Configuration optimization and global sensitivity analysis of Ground-Gen and Fly-Gen Airborne Wind Energy Systems. (November 2021)

• Record Type: Journal Article
• Authors: Trevisi, Filippo; McWilliam, Michael; Gaunaa, Mac
• Is Part Of: Renewable energy. Volume 178(2021)
• Page Start: 385
• Page End: 402
• Publication Date: 2021-11
• Subjects: AWES -- Configuration optimization -- Global sensitivity analysis -- Uncertainty quantification -- Sobol indices; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2021.06.011
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: This paper presents an analysis and optimization of Airborne Wind Energy Systems ( AWESs ), designed to maximize the Annual Energy Production ( AEP ) and, in the second part, the economic profit. A gradient-based optimization algorithm is used to perform the preliminary design of the main AWES sub-systems. A global sensitivity analysis is carried out to study how the design process, represented by the optimization problem, is influenced by aleatory and epistemic uncertainties. In particular, Ground-Gen and Fly-Gen AWESs are studied with a unified model to allow for a quantitative comparison. In the first part of the work, an ideal hybrid AWES design with ground and on-board power generation is considered. With this approach, the common characteristics of Ground-Gen and Fly-Gen AWES designs that maximize AEP are found. In the second part, Ground-Gen and Fly-Gen AWES optimal economic designs are analyzed individually. It is found that a fully developed AWES has strong potential to be highly competitive in the energy market, by providing cheap renewable energy. Fly-Gen AWESs are found to be slightly more profitable than Ground-Gen if the airborne unit is not replaced often. The main physical and economical characteristics of optimal designs are highlighted. Highlights: AWESs are optimized to maximize AEP and profit. Optimal designs are studied with global sensitivity analyses. Optimal designs of Fly-Gen and Ground-Gen AWESs are compared.