Regional Impact Assessment of Monsoon Variability on Wind Power Availability and Optimization in Asia
Recent developments have emphasized the global impacts of climate change and have renewed commitments in renewable energy and energy meteorology. Wind energy depends largely on prevailing meteorological conditions on both local and large scales, thus, wind power optimization should aid its assessment and development. This study uses ERA-Interim daily data from 1979 to 2014 to investigate the impact of the East Asian Monsoon on wind power in Asia. Wind power increase in the Bay of Bengal region
... s wind vectors strengthened from winter (DJF, December-January-February) to summer (JJA, June-July-August), while the predominant direction shifted to southwesterly. The influence of the South China Sea on South East Asia resulted in increased wind power that peaked in winter. Probability distribution functions for four sub-regions revealed higher probabilities of relatively lower wind speeds in JJA, except for the South East region, where most probable wind speeds were reached in winter. The capacity factor also varied by region and by season. Power generation was lowest in JJA for all the regions except the South West. The South East region also had the highest power generated over the domain. This variation of wind power impacts the amount of energy that must be supplied by non-wind sources, termed Demand Net Wind (DNW). Knowledge of DNW fluctuations thus becomes an important consideration for optimization of power plants, grid networking and reliability, and energy markets. development of wind farms on the local and mesoscales, while research on the nature, availability, and variability of wind is also underway by environmentalists, meteorologists, and earth scientists. More recent discourse has also taken various forms, from micro-grids to regional renewable power systems. The regional system allows a connection between renewable power systems that can be shared by provinces, regions, or even nations. Of course, the dependence of renewables on climate means that the affected nations in the case of the international system must first understand the timescale variability of their respective renewable sources. Conventionally, near-surface winds are known to vary, ranging from short, speedy gusts of a few seconds to minutes in duration to prolonged circulations that form a pattern, which itself also varies. Research into wind speed variability with respect to wind energy development has progressed from infancy  to short-span durations [8, 9] , long-term trends, wind speed prediction, and wind power production     . Although abundant works exist on wind energy development and potential, especially for its sustainable characteristics, more recent works are beginning to focus on the variable nature of wind itself [12, 13] . The energy industry is a forerunner in the development of wind power and usually takes the mean wind power potential for a specific number of years as a key indicator , which is justifiable. However, the power output from wind turbines is also subject to the associated variability of wind vectors, which has often been described as intermittency by energy experts. Circulation patterns usually provide insight into wind variability  . The seasonal reversal of wind direction near the surface of the earth is referred to as the monsoon  . The East Asia region (in which China lies) covers about 12 million km 2 and is bounded by Russia and Mongolia to the north and South East Asia on the east. The massive region itself, the Pacific Ocean to the east, as well as the topographic details of the Tibetan Plateau, all form essential circulation-influencing elements. The land-sea thermal contrast created by these elements is the major driver for the climate in the region, termed the East Asian Monsoon, which is basically a reversal of wind flow from a southwesterly pattern to a northeasterly pattern. This reversal causes the warm and wet summer monsoon to alternate with the cold and dry winter monsoon, giving rise to two meteorological seasons, namely summer and winter. Various attempts have been made to fit these seasons to a particular time frame using various parameters such as the switch of zonal winds  , an increase in convective activities  , changes in precipitation patterns  , the summation of the sea level pressure (SLP) gradient between land and sea, also called the Guo Index  , and other conventional methods. A consensus reached, however, is that there are transitional periods for these seasons on both sides that have now been described as spring and autumn. The advance and retreat of the leading monsoon fronts in both winter and summer produce an interphase that is neither summer nor winter, thereby dividing the annual timescale into the seasons of winter, spring, summer, and autumn, which are interchangeably called astronomical seasons in certain fields. In optimizing wind energy output, it is imperative to know whether seasonal variations exist in wind vector properties and if there is a notable pattern in such variation. Such knowledge would be valuable for the design, operation, and optimization of hybrid power systems, thereby impacting on a more efficient and reliable power supply system. By adopting a regional approach for Asia, this study advances knowledge gained from previous contributions in wind assessment studies, especially in terms of seasonal wind power availability and variability, as well regional grid interconnectivity and networking from an increased-penetration approach. Seasonal designations are winter, comprising December-January-February (DJF); spring, comprising March-April-May (MAM); summer, comprising June-July-August (JJA); and autumn, comprising September-October-November (SON). The seasonal variation in wind speed and wind power plus its impact on energy generation over the study area are fully investigated. Data and Methodology The ERA-Interim reanalysis data provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) is a high-resolution database of atmospheric, climate, ocean, and hydrological Atmosphere 2017, 8, 219 3 of 14 dataset with global coverage from 1979 onwards  . For this study, the parameters listed below for the years 1979-2014 at a spatial scale of 0.5 • by 0.5 • on 6-hourly time-steps were utilized over the domain of 10 • -60 • N latitude and 70 • -120 • E longitude. In order to simultaneously examine regional levels and their possible impact on an interconnected system, four regions, namely North West, North East, South West, and South East/Coastal, were also studied. The topographical details of the study area as well as the locations of the regional domains selected are illustrated in Figure 1 . A detailed meteorological regional division is not used, since the aim is to show in a rather unsophisticated manner the possible variations of available wind power essential for wind power optimization on regional scales. The Qinghai-Tibet plateau (>3500 m above sea level) is blacked out in the figures contained in subsequent sections.