Next-Day Power Market Clearing Price Forecasting Using Artificial Fish-Swarm Based Neural Network

摘要

Market clearing price (MCP) is one of the most important factors impacting on power system. Taking into account the features of deregulation and fluctuation, this paper uses artificial neural network to forecast next-day MCP, with period-decoupled data sequence and wavelet transform. For the purpose of better performance, an improved learning algorithm of artificial fish-swarm is proposed. By simulating fish-swarm actions, in random searching for foods, artificial fish-swarm based neural network (AFNN) achieves global optimum. Comparing with traditional next-day MCP forecasting methods, the suggested method could achieve better adaptability and greater predictive accuracy, which -was proved by the experimental results.