repository implements a high-fidelity digital twin and optimization framework for Sodium Iron Pyrophosphate (NFPP) battery systems within an integrated plant–network digital twin framework for solar–BESS microgrids.

Research Scope

1. DFN-Based NFPP Cell Optimization

A hierarchical multi-stage framework for cell design enhancement:

• Layered Material Mapping: Decoupled architecture for eco-friendly salts (NaTCP, NaBOB), cathode dopants (Cr, Mn, Ni), and MTMS functionalization.
• Parameter Optimization: Hierarchical search for structural ($\theta_s$) and material ($\theta_m$) parameters using sensitivity-based Jacobian screening and Genetic Algorithms.

2. Multi-feeder solar–BESS network state realization and anomaly detection using phase dynamics (Core Contribution)

The primary research focus is the realization of network states and anomaly detection in a multi-feeder microgrid coupled by shared solar and BESS sources.

Phase-Based Diagnostics

• Shared Source Coupling: Modeling $P_{source} = P_{solar} + P_{BESS} = \sum P_{F_i} + P_{loss}$.
• Network Realization State: Tracking $X_R = [\Delta \theta_{F1}, \dots, \Delta \theta_{Fn}]$ for phase-based anomaly detection.
• Propagation Analysis: Analyzing how disturbances in one feeder propagate through the shared source to affect the wider network.
• Anomaly Localization: Identifying feeder-level faults when $\Delta \theta_{Fi}$ deviates from the expected stability envelope.

3. Physical Power Plant Model (Digital Twin)

The plant environment represents the physical microgrid hardware:

• Microgrid Assets: 100kWp Solar PV, 50kW Primary Generation, and 100kWh BESS (208 modules).
• Multi-Feeder Topology: Feeders coupled to a shared solar-BESS source via utility-scale power conditioning.
• Architecture: Multi-string Central Inverter → LV/MV Step-up Transformer → MV Switchgear → Utility Grid.

Repository Structure

• src/cell_optimization/: Material discovery engines and structural optimization scripts.
• src/power_plant/: Utility-scale power plant control logic, digital twin components, and energy dispatch validation.
• src/simulation/: Multi-feeder network simulator, cell simulation utilities and phase dynamics analysis.
• nfpp_sodium_ion/: Registered PyBaMM parameter set for NFPP/Hard-Carbon chemistry.
• src/report.ipynb: Orchestration notebook for the complete research pipeline.

Getting Started

Installation

# Install core dependencies
pip install -r requirements.txt

# Install PyBaMM parameter package
pip install -e nfpp_sodium_ion/

Execution

Run the complete research pipeline via the Jupyter notebook:

jupyter notebook src/report.ipynb

References

• Paper Title: DFN-Based Optimization of NFPP Sodium-Ion Cells within an Integrated Plant–Network Digital Twin Framework for Solar–BESS Microgrids
• Core Chemistry: Sodium Iron Pyrophosphate (NFPP) vs. Hard Carbon
• Modeling Framework: PyBaMM (Electrochemical), FEniCSx (Mechanical), Simscape, Matlab (Power Systems)