An approach to multi-objective life cycle cost optimization of wind turbine tower structures

[摘要] ENGLISH ABSTRACT: Support tower structures of Wind Energy Conversion Systems (WECS) are major costitems and by means of integrated design and optimization, the Life-Cycle Cost (LCC) canbe reduced substantially. In this thesis, Horizontal Axis Wind Turbine (HAWTs) towerstructures are investigated by means of a technique or tool that can bene t in decisionmaking related situations to reduce the LCC of such WECS support towers from inceptionto disposal.Often, during the conceptual design phase a certain level of uncertainty or fuzziness existsand plays a role. The central focus in this project is on lattice type towers; however anaccount on tapered, tubular monopole towers is given as well. The problem is identi ed tobe of a multi-objective nature, where a variety of criteria or objectives that are identi edplay a role in the possible reduction of the total LCC of the structure. The study alsoentails the delineation and discussion of the factors and components that a ect the LCCof a steel structure. The decision maker has control over only a few of these factors andcomponents as identi ed, and these can be formulated by means of an objective to be minimized (or maximized in several other cases). Some of the objectives are incommensurableand others are commensurable with each other. In other words, several of theseobjectives either `compete' or don't `compete' against each other, respectively. The investigationresulted in the development of a multi-objective LCC optimization using the λ-formulation (or min-max formulation) as the objective aggregating approach for thefour objectives identi ed (varied during analysis for sensitivity checks). The objectivesare user-de ned in terms of membership functions that grade the degree of membershipfrom total acceptance to total rejection by means of boundary values. This formulation isNon-Pareto based and the decision maker obtains the best trade-oor best compromisesolution. The detailed discussion around these objectives is included in the literaturestudy. The objectives in the multi-objective study are weight, cost, perimeter and nodaldeflections, and a weighting of the objectives is possible but this is excluded from thisstudy.A Genetic Algorithm (GA), coded in MATLAB, is implemented as the optimization toolor technique. The algorithm uses a quadratic penalty function approach and a nativelywritten Finite Element Analysis (FEA) tool is used for the response model in thetnessevaluation process, where the performance for stability, capacity and overall deflectionsof an individual in the population is quanti ed. A GA has the advantage that it operateson an entire population of individuals using basic principles such as genetics, crossover,mutation, selection and survival of thettest from biology and Darwinian principles.GAs are very robust and e ective global search methods that can be applied to most elds of study. GAs have previously been e ectively applied in structural, single objectiveoptimization (structural weight) problems. The GA is adopted and modi ed and veri edwith results on academic problems obtained from literature. Satisfactory performancewas observed, although room for improvement is identi ed.A case study on a full scale model is performed, using circular hollow sections and equal leg angle sections. These are commonly used steel profi les for lattice type towers. The resultsobtained are as expected. The structural mass was used as a measure to compare theresults. A heavier structure is obtained using the equal leg angle sections compared to theCHS structure with a di fference of up to 20% in weight. The best compromise solutionsare feasible and near optimal, given the conditions of the equally weighted objectives inthis study. The membership function defi nition and boundary value determination stillremains a key issue when using fuzzy logic to incorporate the preference information ofthe decision maker.

[发布机构] Stellenbosch University