Study on ADMM-GBS-based real-time electricity price forecast considering wind power consumption

Accurate real-time electricity price forecasting plays a crucial role in maintaining the stability of power systems and ensuring the efficient operation of the market. The increasing integration of renewable energy sources such as wind power has brought about greater price volatility, complicating the forecasting process. Traditional forecasting methods often fail to address these complexities. To solve this problem, this study proposes a new forecasting model. This method integrates the Alternating Direction Method of Multipliers (ADMM) and the Gaussian Back Substitution (GBS). By analyzing the impact of wind power consumption on electricity prices, this model developed targeted features to enhance its predictive ability. ADMM provides efficient distributed optimization, while GBS ensures high prediction accuracy, thereby achieving accurate real-time price prediction. This work not only promotes better operation of the electricity market but also supports the development of renewable energy and drives the improvement of the energy structure.