Coupling Hidden Markov Short Term Load Forecasting Method For High Proportion Of Renewable Energy Power System

The accurate prediction of short-term load plays a crucial role in grasping the variation of user load and formulating a scientific and rational planning strategy.With the continuous development of renewable energy technologies,a large proportion of renewable energy grids will become the basic characteristics of the future power system.The continuous development of smart grid technologies and subsidies for renewable energy price subsidies will provide technical support for the time-shift of active load and Policy incentives and double promotion make the coupling between load demand and renewable energy output stronger.Based on the above background,this paper presents a short-term load forecasting method based on the coupled Hidden Markov Model.The introduction of renewable energy output effect in the load demand forecasting to improve the short-term load forecasting efficiency of highproportion renewable energy power system mainly completes the following jobs:(1)The research status quo of short-term load forecasting method in power system is researched,and the problems that the short-term load forecasting method is still unresolved are put forward;(2)Investigating the status quo of renewable energy development,analyzing the problem of limiting large-scale renewable energy grid-connected in China,analyzing renewable energy power system renewables from two aspects of renewable energy policy incentives and smart grid technical support The internal mechanism of interactive coupling of energy output and load demand;(3)The method of data preprocessing in power system load forecasting is studied,and the cross-spectrum analysis method of pre-processed load demand and renewable energy output data is proposed.By using the coherence spectrum and phase spectrum index,Lagging behind the relationship between the characterization;(4)Hidden Markov and coupled Hidden Markov models are studied for the forward-backward algorithm,Viterbi algorithm and BW algorithm to solve the evaluation,decoding and learning problems.The coupled Hidden Markov Short-term load forecasting model(5)Combining with cluster analysis method and Markov error correction process,a short-term load forecasting method based on coupled hidden Markov model is proposed.The case study shows that the forecasting method proposed in this paper is effective and predictive.It is a feasible attempt to predict the power demand of high proportion of renewable energy access to the power system.