Biogas-to-Resilience: model scripts and results for "Biogas as a Resilience Fuel for Wastewater Treatment under Chronic Grid Failure: Demand-Based Design, Gas Storage and Economics for Three Lebanese Plants

Python scripts, result files and figures for the article “Biogas as a Resilience Fuel for Wastewater Treatment under Chronic Grid Failure: Demand-Based Design, Gas Storage and Economics for Three Lebanese Plants” (Energies, resubmission of energies-4676450). The model assesses whether sludge biogas can keep three Lebanese wastewater treatment plants (Al Ghadir, Tripoli, Saida) running through daily blackouts of 4, 12 and 20 h/d. It covers bottom-up electricity demand at three service levels, gasholder sizing with an hourly simulation of persistent random outages and variable gas production, a closed COD balance with a digester heat balance, an hourly CHP reliability model under normal and crisis operation and maintenance, greenhouse-gas accounting including the sludge chain against a single reference plant, and economics in constant 2024 USD with break-even values, PV–battery systems and hybrids. Fifty-six uncertain inputs are propagated jointly through 10,000 Monte Carlo draws. Running bash run_all.sh (about one hour; Python 3 with the versions in requirements.txt) regenerates every results file (task*_results.xlsx), the logs and Figures 2–7; make_figure1.py draws Figure 1. README.txt describes each script, and File_S1_Model_log.pdf documents every change to the model since the first submission. This version adds Figure 1 and its script, the TIFF figures, a licence file and a corrected check-table row in Task 2; no reported result changed. PVGIS data: European Union, JRC.