Performance Analysis And Simulation Algorithm Study Of Wind/Photovoltaic Power

With the development of wind/photovoltaic power generation technology, the scale of wind/photovoltaic power is increasing as well as its grid connected operation. However, the power quality, stability and reliability of large scale distributed wind/photovoltaic are negatively affected due to its intermittence and randomness. Therefore, to build accurate and reasonable time series model of wind/photovoltaic power output is extremely important for power grid planning and operation. In this paper, the characteristics and time series modeling of wind/photovoltaic power are researched.The basic data processing knowledge and method in this paper are introduced in the beginning. After that, the modeling evaluation index system which includes statistical characteristics parameters, correlation, probability distribution is established. Besides, the data preprocessing method of wind/photovoltaic power is studied to facilitate the characteristics studying and modeling.Then, the power characteristics of wind and photovoltaic are defined and researched based on actual wind and photovoltaic power data, respectively. And PV power research includes daily characteristics, seasonal characteristics, weather characteristics and fluctuation characteristics. Besides daily and fluctuation characteristics, the research about wind power includes state transfer characteristics.In addition, considering the fluctuation, daily characteristics, seasonal characteristics and weather characteristics, a Markov model for generating time series of photovoltaic power is established based on Markov chain. The simulation data are obtained by improved model which established by actual photovoltaic power data. By comparing the simulation data and the historical sequence, the effectiveness of improved model-generated data is confirmed. Meanwhile, the comparison between improved model-generated and original model-generated data proves the necessity of model improvements. Besides, the fluctuation characteristics of wind power are considered to establish an improved Markov model for generating time series of wind power. The original Markov chain model simulation data and improved model data are obtained on account of measured data of wind power. Finally, the effectiveness and accuracy of improved model-generated data are verified by comparing two kinds of simulation data and historical sequence.