A Wind Speed Simulation Approach Based on Markov Sequence Model and Archimedean Copula

Simulating wind speed has important implications in wind energy research. This paper provides a wind speed simulation approach based on Markov sequence model and Archimedean Copula for planning purposes. Firstly, a Markov Sequence model is presented to describe the transfer rule of wind speed time series (WSTS). Secondly, an Archimedean Copula function (AMC) is applied to capture the temporal dependence between wind speeds of adjacent times and then obtain the transition kernel. Finally, conditional sampling technique is used to generate the wind speed of next hour. The advantage of the model lies in avoiding the loss of information of wind speed data during the discretization procedure by replacing the discrete transition matrix with the transition kernel and characterizing different dependence structure with Archimedean Copula function. A case study proves that the model can offer satisfactory fit for both probability distribution and temporal dependence. The model is applied to a reliability test system. The results show that the model can be used to evaluate the reliability of power systems with wind energy.