A multi‐criteria methodology for wind energy resource assessment and development at an intercontinental level: Facing low‐carbon energy transition. Issue 2 (22nd September 2022)

• Record Type: Journal Article
• Authors: Wu, Jiawei; Xiao, Jinyu; Hou, Jinming; Sun, Wei; Li, Peng; Lyu, Xunyan
• Is Part Of: IET renewable power generation. Volume 17:Issue 2(2023)
• Page Start: 480
• Page End: 494
• Publication Date: 2022-09-22
• Subjects: Renewable energy sources -- Periodicals; 333.79405
• DOI: 10.1049/rpg2.12590
• Languages: English
• ISSNs: 1752-1416

Abstract

Abstract: Quantitative assessment and effective utilization of wind energy resources in global range are substantively meaningful in contemporary low‐carbon energy scenarios. In order to enrich the assessment with large‐scale applicability, multi‐factor consideration and quantitative economic analysis, a multi‐criteria assessment method for global wind energy with consideration of both environmental and economic factors (existing power grids, transportation, etc.) is proposed. Based on 18 items of basic digital data, a model is established from three dimensions of theoretical, technical and economic criteria, respectively. Global wind resources assessment is then accomplished with a spatial resolution of 500 m. The results indicate that global technical potential is 206 TW, of which 73% is from onshore wind, and around 132 TW is suitable for centralized development. Specifically, the global average development cost is 4.28 ¢/kWh, including 4.13 ¢/kWh onshore and 4.57 ¢/kWh offshore. The global distribution maps are drawn. Furthermore, combining geospatial calculation and statistical analysis, the cumulative probability distribution curves are obtained with two key indexes of capacity factor and development cost. A case study supporting a low‐carbon energy transition scenario indicates the overall cost of the future wind power demand of 6.76 TW can reduce to 2.48 ¢/kWh ideally in 2035. Finally, a rationality verification method is proposed. By the case study of global built wind farms, the geographical location coincidence of the assessment results is 83%.