Multi-objective optimization of the airfoil shape of Wells turbine used for wave energy conversion

Wells turbine is one of the technical systems allowing an efficient use of the power contained in oceans’ and seas’ waves with a relatively low investment level. It converts the pneumatic power of the air stream induced by an Oscillating Water Column into mechanical energy. The standard Wells turbines show several well-known disadvantages: low tangential force, leading to low power output from the turbine; high undesired axial force; usually a low aerodynamic efficiency and a limited range of operation due to stall. In the present work an optimization process is employed in order to increase the tangential force induced by a monoplane Wells turbine using symmetric airfoil blades. The automatic optimization procedure is carried out by coupling an in-house optimization library (OPAL (OPtimization ALgorithms)) with an industrial CFD (Computational Fluid Dynamics) code (ANSYS-Fluent). This multi-objective optimization relying on Evolutionary Algorithms takes into account both tangential force coefficient and turbine efficiency. Detailed comparisons are finally presented between the optimal design and the classical Wells turbine using symmetric airfoils, demonstrating the superiority of the proposed solution. The optimization of the airfoil shape leads to a considerably increased power output (average relative gain of +11.3%) and simultaneously to an increase of efficiency (+1%) throughout the full operating range.     

Near-wake characteristics of a model horizontal axis tidal stream turbine

The results of a detailed experimental investigation of the near-wake (up to seven turbine diameters downstream) of a model horizontal axis tidal turbine (HATT) device in a large-scale recirculating water channel facility are reported. An Acoustic Doppler Velocimeter is used to provide detailed three-dimensional mean and turbulent flow field information at five different depths across the full width of the channel downstream of the turbine, giving the most complete three-dimensional velocities and Reynolds normal and shear stress data set yet available. In addition the Reynolds-stress anisotropy tensor is used to illustrate the degree of anisotropy of the Reynolds stress within the turbine's wake. These results reveal the strongly anisotropic nature of the near-wake turbulence suggesting isotropic turbulence models should not be used to model near-wake dynamics. Finally the power-law decay rates of the maximum normalised turbulent kinetic energy differ significantly from those found downstream of grids, meshes or perforated disks, suggesting that previous modelling approaches, which neglected swirl effects and modelled the turbine by absorption discs, may significantly over predict the turbulent kinetic energy decay rate of HATT wakes.     

Kinetic energy extraction of a tidal stream turbine and its sensitivity to structural stiffness attenuation

The hydrodynamic forces imparted on a tidal turbine rotor, whilst causing it to rotate and hence generate power, will also cause the blades to deform. This deformation will affect the turbine's performance if not included in the early design phase and could lead to a decrease in power output and a reduction in operational life. Conversely, designing blades to allow them to deform slightly may reduce localised stress and therefore prolong the life of the blades and allow the blades to deform in to their optimum operational state. The aim of this paper is to better understand the kinetic energy extraction by varying the material modulus of a turbine blade. Shaft torque/power, blade tip displacement, and axial thrust results are presented for 2, 3 and 4 bladed rotor configurations at peak power extraction. For the rotor design studied the FSI model data show that there is a low sensitivity to blade deformation for the 2, 3 and 4 bladed rotors. However, the results reveal that the 3 bladed rotor displayed maximum hydrodynamic performance as a rigid structure which then decreased as the blade deformed. The 2 and 4 bladed rotor configurations elucidated a slight increase in hydrodynamic performance with deflection.     

Multi-objective approach in thermoenvironomic optimization of a benchmark cogeneration system

Multi-objective optimization for designing of a benchmark cogeneration system known as CGAM cogeneration system has been performed. In optimization approach, the exergetic, economic and environmental aspects have been considered, simultaneously. The thermodynamic modeling has been implemented comprehensively while economic analysis conducted in accordance with the total revenue requirement (TRR) method. The results for the single objective thermoeconomic optimization have been compared with the previous studies in optimization of CGAM problem. In multi-objective optimization of the CGAM problem, the three objective functions including the exergetic efficiency, total levelized cost rate of the system product and the cost rate of environmental impact have been considered. The environmental impact objective function has been defined and expressed in cost terms. This objective has been integrated with the thermoeconomic objective to form a new unique objective function known as a thermoenvironomic objective function. The thermoenvironomic objective has been minimized while the exergetic objective has been maximized. One of the most suitable optimization techniques developed using a particular class of search algorithms known as multi-objective evolutionary algorithms (MOEAs) has been considered here. This approach which is developed based on the genetic algorithm has been applied to find the set of Pareto optimal solutions with respect to the aforementioned objective functions. An example of decision-making has been presented and a final optimal solution has been introduced. The sensitivity of the solutions to the interest rate and the fuel cost has been studied.     

Multi-objective optimization of a multi water-to-water heat pump system using evolutionary algorithm

This paper deals with the energy recovery in the dairy industry. Thermodynamic, economic and environmental optimization of three water-to-water heat pumps has been studied in order to replace totally or partially a fuel boiler used to produce heat at different temperature levels in a cheese factory. These heat pumps have their evaporators connected to one effluents source and two of them are equipped by storage tanks at the condenser side. Multi-objective optimization permits optimal repartition of mass flow rates of effluents and optimal choice of electrical power of the compressors and volumes of storage tanks. The thermodynamic objective is based on the exergy destruction in the whole system. The economic objective is based on the investment cost and the operating cost obtained with the heat pump system. The environmental impact objective has been defined and expressed in cost terms by considering a CO₂ taxation (carbon tax) on the GHG emissions. This objective has been integrated with the economic objective. Multi-objective genetic algorithms are used for Pareto approach optimization.     

Design and optimization of a non-TEMA type tubular recuperative heat exchanger used in a regenerative gas turbine cycle

A special non-TEMA type tubular recuperative heat exchanger used as a regenerator of a gas turbine cycle is considered for multi-criteria optimization. It is assumed that the recuperator is designed for an existing gas turbine cycle to be retrofitted. Three scenarios for optimization of the proposed system have been considered. In one scenario, the objective is minimizing the cost of recuperator; while in another scenario maximizing the cycle exergetic efficiency is considered. In third scenario, both objectives are optimized simultaneously in a multi-objective optimization approach. Geometric specification of the recuperator including tubes length, tubes outside/inside diameters, tube pitch in the tube bundle, inside shell diameter, outer and inner tube limits of the tube bundle and the total number of disc and doughnut baffles are considered as decision variables. Combination of these objectives and decision variables with suitable engineering and physical constraints (including NO_x and CO emission limitations) makes a set of MINLP optimization problem. Optimization programming in MATLAB is performed using one of the most powerful and robust multi-objective optimization algorithms namely NSGA-II. This approach which is based on the Genetic Algorithm is applied to find a set of Pareto optimal solutions. Pareto optimal frontier is obtained and a final optimal solution is selected in a decision-making process. It is shown that the multi-objective optimization scenario can be considered as a generalized optimization approach in which balances between economical viewpoints of both heat exchanger manufacturer and end user of recuperator.     

Multi-objective design optimization of a natural gas-combined cycle with carbon dioxide capture in a life cycle perspective

The use of multi-objective optimization techniques is attractive to incorporate environmental objectives into the design of energy conversion systems. A method to locally optimize a given process while considering its global environmental impact by using life cycle assessment (LCA) to account for avoidable and unavoidable off-site emissions for each independent material input is presented. It is applied to study the integration of a CO₂-capture process using monoethanolamine in a natural gas-combined cycle power plant, simultaneously optimizing column dimensions, heat exchange, and absorbent flow configuration with respect to two objectives: the levelized cost of electricity and its life cycle global-warming potential. The model combines a process flow-sheeting model and a separate process-integration model. After optimization using an evolutionary algorithm, the results showed that widening the absorber and generating near-atmospheric pressure steam are cost-effective options but that increasing stripper complexity is less so. With $7.80/GJ natural gas and $20/ton CO₂ handling, the minimum on-site CO₂ abatement cost reaches $62.43/ton on a life cycle basis, achieved with a capture rate of over 90%. Of this, $2.13/ton is related to off-site emissions – a specific advantage of LCA that could help industries and governments anticipate the actual future costs of CO₂ capture.     

Multi-objective optimization of a joule cycle for re-liquefaction of the Liquefied Natural Gas

A LNG re-liquefaction plant is optimized with a multi-objective approach which simultaneously considers exergetic and exergoeconomic objectives. In this regard, optimization is performed in order to maximize the exergetic efficiency of plant and minimize the unit cost of the system product (refrigeration effect), simultaneously. Thermodynamic modeling is performed based on energy and exergy analyses, while an exergoeconomic model based on the total revenue requirement (TRR) are developed. Optimization programming in MATLAB is performed using one of the most powerful and robust multi-objective optimization algorithms namely NSGA-II. This approach which is based on the Genetic Algorithm is applied to find a set of Pareto optimal solutions. Pareto optimal frontier is obtained and a final optimal solution is selected in a decision-making process. An example of decision-making process for selection of the final solution from the available optimal points of the Pareto frontier is presented here. The feature of selected final optimal system is compared with corresponding features of the base case and exergoeconomic single-objective optimized systems and discussed.     

新型变桨风力机结构设计与性能分析

为满足分布式电网发展要求,提高小型风力机风能利用率,防止大风条件损坏风力发电设备,文章设计了一种应用于小型风力机的新型主动统一变桨调节装置。文章介绍了装置的基本构造与工作原理,利用熔融沉积3D打印技术制作小比例模型验证了变桨装置的可行性,并通过数值模拟方法对功率输出性能及风轮载荷进行了模拟分析。模拟结果表明:通过适当调节桨距角大小,可有效控制风力机输出功率保持在额定功率值附近,且高转速条件下增大桨距角对功率输出性能有较强抑制作用;叶片应力集中区域主要在叶根及叶片中部靠近前缘部位,在功率调控过程中,随着桨距角与风速的增加,应力集中区域由叶中向叶根转移,最大应力值总体呈下降趋势。     

Multi-objective optimization of a hydrogen production through the HyS process powered by solar energy in different scenarios

Thermochemical or hybrid cycles powered by concentrated solar energy are a very promising way to produce an effective clean hydrogen through the water splitting, in terms of greenhouse gas (GHG) emissions and power production sustainability. SOL2HY2 is an European project focused on this goal. It deepens the so-called HyS process in a closed or partially open version using a proper SO₂ depolarized electrolyser, and moreover, it investigates key materials and process solutions, along the entire production chain. However, the identification of the best solution to obtain a suitable hydrogen in terms of cost, efficiency, availability of energy and material, sharing of renewable energy source, continuity of operation in different locations and plant sizes, poses many challenges in terms of flexibility and complexity of the system. In fact, it involves various chemical equipment, different solar and thermal storage technologies, and variable operative conditions with different reaction temperatures and mixture concentrations. Hence it arises the importance to have a tool for the investigation of this system.In this paper, data analysis and multi-objective techniques are used to study and optimize the process under consideration. Several mathematical methods have been exploited to make the best use of the available data, such as Design of Experiments techniques, meta-modeling strategies and genetic algorithms. All these methods have been implemented in the open source environments Scilab and R.     

Influence of blade deformation and yawed inflow on performance of a horizontal axis tidal stream turbine

For a better design of tidal stream turbines operated in off-design conditions, analyses considering the effects of blade deformation and yawed inflow conditions are necessary. The flow load causes deformation of the blade, and the deformation affects the turbine performance in return. Also, a yawed inflow influences the performance of the turbine. As a validation study, a computational fluid dynamics (CFD) simulation was carried out to predict the performance of a horizontal axis tidal stream turbine (HATST) with rigid blades. The numerical uncertainty for the turbine performance with blade deformation and a yawed inflow was evaluated using the concept of the grid convergence index (GCI). A fluid–structure interaction (FSI) analysis was carried out to estimate the performance of a turbine with flexible composite blades, with the results then compared to those of an analysis with rigid blades. The influence of yawed inflow conditions on the turbine performance was investigated and found to be important in relation to power predictions in the design stages.     

Numerical analysis of 3-D unsteady flow in a vaneless counter-rotating turbine

To reveal the unsteady flow characteristics of a vaneless counter-rotating turbine (VCRT), a three-dimensional, viscous, unsteady computational fluid dynamics (CFD) analysis was performed. The results show that unsteady simulation is superior to steady simulation because more flow characteristics can be obtained. The unsteady effects in upstream airfoil rows are weaker than those in downstream airfoil rows in the VCRT. The static pressure distribution along the span in the pressure surface of a high pressure turbine stator is more uniform than that in the suction surface. The static pressure distributions along the span in the pressure surfaces and the suction surfaces of a high pressure turbine rotor and a low pressure turbine rotor are all uneven. The numerical results also indicate that the load of a high pressure turbine rotor will increase with the increase of the span. The deviation is very big between the direction of air flow at the outlet of a high pressure turbine rotor and the axial direction. A similar result can also be obtained in the outlet of a low pressure turbine rotor. This means that the specific work of a high pressure turbine rotor and a low pressure turbine rotor is big enough to reach the design objectives. Translated from Journal of Engineering Thermophysics, 2006, 27(1): 35–38 [译自: 工程热物理学报]     

Multi-objective opportunistic maintenance optimization of a wind farm considering limited number of maintenance groups

Several different models provided by researchers to maintain a wind turbine, but most of these models only focused on the case involved a single objective optimization problem. In practice, real cases of wind farms lead to multi-objective approach to optimize maintenance efforts. In this paper, based on an opportunistic approach, a multi-objective based model is proposed to optimize the maintenance of a farm involved several different types of wind turbines. The assumptions of stochastic behavior of wind velocity as well as the existence of a limited number for maintenance groups are also considered in this new approach. The proposed model considering imperfect maintenance, attempts (1) maximizing the expected rate of energy and (2) minimizing the total expected costs related to maintenance efforts. The opportunistic approach is also provided by the component's reliability threshold values. The comparative analysis addresses that the capability of the proposed model is more efficient compared to models addressed in literature.     

Numerical simulation on effect of pressure distribution of wind turbine blade with a tip vane

It is important to study the pressure distribution on the blade and in the adjacent area while searching the power augmentation theory with adding a tip vane to the wind turbine. This paper shows the CFD simulation relationship of the pressure distribution on the rotor blade and in the adjacent area, after calculating the pressure of the different chordwise and spanwise point on the blade with the tip vane-V(8.8×8) and without the tip vane under tip speed ratio λ 4.5. Combining the isobaric section figure in certain location, it can be seen that the tip vane improve the pressure difference between pressure and suction surface. The most influenced zone is found and these can further display the power augmentation theory of the wind turbine using the tip vane. The simulation calculation was based on N-S equations. 3-D, steady, implicit solver was chosen. Turbulence model was k-ω SST. Discretization scheme is SECOND ORDER UPWIND. Pressure-velocity coupling was a typical SIMPLE scheme. In the whole grid system, two-divided grid formation was adopted, that is, inner region and outer region. Inner region including rectangular solid blade and neighboring, outer region is semi-cylinder. There were together 720,000 nodes with tetra-prism unstructured mesh.     

Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects

Along with the continuing global warming, the environmental constraints are expected to play more and more important role in the operation of distributed energy resource (DER) systems, besides the economic objective. In this study, a multi-objective optimization model is developed to analyze the optimal operating strategy of a DER system while combining the minimization of energy cost with the minimization of environmental impact which is assessed in terms of CO₂ emissions. The trade-off curve is obtained by using the compromise programming method. As an illustrative example, the DER system installed in an eco-campus in Japan has been selected for case study. The distributed technologies under consideration include photovoltaics (PV), fuel cell and gas engine for providing electrical and thermal demands. The obtained results demonstrate that increasing the satisfaction degree of economic objective leads to increased CO₂ emissions. The operation of the DER system is more sensitive when environmental objective is paid more attention. Moreover, according to the sensitivity analysis, the consideration of electricity buy-back, carbon tax, as well as fuel switching to biogas, has more or less effect on the operation of DER systems.     

Multi-objective optimization of the engine performance and emissions for a hydrogen/gasoline dual-fuel engine equipped with the port water injection system

Hydrogen is one of the most promising options being considered as the fuel of future. However, injection of hydrogen into modern gasoline fueled engines can cause some issues such as power loss. This study, therefore, aims to address this challenge in a simulated hydrogen/gasoline dual-fueled engine by developing a novel and innovative approach without possible side effects such as NOx increment. To achieve this goal, the impacts of water injection and the start of the combustion (SOC) modification in a gasoline/hydrogen duel fueled engine have been rigorously investigated. In current methodology, an engine is simulated using AVL BOOST software and the model is validated against the experimental data. The Latin Hypercube design of experiments method was employed to determine the design points in 3-dimensional space. Due to the existing trade-off between NOx and BMEP, multi-objective optimization using genetic algorithm (GA) was implemented to determine the optimum values of water injection and SOC in various hydrogen energy shares and the effects of optimum design parameters on the main engine performance and emission parameters were investigated. The results showed that the proposed solution could recover the brake mean effective pressure (BMEP) and in some hydrogen energy shares even increase it above the level of single fueled gasoline engine with the added benefit of there being no increase in NOx compared to the original level. Furthermore, other emissions and engine performance parameters are improved including the engine equivalent Brake specific fuel consumption (BSFC) which was shown to increased up to 4.61%.     

Multi-objective optimization of the hybrid wind/solar/fuel cell distributed generation system using Hammersley Sequence Sampling

As the development of China's economy, environmental problems in China become more and more serious. Solar energy and wind energy are considered as ones of the best choices to solve the environmental problems in China and the hybrid wind/solar distributed generation (DG) system has received increasing attention recently. However, the instability and intermittency of the wind and solar energy throw a huge challenge on designing of the hybrid system. In order to ensure the continuous and stable power supply, optimal unit sizing of the hybrid wind/solar DG system should be taken into consideration in the design of the hybrid system. This paper establishes a multi-objective optimization framework based on cost, electricity efficiency and energy supply reliability models of the hybrid DG system, which is composed of wind, solar and fuel cell generation systems. Detailed models of each unit for the hybrid wind/solar/fuel cell system were established. Advanced ε-constraints method based on Hammersley Sequence Sampling was employed in the multi-objective optimization of the hybrid DG system. The approximate Pareto surface of the multi-objective optimization problems with a range of possible design solutions and a logical procedure for searching the global optimum solution for decision makers were presented. In this way, this work provided an efficient method for decision makers in the design of the hybrid wind/solar/fuel cell system.     

Aerodynamic optimization of wind turbine rotors using a blade element momentum method with corrections for wake rotation and expansion

The blade element momentum (BEM) method is widely used for calculating the quasi‐steady aerodynamics of horizontal axis wind turbines. Recently, the BEM method has been expanded to include corrections for wake expansion and the pressure due to wake rotation (), and more accurate solutions can now be obtained in the blade root and tip sections. It is expected that this will lead to small changes in optimum blade designs. In this work, has been implemented, and the spanwise load distribution has been optimized to find the highest possible power production. For comparison, optimizations have been carried out using BEM as well. Validation of shows good agreement with the flow calculated using an advanced actuator disk method. The maximum power was found at a tip speed ratio of 7 using , and this is lower than the optimum tip speed ratio of 8 found for BEM. The difference is primarily caused by the positive effect of wake rotation, which locally causes the efficiency to exceed the Betz limit. Wake expansion has a negative effect, which is most important at high tip speed ratios. It was further found that by using , it is possible to obtain a 5% reduction in flap bending moment when compared with BEM. In short, allows fast aerodynamic calculations and optimizations with a much higher degree of accuracy than the traditional BEM model. Copyright © 2011 John Wiley & Sons, Ltd.     

Tidal farm analysis using an analytical model for the flow velocity prediction in the wake of a tidal turbine with small diameter to depth ratio

A tidal turbine is a device converting hydrodynamic power into electrical power. Lately, more and more projects have been developed in order to optimize the productivity of this kind of energy. In such research with industrial interest, under the impact of the wake effect on the output power, the analysis of a tidal farm layout is regarded as the first priority. Simple approaches such as those developed for wind farms could be used in tidal turbine arrangement optimization. These methodologies can be improved by taking into account the turbulence in tidal farms and tidal turbines' mechanical characteristics. The goal of this work is to propose a predictive analytical model to estimate the tidal speed in the far wake of tidal turbines with small diameter to depth ratio (20% here). It is a first step prior to integrate the wake model in a tidal farm layout optimization algorithm. The wake model development is achieved reanalyzing the far wake's equations used in wind farm applications. A turbine represented by an Actuator Disc (AD) in conjunction with a Computational Fluid Dynamics (CFD) numerical model is used as a reference for this purpose. The CFD-AD model has been validated with experimental results from literature. The novelty of the present work consists in expressing the far wake's radius expansion as a function of the ambient turbulence and the thrust coefficient. The proposed equation is used in conjunction with the Jensen's model in a manner that the velocities downstream a tidal turbine can be estimated. The velocity distribution in the far wake of a single turbine obtained by the proposed model is in good agreement with the CFD numerical model. As a matter of fact, the model provides satisfactory accuracy in the cases of two parks: one with five aligned turbines and one with ten staggered turbines.