Power Market Forecasting Using Particle Swarm Optimization with Grey Model Integration
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Resource Overview
Custom implementation combining particle swarm optimization and grey model for power market forecasting, featuring standard PSO algorithm with parameter optimization capabilities for grey model coefficients.
Detailed Documentation
This research presents a novel approach to power market forecasting by integrating particle swarm optimization (PSO) with grey prediction models. I developed custom source code implementing the standard particle swarm optimization algorithm to optimize the parameters of the grey model. The implementation includes key functions for swarm initialization, velocity updates using inertial weights, and position updates based on personal and global best solutions. The algorithm effectively handles the optimization of grey model coefficients to improve prediction accuracy. Through extensive testing and validation, this hybrid approach demonstrates significant potential in power market forecasting. The evaluation results confirm that our model achieves exceptional performance in predicting power market trends, with particular strength in handling small-sample data scenarios common in market forecasting applications.
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