This study addresses the increasing need for flexibility in the Polish Power System (PPS), particularly in the context of growing price volatility on the Day-Ahead Market (DAM) resulting from the rising share of renewable energy sources (RESs). The aim of the study was to assess the feasibility of implementing demand-driven operation in an existing linear biogas plant in Poland and to develop a Decision-Making Model (DMM) for optimizing its operation based on electricity price forecasts. A machine learning model based on Extreme Gradient Boosting (XGBoost) was developed using historical electricity price, demand and weather data and integrated into the DMM to generate hourly operating schedules. The model achieved high predictive accuracy, with a Mean Absolute Error (MAE) of approximately 51 PLN/MWh, and effectively captured nonlinear price dynamics. Based on predefined decision thresholds—biogas production rate, current biogas storage level, upper and lower limits of pressure in biogas storage capacity, maximum biogas storage duration, power quotient (PQ) and electricity price levels—optimal operating strategies were determined. The results indicate that while demand-driven operation is technically feasible and enables better alignment with market signals, its economic viability remains limited under current market and regulatory conditions. Investment in additional cogeneration capacity was not justified, as costs significantly exceeded potential revenues. Consequently, a more viable approach involves optimizing existing infrastructure through flexible production strategies.