Global energy demand has been growing over the last decades, having a significant impact on the environment. Alternatives that can mitigate these effects are crucial for the future of our planet. Wastewater Treatment Plants (WWTPs) are a vital infrastructure to manage residual waters, presenting an opportunity for energy production from the released biogas during the anaerobic digestion phase. The present study uses a multivariate recursive forecasting approach to evaluate the performance of Transformer-based models in forecasting electricity production in this context. Transformer-based candidate models were developed, and their hyperparameters were tuned using a grid search. The best Transformer candidate achieved the second-best Root Mean Square Error (RMSE) value of 359.4 kWh, outperforming the Gated Recurrent Unit (GRU) by 9%, although the Long Short-Term Memory (LSTM) model performed the best.