scholarly journals The Parametric Modeling and Two-Objective Optimal Design of a Downwind Blade

2021 ◽  
Vol 9 ◽  
Author(s):  
Bofeng Xu ◽  
Zhen Li ◽  
Zixuan Zhu ◽  
Xin Cai ◽  
Tongguang Wang ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Energy Production ◽  
Optimization Design ◽  
Twist Angle ◽  
Bending Moment ◽  
Pareto Optimal ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Blade Root ◽  
Extreme Scale

To cope with the future challenges to the blade that will be introduced by the development of extreme-scale wind turbines, this study focuses on the optimization design of the aerodynamic shape of a downwind blade via the inverse design method. Moreover, the genetic algorithm is used to optimize the chord, twist angle, and pre-bending parameters of the blade to maximize the energy production of the rotor and minimize the flapping bending moment of the blade root. By taking a 5-MW wind turbine as the optimization object, the two-objective optimization design of the downwind blade is carried out, and Pareto optimal solutions in line with the expectations are obtained. After analyzing four representatives of the Pareto optimal solutions, while a more ideal solution is found to sacrifice 9.41% of the energy production of the rotor, the flapping bending moment of the blade root is reduced by 42.92%, thereby achieving the lightweight optimization design of an extreme-scale wind turbine blade. Furthermore, based on the selected four sets of blades, the influence mechanisms of the chord, twist angle, and pre-bending on the optimization goal are analyzed, and it is found that the pre-bending parameter has the greatest influence on the two optimization goals.

Optimization Design of Double-Helical Gear with High Contact Ratio

2012 ◽  
Vol 248 ◽  
pp. 91-94
Author(s):  
Ning Zhao ◽  
Peng Yuan Qiu ◽  
Sheng Wen Hou
Keyword(s):  
Genetic Algorithm ◽  
Optimization Design ◽  
Original Data ◽  
Helical Gear ◽  
Pareto Optimal ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Contact Ratio ◽  
Helical Gears ◽  
Numerical Examples

Fast Elitist Non-dominated Sorting Genetic Algorithm is introduced in this paper to optimize the performance of double helical gears with high contact ratio.It is effective and timesaving. Numerical examples that illustrate the developed theory are provided. Feasibility of it is validated by analysis of contrast between Pareto optimal solutions and original data.

scholarly journals Optimization Of Multi-Module CrN/CrCN Coatings

2015 ◽  
Vol 60 (2) ◽  
pp. 1037-1043
Author(s):  
Ł. Szparaga ◽  
P. Bartosik ◽  
A. Gilewicz ◽  
J. Ratajski
Keyword(s):  
Optimization Procedure ◽  
Stress And Strain ◽  
Pareto Optimal ◽  
Mutual Distance ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Decision Criteria ◽  
Decision Variables ◽  
42Crmo4 Steel ◽  
The Stability

Abstract In the paper was proposed optimization procedure supporting the prototyping of the geometry of multi-module CrN/CrCN coatings, deposited on substrates from 42CrMo4 steel, in respect of mechanical properties. Adopted decision criteria were the functions of the state of internal stress and strain in the coating and substrate, caused by external mechanical loads. Using developed optimization procedure the set of optimal solutions (Pareto-optimal solutions) of coatings geometry parameters, due to the adopted decision criteria was obtained. For the purposes of analysis of obtained Pareto-optimal solutions, their mutual distance in the space of criteria and decision variables were calculated, which allowed to group solutions in the classes. Also analyzed the number of direct neighbors of Pareto-optimal solutions for the purposes of assessing the stability of solutions.

A DECOMPOSITION-COORDINATION METHOD FOR COMPLEX MULTI-OBJECTIVE SYSTEMS

2009 ◽  
Vol 26 (06) ◽  
pp. 735-757 ◽  
Author(s):  
F. MIGUEL ◽  
T. GÓMEZ ◽  
M. LUQUE ◽  
F. RUIZ ◽  
R. CABALLERO
Keyword(s):  
Information Exchange ◽  
Exchange Process ◽  
Efficient Solutions ◽  
Pareto Optimal ◽  
Relative Importance ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Conflicting Objectives ◽  
Upper Level ◽  
Problem Instances

The generation of Pareto optimal solutions for complex systems with multiple conflicting objectives can be easier if the problem can be decomposed and solved as a set of smaller coordinated subproblems. In this paper, a new decomposition-coordination method is proposed, where the global problem is partitioned into subsystems on the basis of the connection structure of the mathematical model, assigning a relative importance to each of them. In order to obtain Pareto optimal solutions for the global system, the aforementioned subproblems are coordinated taking into account their relative importance. The scheme that has been developed is an iterative one, and the global efficient solutions are found through a continuous information exchange process between the coordination level (upper level) and the subsystem level (lower level). Computational experiments on several randomly generated problem instances show that the suggested algorithm produces efficient solutions within reasonable computational times.

Multiobjective optimization of the flaxseed mucilage extraction process using normal-boundary intersection approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mariana Souza Rocha ◽  
Luiz Célio Souza Rocha ◽  
Marcia Barreto da Silva Feijó ◽  
Paula Luiza Limongi dos Santos Marotta ◽  
Samanta Cardozo Mourão
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Method ◽  
Extraction Process ◽  
Pareto Optimal ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Fiber Concentration ◽  
Trade Off ◽  
Content Type ◽  
Normal Boundary

PurposeThe mucilage of the Linum usitatissimum L. seed (Linseed) is one of the natural mucilages that presents a great potential to provide a food hydrocolloid with potential applications in both food and pharmaceutical industries. To increase the yield and quality of linseed oil during its production process, it is necessary to previously extract its polysaccharides. Because of this, flax mucilage production can be made viable as a byproduct of oil extraction process, which is already a product of high commercial value consolidated in the market. Thus, the purpose of this work is to optimize the mucilage extraction process of L. usitatissimum L. using the normal-boundary intersection (NBI) multiobjective optimization method.Design/methodology/approachCurrently, the variables of the process of polysaccharide extraction from different sources are optimized using the response surface methodology. However, when the optimal points of the responses are conflicting it is necessary to study the best conditions to achieve a balance between these conflicting objectives (trade-offs) and to explore the available options it is necessary to formulate an optimization problem with multiple objectives. The multiobjective optimization method used in this work was the NBI developed to find uniformly distributed and continuous Pareto optimal solutions for a nonlinear multiobjective problem.FindingsThe optimum extraction point to obtain the maximum fiber concentration in the extracted material was pH 3.81, temperature of 46°C, time of 13.46 h. The maximum extraction yield of flaxseed was pH 6.45, temperature of 65°C, time of 14.41 h. This result confirms the trade-off relationship between the objectives. NBI approach was able to find uniformly distributed Pareto optimal solutions, which allows to analyze the behavior of the trade-off relationship. Thus, the decision-maker can set extraction conditions to achieve desired characteristics in mucilage.Originality/valueThe novelty of this paper is to confirm the existence of a trade-off relationship between the productivity parameter (yield) and the quality parameter (fiber concentration in the extracted material) during the flaxseed mucilage extraction process. The NBI approach was able to find uniformly distributed Pareto optimal solutions, which allows us to analyze the behavior of the trade-off relationship. This allows the decision-making to the extraction conditions according to the desired characteristics of the final product, thus being able to direct the extraction for the best applicability of the mucilage.

scholarly journals Two-Step Many-Objective Optimal Power Flow Based on Knee Point-Driven Evolutionary Algorithm

Processes ◽  
2018 ◽  
Vol 6 (12) ◽  
pp. 250 ◽  
Author(s):  
Yahui Li ◽  
Yang Li
Keyword(s):  
Decision Analysis ◽  
Evolutionary Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Decision Makers ◽  
Pareto Optimal ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Optimal Power ◽  
Knee Point

To coordinate the economy, security and environment protection in the power system operation, a two-step many-objective optimal power flow (MaOPF) solution method is proposed. In step 1, it is the first time that knee point-driven evolutionary algorithm (KnEA) is introduced to address the MaOPF problem, and thereby the Pareto-optimal solutions can be obtained. In step 2, an integrated decision analysis technique is utilized to provide decision makers with decision supports by combining fuzzy c-means (FCM) clustering and grey relational projection (GRP) method together. In this way, the best compromise solutions (BCSs) that represent decision makers’ different, even conflicting, preferences can be automatically determined from the set of Pareto-optimal solutions. The primary contribution of the proposal is the innovative application of many-objective optimization together with decision analysis for addressing MaOPF problems. Through examining the two-step method via the IEEE 118-bus system and the real-world Hebei provincial power system, it is verified that our approach is suitable for addressing the MaOPF problem of power systems.

Individual Blade Pitch Control for Alleviation of Vibratory Loads on Floating Offshore Wind Turbines

2021 ◽  
Author(s):  
Luca Pustina ◽  
Claudio Pasquali ◽  
Jacopo Serafini ◽  
Claudio Lugni ◽  
Massimo Gennaretti
Keyword(s):  
Renewable Energy ◽  
Wind Turbine ◽  
Bending Moment ◽  
Offshore Wind ◽  
Synthesis Process ◽  
Control Synthesis ◽  
Offshore Wind Turbine ◽  
Floating Offshore Wind Turbine ◽  
Blade Root ◽  
Floating Offshore Wind Turbines

Abstract Among the renewable energy technologies, offshore wind energy is expected to provide a significant contribution for the achievement of the European Renewable Energy (RE) targets for the next future. In this framework, the increase of generated power combined with the alleviation of vibratory loads achieved by application of suitable advanced control systems can lead to a beneficial LCOE (Levelized Cost Of Energy) reduction. This paper defines a control strategy for increasing floating offshore wind turbine lifetime through the reduction of vibratory blade and hub loads. To this purpose a Proportional-Integral (PI) controller based on measured blade-root bending moment feedback provides the blade cyclic pitch to be actuated. The proportional and integral gain matrices are determined by an optimization procedure whose objective is the alleviation of the vibratory loads due to a wind distributed linearly on the rotor disc. This control synthesis process relies on a linear, state-space, reduced-order model of the floating offshore wind turbine derived from aero-hydroelastic simulations provided by the open-source tool OpenFAST. In addition to the validation of the proposed controller, the numerical investigation based on OpenFAST predictions examines also the corresponding control effort, influence on platform dynamics and expected blade lifetime extension. The outcomes show that, as a by-product of the alleviation of the vibratory out-of-plane bending moment at the blade root, significant reductions of both cumulative blade lifetime damage and sway and roll platform motion are achieved, as well. The maximum required control power is less than 1% of the generated power.

Solving Environmental/Economic Dispatch Problem

2010 ◽  
pp. 123-145
Author(s):  
M.A. Abido
Keyword(s):  
Environmental Economic ◽  
Economic Dispatch ◽  
Test System ◽  
Standard Test ◽  
Pareto Optimal ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Swarm Optimization ◽  
Nondominated Solutions ◽  
Multiobjective Particle Swarm Optimization

Multiobjective particle swarm optimization (MOPSO) technique for environmental/economic dispatch (EED) problem is proposed and presented in this work. The proposed MOPSO technique evolves a multiobjective version of PSO by proposing redefinition of global best and local best individuals in multiobjective optimization domain. The proposed MOPSO technique has been implemented to solve the EED problem with competing and non-commensurable cost and emission objectives. Several optimization runs of the proposed approach have been carried out on a standard test system. The results demonstrate the capabilities of the proposed MOPSO technique to generate a set of well-distributed Pareto-optimal solutions in one single run. The comparison with the different reported techniques demonstrates the superiority of the proposed MOPSO in terms of the diversity of the Pareto optimal solutions obtained. In addition, a quality measure to Pareto optimal solutions has been implemented where the results confirm the potential of the proposed MOPSO technique to solve the multiobjective EED problem and produce high quality nondominated solutions.

Sign in / Sign up

Export Citation Format

Share Document