A Virtual Power Plant Electricity-Carbon Price Forecasting Model Based on Adaptive Learning Algorithms

Key Points

• The central aim is to develop a forecasting model for electricity-carbon prices using adaptive learning algorithms.
• Utilized adaptive learning algorithms for model development.
• Incorporated variables related to electricity and carbon pricing dynamics.
• Analyzed forecasting accuracy through model validation techniques.
• Achieved an improved forecasting accuracy of electricity-carbon price compared to traditional methods.
• Demonstrated significant reduction in forecasting errors, enhancing predictions over a standard benchmark.