Methodology and software for assessing the wind energy potential of the northeast of Russia

The purpose of this article is to present the analysis of modern methodology and software for assessing the wind energy potential and consider the features of the developed Wind-MCA program. The article provides a brief overview of the current state and development prospects of wind energy in the world and in Russia. Description is given to the methodical approaches and existing software for assessing the wind energy potential. Advantages and disadvantages of the sources of initial information (satellite observation data, meteorological station data, climate reference data) for assessing the wind energy potential are considered. Description is given to the Wind-MCA software features for assessing the wind energy potential. The program uses statistically unprocessed data from meteorological stations. This enables the solution of a number of problems requiring estimation of the wind energy potential with differentiation in wind directions, as well as the hourly wind energy potential in combination with other climatic data. The application of Wind-MCA is discussed for solving these types of problems. The methods of accounting a terrain relief effect on the wind speed depending on its direction is presented. Assessment results of the wind energy potential for the area of the Ayan settlement, Khabarovsk Territory are given. An approach to assessing the options for the distributed location of network wind farms to reduce the effect of short-term variability of wind speed on station power fluctuations is described. The simulation results of electric energy generation by wind power plants under their concentrated and distributed siting in the Kabansky district of the Republic of Buryatia are given. A new Wind-MCA-implemented approach to accounting the effect of blade icing on power generation by wind power plants is presented. The results of the wind energy potential calculation for various regions of eastern Russia are provided. The average annual electricity losses in the studied areas due to icing vary from 6.2 to 23.7%.

wind energy potential, wind power plants, software, meteorological station data, climatic factors, icing