Short-Term Prediction of Wind Power Output Based on Markov Chain

Wind power short-term predicting technology has a great significance in process of wind power decision-making. Recent years, the technology had been studied extensively in industry. Markov chain model has strong adaptability, forecast accuracy higher and other else advantages, which is suitable for wind power short-term prediction. This paper have set up one step Markov prediction model and based on which predicting short-term wind power output, and taken the historical power data of an actual wind farm in Jilin Province as an example to simulate and analyze. The paper also have proposed and used RMSE, MXPE, MAPE error analysis indicators to analyze simulation results of different status spaces. The results showed that when the status space is 60 the prediction accuracy of the method is best.