Enhancing power load forecasting accuracy under high renewable energy penetration with a MSN-KAN framework: A novel approach to mitigate non-stationarity and enhance interpretability

Key Points

• Enhanced accuracy in power load forecasting is achieved through the MSN-KAN framework, addressing non-stationarity and improving interpretability.
• The framework integrates innovative algorithms for better adaptability to varying energy sources and conditions in real-time scenarios.
• Assessment using a structured approach evaluates forecasting performance against traditional methods, focusing on accuracy metrics and interpretability.
• This advancement may enable more effective energy management and planning, particularly in environments with high renewable energy integration.