Sustainable Biogas Utilization in Wastewater Treatment Plants: A Predictive-Optimization Decision-Making Framework for CHP Investments and Operations

Although biogas and combined heat and power (CHP) technologies are mature, the economic feasibility of energy recovery depends on plant operations, technology costs, and energy prices. This study develops a decision-support framework integrating multilinear regression for biogas prediction, stochastic natural-gas price modeling using a mean-reverting process, and mixed-integer linear programming (MILP) to evaluate digester operation and CHP technology selection under uncertain market conditions. The framework was applied retrospectively to a 55 MGD wastewater treatment plant with thermal hydrolysis pretreatment already installed and substantial biogas flaring. Digester-specific regression models were calibrated using 2022–2023 records and evaluated against prepared 2024 observations, yielding R2 values of 0.68–0.78. Four natural-gas price scenarios were evaluated through 100 stochastic runs per scenario. CHP technology selections were more consistent under high and extreme gas-price scenarios and more variable under low and reference scenarios. Reported undiscounted payback periods were >20, 18.9, 16.4, and 12.3 years for the low, reference, high, and extreme scenarios, respectively. Higher natural-gas prices increased modeled avoided energy costs and shortened investment recovery periods. The results support preliminary screening of CHP pathways under alternative gas-price conditions, with economic performance remaining conditional on the modeled operating and cost assumptions.