This paper deals with conceptual engineering solutions for floating wind power plant designed to supply electrical power to Russian Arctic coastal and island territory. Layout of a sea-based Arctic wind power plant design was proposed based on the analysis of current wind turbines. Main wind, wave and ice loads acting on the wind power plant in Arctic conditions have been determined. Options of floating wind power plant substructures have been analysed. Numerical modelling of behaviour of the conceptual offshore wind power plant options in question has been performed. Strength analysis of substructures for Arctic offshore wind power plant options in question has been performed.
Russian grid energy industry has been traditionally based on major hydraulic power plants, nuclear and thermal power plants. However, offshore, island, and coastal areas of the Arctic ocean have significant wind energy resources. Their exploitation through building autonomous floating wind power plant and coastal wind power plants, and wind-diesel power plants may contribute significantly to reduction in diesel fuel deliveries to the Northern Regions, and to power supply improvement (Elistratov, 2016). In this article, ice-resistant floating wind power plants are discussed in more detail.
Arctic regions have high wind power potential; however, there are challenges of estimation of wind power resources in the regions in question due to low density of meteorological stations in the coastal areas (1 station per 50 to 70 thousand sq. km) and lack of these for offshore territories. Without meteorological information of good quality, wind energy resources estimation is performed using MERRA reanalysis data bases that are based on satellite observations and represent multi-year hourly series of wind velocity and direction values at grid points with step of 2/3° in latitude 0.5° in longitude. Estimation and prediction of short-term, medium-term, and long-term variation of wind power resources incoming to the Arctic regions have been made using proprietary methodology for wind energy resources estimation in conditions of limited climatic information based on three-level approach (Elistratov, 2016). Fig. 1 shows a map of territorial distribution of yield wind energy resources at 50 m height for the Nenets Autonomous District (Elistratov, Dyuldin, Slivkanich, 2016).
