Onshore versus offshore wind power trends and recent study practices in modeling of wind turbines’ life-cycle impact assessments

Abstract

Wind energy has gradually become one of the most efficient and reliable forms of sustainable energy, and it is being globally utilized to accelerate the expansion of green power production. However, recent projections of onshore & offshore wind energy systems indicate that further improvements are continuously required in terms of the deployments, capacity factors, costs, etc. to achieve an optimal wind power generation. According to these projections, the most critical current issue is the offshore systems' high levelized cost of energy, which demands the enhancements of the technologies to ensure the cost reduction in the future. Moreover, a number of reports are underscoring that offshore power systems can also leave a larger carbon footprints through their life-cycles compared to the onshore counterpart. On the other hand, the modelling methods of the power plants' life-cycle impact assessment (LCIA) have nowadays become among the most compelling research problems in the field of wind power systems engineering. In addition to comparatively assessing the characteristics of onshore & offshore energy systems based on some reports & studies, this work is therefore aimed at rigorously exploring the existing study practices in modelling the wind power plants' LCIA. A number of these practices were based on the implementation of various conventional modelling methods that may not help to make accurate assessments of the wind power plants’ life-cycle impacts. Hence, one of the main contributions of this study is to summarize a novel LCIA modelling approach based on Internet of Things (IoT) and predictive digital twin technologies. Unlike the conventional methods, real-time data extraction from the power plants makes these technologies possible to conduct the most accurate assessments of the life-cycle impacts.