Electricity price forecasting remains a critical research focus in modern power systems, where future electricity prices are influenced not only by historical electricity price patterns but also by exogenous factors. Traditional approaches often employ single-stream recurrent neural networks to integrate exogenous variables with historical electricity price sequences. However, since historical electricity prices and exogenous information inherently represent distinct modalities, single-stream ar