A Mesoscale Weather Prediction Application Towards Large Scale Wind And PV Integration In China

In recent years the development of renewable energy sources in the electricity sector is a global phenomenon evolving with faster rates of increase than the most ambitious policy makers would expect. Wind turbines and photovoltaics are the most mature technologies for electricity production. China with 1.4billion people living on 9.6million km2 of land, rich natural resources and cultural deposits, is undergoing rapid economic development, industrialization and continuous improvement of living standards, which resulted in sharply rising energy consumption. Contrary to the trend recorded in developed countries, future energy demand in China will keep growing at a rapid rate, imposing a high pressure on the power supply side. In this framework, wind energy and photovoltaics are considered as very promising fields for Chinese economy, which may significantly contribute towards energy independence and CO2 emissions reduction.Full climate characterization may require several decades of measurements. Additionally, if the purpose of the approach claims for simultaneous data in a wide area, then the approach of measurements is unpractical and very expensive. In this connection, wind and solar data in selected points in China, these points are obtained by Mesoscale Weather Prediction Model--COAMPS (Coupled Ocean-Atmosphere Mesoscale Prediction Sysytem), statistically analysed and used as input to estimate energy output. It is very important for system operators to demonstrate the variability of distributed energy production from wind farms and photovoltaics. The obtained results illustrate in quantitative terms the temporal and spatial dispersion of wind and solar energy production.In this connection a mesoscale application is used to provide information about the wind velocity and solar radiation and estimate energy produced from wind farms and photovoltaics in the whole Chinese territory, in order to analyse the temporal and spatial variation and the correlation between the two resources and between different sub-regions. Some useful conclusions may be drawn:1. The resulted Aeolian maps are in general accordance with the previous attempts of wind energy assessment in China. The windiest areas are:South-West China and especially Tibet plateau. North China, especially Inner Mongolia, all the East coast of China, North Shanxi, North Hebei and West Gansu. yellow Sea, East China Sea and South China Sea. Areas with good solar potential are:North Ningxia, West Gansu, South-East Xinjiang and Tibet plateau.2. The parallel analysis performed for wind and solar power in China, shows the spatial and temporal variation of the two main renewable energy sources suitable for large scale electricity supply. It is shown that in a distance up to 2000km, the correlation factors are higher than 0.7 indicating the rather limited effect of weather conditions to differentiate solar radiation and the resulted PV energy production at this spatial range. Even in wider ranges of latitudes and longitudes, in large distances up to almost 5000km, in China the solar radiation is obviously less correlated but still with factors more than 0.4. Far from that, wind velocity even in a moderate distance of 500km represents a correlation coefficient less than 0.4 and in 1000km there is almost no correlation. The smoothing effect is limited in case of solar and more intensive in case of wind. In case of wind power there is a benefit when wind power is aggregated in wider geographical zone, regardless the examined time scale.3. The dimensionless (by the mean load of the subsystem) shows the relative wind capacity against the local load demand In NECG a wind capacity of 75% of the annual mean load has already been reached in 2014. The comparison of the wind installed capacity with the local consumption gives a first idea of the expected wind energy curtailment, especially in areas with limited interconnections and weak grid. In most of the regional clusters the wind capacity is less than 50% of the average load demand. According to the simulation results, in 2014, wind energy curtailment will mainly occur in North China. The rate of curtailment reaches 20% in NECG and 5% in NCG. By 2050,5% more wind energy supply (fig.c) may occur thanks to the system integration and the reduction of curtailment rate from 29% to almost 3%. Based on this simulation, Renewable energy supply (wind, PV and hydro) could reach 43% by 2050 in China. Without system integration and development of grid infrastructures, the RES contribution will not exceed 38%.