The wind model based on Markov process to determine the capacity for wind farm

Abstract

The wind model based on Markov process was proposed to determine the best installed capacity of wind farm. Firstly, piecewise probability distribution model based on Markov process was proposed to establish the scheduling multiple state probability distribution of wind power. Secondly, the probability production simulation method using the sequential convolution and non-sequential convolution was proposed to calculate the evaluation index which includes annual utilization hours of wind farm, wind curtailment, cost of traditional units and benefit of wind farm. Then the best installed capacity of wind farm could be calculated according to the above evaluation index with the aim to minimize the cost of the system. A case study was employed to illustrate the effectiveness of the proposed approach.