A Feature-Based Cost Estimation Model for Wind Turbine Blade Spar Caps

Abstract

A problem for wind turbine operators is decreasing prices for wind-generated electricity. Many turbines are approaching their rated 20-year lives. A more economically viable and sustainable solution that reduces Levelized Cost of Energy (LCOE) and avoids expensive turbine replacement is retrofitting new spar caps blades. A new cost model assesses the feasibility of retrofitting 35 to 75 m turbines with GFRP (glass fiber reinforced polymer composite) and longer length CFRP (carbon fiber reinforced composite) spar caps. Spar cap cost scales with features such as mass, volume fraction and complexity. Organizational learning is a cost factor. Material and direct labor increase as proportions of total cost while tooling, capital, utilities, and indirect labor decrease. There is good agreement between a manufacturer and the model. Twenty-year turbines were compared with retrofitted spar caps over 25 years for LCOE. Same length GFRP and longer length CFRP spar cap retrofits decrease LCOE. Longer length CFRP spar caps decrease LCOE compared with GFRP retrofits over 25 years. CFRP material cost impacts CFRP retrofit feasibility. Retrofitted turbines must meet engineering, operational performance, and planning requirements criteria. Software algorithms may improve human learning and enable automatic updates from varying design and cost inputs, thereby increasing cost prediction accuracy.

Managing Cloud Intelligent Systems over Digital Ecosystems: Revealing Emerging App Technology in the Time of the COVID19 Pandemic

“…The task prioritizing phase will determine the priority of each task and the instance selection phase will determine the best task to execute. Compared to MOHEFT, FDHEFT has a better execution time and gets a better solution with fuzzy dominance sort [3,[13][14][15][16][17][18].…”

“…Cloud intelligent systems are a new business model related to the management of computing resources, both storage, communication networks and computing power using the pay-as-you-go paradigm where users only pay according to the resources they use. Pay-as-you-go offers computing facilities on a large scale without having to own hardware so users do not pay for investment in information and communication technology (ICT) infrastructure [3][4][5][6][7]. However, during the COVID19 pandemic the communication and marketing patterns will be more through digital canal.…”

Bottom-up manufacturing cost optimisation of composite aircraft structures: Manual layup vs. automated layup

“…Many previous works have developed approaches for modelling the costs associated with layup techniques [2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26]. One notable example is Hagnell et al [19] where a cost modelling methodology was developed to model the costs associated with ML, AFP and Automatic Tape Layup (ATL), an alternative to AFP that uses tapes instead of tows.…”

Reliability-based bottom-up manufacturing cost optimisation for composite aircraft structures

“…Many examples can be found in the literature presenting methods for the comprehensive manufacturing cost estimation of composite aircraft parts (Sun et al 2021;Muflikhun and Yokozeki 2021;Zabihi et al 2020;Van Grootel et al 2020;Clarke et al 2020;Chen et al 2020;Hueber et al 2019;Hagnell 2019;Wang et al 2018;Soares et al 2018;Shama Rao et al 2018;Aniruddha 2018;Al-Lami et al 2018;Pinto 2017;Kalantari et al 2016;Hueber et al 2016;Hagnell et al 2016;Hagnell and Åkermo 2015;Shehab et al 2013;Schubel 2012;Weitao 2011;Song et al 2009;Liu 2009;Mazumdar 2002;Haffner 2002). One notable example is a doctoral thesis by Haffner (2002) which provides a comprehensive overview of common methods used to manufacture composite aircraft parts, including detailed estimates for material, tool, machine, and labour costs.…”