scholarly journals Automatic Blade Shape Optimization of a Three-Bladed Modified Savonius Turbine

2022 ◽  
Vol 9 ◽  
Author(s):  
Mohamed H. Mohamed ◽  
Faris Alqurashi ◽  
Dominique Thévenin
Keyword(s):  
Optimization Technique ◽  
Optimal Solution ◽  
Optimal Configuration ◽  
Power Coefficient ◽  
Cylindrical Shape ◽  
Ansys Fluent ◽  
Optimization Study ◽  
Blade Shape ◽  
Regular Design ◽  
Turbine Design

In this study, the performance of a new wind turbine design derived from a conventional Savonius turbine is optimized by numerical simulation. The new design consists of three blades without passage between them (closed center). The coupling between the CFD codes (ANSYS Fluent) and the optimizer (OPAL) is used through an automatic procedure in-house codes, as documented, for example, in Thévenin et al.’s Optimization and Computational Fluid Dynamics (2008). A single-objective function (output power coefficient, Cp) is considered as the target of the optimization technique and the shape of the blade as an optimization parameter and relies on evolutionary algorithms. An optimal solution can emerge from this optimization study. By comparison between regular design (semi-cylindrical shape blades) and the optimal configuration, a considerable improvement (up to 7.13% at λ = 0.7) of the optimal configuration performance can be obtained in this manner.

A Numerical Investigation to Study Effects of a Savonius Rotor’s Plate Shape on its Optimum Overlap Ratio

2012 ◽  
Author(s):  
Morteza Abbaszadeh ◽  
Fariba Bagherzadeh ◽  
Mina Iravani
Keyword(s):  
Design Method ◽  
Power Coefficient ◽  
Ansys Fluent ◽  
Wide Range ◽  
Blade Shape ◽  
Plate Shape ◽  
Commercial Software Package ◽  
Overlap Ratio ◽  
The Relationship ◽  
Novel Design

Present study is aimed to investigate the relationship between blade shape of Savonius rotor and its optimum overlap, an important parameter that can improve the rotor’s performance superbly. To set a relation between rotor’s shape and its overlap, a new parameter called “trailing angle” was introduced in this study and by a novel design method, several models were designed to represent a wide range of trailing angles. The investigation has been carried out by using Reynolds Stress Method (RSM) through ANSYS Fluent commercial software package. The application of the method was validated by comparing the results of a conventional model with experimental data acquired from one of the references. Results of this study have proved that optimum overlap ratio is associated with blades’ trailing angle and by increasing the trailing angle, optimum overlap would decrease. The results also demonstrate that by application of a proper overlap ratio, power coefficient of the rotor would increase by nearly 22 percent.

Well Placement Technique and Production Optimization for Mature Field - A Case Study of L-X Field

2020 ◽  
Vol 46 ◽  
pp. 168-179
Author(s):  
Patrick Nwafor ◽  
Kelani Bello
Keyword(s):  
Oil And Gas ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Oil And Gas Industry ◽  
Optimization Method ◽  
Simulation Software ◽  
Production Optimization ◽  
Direct Optimization ◽  
Well Placement ◽  
Local Optimal Solution

A Well placement is a well-known technique in the oil and gas industry for production optimization and are generally classified into local and global methods. The use of simulation software often deployed under the direct optimization technique called global method. The production optimization of L-X field which is at primary recovery stage having five producing wells was the focus of this work. The attempt was to optimize L-X field using a well placement technique.The local methods are generally very efficient and require only a few forward simulations but can get stuck in a local optimal solution. The global methods avoid this problem but require many forward simulations. With the availability of simulator software, such problem can be reduced thus using the direct optimization method. After optimization an increase in recovery factor of over 20% was achieved. The results provided an improvement when compared with other existing methods from the literatures.

Application of UPFC for enhancement of voltage profile and minimization of losses using Fast Voltage Stability Index (FVSI)

2012 ◽  
Vol 61 (2) ◽  
pp. 239-250 ◽  
Author(s):  
M. Kumar ◽  
P. Renuga
Keyword(s):  
Power System ◽  
Voltage Stability ◽  
Reactive Power ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Stability Index ◽  
Test System ◽  
Unified Power Flow Controller ◽  
Voltage Profile ◽  
Voltage Stability Index

Application of UPFC for enhancement of voltage profile and minimization of losses using Fast Voltage Stability Index (FVSI)Transmission line loss minimization in a power system is an important research issue and it can be achieved by means of reactive power compensation. The unscheduled increment of load in a power system has driven the system to experience stressed conditions. This phenomenon has also led to voltage profile depreciation below the acceptable secure limit. The significance and use of Flexible AC Transmission System (FACTS) devices and capacitor placement is in order to alleviate the voltage profile decay problem. The optimal value of compensating devices requires proper optimization technique, able to search the optimal solution with less computational burden. This paper presents a technique to provide simultaneous or individual controls of basic system parameter like transmission voltage, impedance and phase angle, thereby controlling the transmitted power using Unified Power Flow Controller (UPFC) based on Bacterial Foraging (BF) algorithm. Voltage stability level of the system is defined on the Fast Voltage Stability Index (FVSI) of the lines. The IEEE 14-bus system is used as the test system to demonstrate the applicability and efficiency of the proposed system. The test result showed that the location of UPFC improves the voltage profile and also minimize the real power loss.

Performance study of twisted Darrieus hydrokinetic turbine with novel blade design

2021 ◽  
pp. 1-37
Author(s):  
Mabrouk Mosbahi ◽  
Mouna Derbel ◽  
Mariem Lajnef ◽  
Bouzid Mosbahi ◽  
Zied Driss ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Maximum Power ◽  
Power Coefficient ◽  
Speed Ratio ◽  
Small Scale ◽  
Performance Study ◽  
Hydrokinetic Turbine ◽  
Blade Shape ◽  
Water Turbine ◽  
Water Canals

Abstract Twisted Darrieus water turbine is receiving growing attentiveness for small-scale hydropower generation. Accordingly, the need for raised water energy conversion incentivizes researchers to focalise on the blade shape optimization of twisted Darrieus turbine. In view of this, an experimental analysis has been performed to appraise the efficiency of a spiral Darrieus water rotor in the present work. To better the performance parameters of the studied water rotor with twisted blades, three novel blade shapes, namely U-shaped blade, V-shaped blade and W-shaped blade, have been numerically tested using a computational fluid dynamics three-dimensional numerical model. Maximum power coefficient of Darrieus rotor reaches 0.17 at 0.63 tip-speed ratio using twisted blades. Using V-shaped blades, maximum power coefficient has been risen up to 0.185. The current study could be practically applied to provide more effective employment of twisted Darrieus turbines and to improve the generated power from flowing water such as river streams, tidal currents, or other man made water canals.

Towards Intelligent Road Traffic Management over Weighted Large Graphs Hybrid Meta-heuristic-Based Approach

2022 ◽  
Vol 24 (3) ◽  
pp. 0-0
Keyword(s):  
Traffic Management ◽  
Large Scale ◽  
Road Traffic ◽  
Optimization Technique ◽  
Shortest Paths ◽  
Hybrid Genetic Algorithm ◽  
Optimal Solution ◽  
Computation Time ◽  
Exact Algorithm ◽  
On The Road

This paper introduces a new approach of hybrid meta-heuristics based optimization technique for decreasing the computation time of the shortest paths algorithm. The problem of finding the shortest paths is a combinatorial optimization problem which has been well studied from various fields. The number of vehicles on the road has increased incredibly. Therefore, traffic management has become a major problem. We study the traffic network in large scale routing problems as a field of application. The meta-heuristic we propose introduces new hybrid genetic algorithm named IOGA. The problem consists of finding the k optimal paths that minimizes a metric such as distance, time, etc. Testing was performed using an exact algorithm and meta-heuristic algorithm on random generated network instances. Experimental analyses demonstrate the efficiency of our proposed approach in terms of runtime and quality of the result. Empirical results obtained show that the proposed algorithm outperforms some of the existing technique in term of the optimal solution in every generation.

Computational fluid dynamic analysis of roof-mounted vertical-axis wind turbine with diffuser shroud, flange, and vanes

2018 ◽  
Vol 42 (4) ◽  
pp. 404-415
Author(s):  
H. Abu-Thuraia ◽  
C. Aygun ◽  
M. Paraschivoiu ◽  
M.A. Allard
Keyword(s):  
Wind Turbine ◽  
Urban Areas ◽  
Guide Vane ◽  
Fluid Dynamic ◽  
Vertical Axis ◽  
Power Coefficient ◽  
Small Scale ◽  
Vertical Axis Wind Turbine ◽  
Guide Vanes ◽  
Turbine Design

Advances in wind power and tidal power have matured considerably to offer clean and sustainable energy alternatives. Nevertheless, distributed small-scale energy production from wind in urban areas has been disappointing because of very low efficiencies of the turbines. A novel wind turbine design — a seven-bladed Savonius vertical-axis wind turbine (VAWT) that is horizontally oriented inside a diffuser shroud and mounted on top of a building — has been shown to overcome the drawback of low efficiency. The objective this study was to analyze the performance of this novel wind turbine design for different wind directions and for different guide vanes placed at the entrance of the diffuser shroud. The flow field over the turbine and guide vanes was analyzed using computational fluid dynamics (CFD) on a 3D grid for multiple tip-speed ratios (TSRs). Four wind directions and three guide-vane angles were analyzed. The wind-direction analysis indicates that the power coefficient decreases to about half when the wind is oriented at 45° to the main axis of the turbine. The analysis of the guide vanes indicates a maximum power coefficient of 0.33 at a vane angle of 55°.

Performance Evaluation of Population Seeding Techniques of Permutation-Coded GA Traveling Salesman Problems Based Assessment

2021 ◽  
pp. 1074-1115
Author(s):  
Victer Paul ◽  
Ganeshkumar C ◽  
Jayakumar L
Keyword(s):  
Genetic Algorithms ◽  
Nearest Neighbor ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Computation Time ◽  
Search Space ◽  
Population Based ◽  
Vital Role ◽  
Traveling Salesman ◽  
Performance Criteria

Genetic algorithms (GAs) are a population-based meta-heuristic global optimization technique for dealing with complex problems with a very large search space. The population initialization is a crucial task in GAs because it plays a vital role in the convergence speed, problem search space exploration, and also the quality of the final optimal solution. Though the importance of deciding problem-specific population initialization in GA is widely recognized, it is hardly addressed in the literature. In this article, different population seeding techniques for permutation-coded genetic algorithms such as random, nearest neighbor (NN), gene bank (GB), sorted population (SP), and selective initialization (SI), along with three newly proposed ordered-distance-vector-based initialization techniques have been extensively studied. The ability of each population seeding technique has been examined in terms of a set of performance criteria, such as computation time, convergence rate, error rate, average convergence, convergence diversity, nearest-neighbor ratio, average distinct solutions and distribution of individuals. One of the famous combinatorial hard problems of the traveling salesman problem (TSP) is being chosen as the testbed and the experiments are performed on large-sized benchmark TSP instances obtained from standard TSPLIB. The scope of the experiments in this article is limited to the initialization phase of the GA and this restricted scope helps to assess the performance of the population seeding techniques in their intended phase alone. The experimentation analyses are carried out using statistical tools to claim the unique performance characteristic of each population seeding techniques and best performing techniques are identified based on the assessment criteria defined and the nature of the application.

scholarly journals Robust Approximate Optimality Conditions for Uncertain Nonsmooth Optimization with Infinite Number of Constraints

Mathematics ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 12 ◽  
Author(s):  
Xiangkai Sun ◽  
Hongyong Fu ◽  
Jing Zeng
Keyword(s):  
Optimality Conditions ◽  
Optimization Problem ◽  
Constraint Qualification ◽  
Optimization Problems ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Sufficient Optimality Conditions ◽  
Convex Constraint ◽  
Approximate Optimality Conditions ◽  
Necessary And Sufficient

This paper deals with robust quasi approximate optimal solutions for a nonsmooth semi-infinite optimization problems with uncertainty data. By virtue of the epigraphs of the conjugates of the constraint functions, we first introduce a robust type closed convex constraint qualification. Then, by using the robust type closed convex constraint qualification and robust optimization technique, we obtain some necessary and sufficient optimality conditions for robust quasi approximate optimal solution and exact optimal solution of this nonsmooth uncertain semi-infinite optimization problem. Moreover, the obtained results in this paper are applied to a nonsmooth uncertain optimization problem with cone constraints.

scholarly journals An Enhanced Partial Search to Particle Swarm Optimization for Unconstrained Optimization

Mathematics ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 357 ◽  
Author(s):  
Shu-Kai S. Fan ◽  
Chih-Hung Jen
Keyword(s):  
Particle Swarm Optimization ◽  
Unconstrained Optimization ◽  
Optimization Technique ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Pso Algorithm ◽  
Particle Swarm Optimizer ◽  
Swarm Optimization ◽  
Searching Strategy ◽  
Wide Range

Particle swarm optimization (PSO) is a population-based optimization technique that has been applied extensively to a wide range of engineering problems. This paper proposes a variation of the original PSO algorithm for unconstrained optimization, dubbed the enhanced partial search particle swarm optimizer (EPS-PSO), using the idea of cooperative multiple swarms in an attempt to improve the convergence and efficiency of the original PSO algorithm. The cooperative searching strategy is particularly devised to prevent the particles from being trapped into the local optimal solutions and tries to locate the global optimal solution efficiently. The effectiveness of the proposed algorithm is verified through the simulation study where the EPS-PSO algorithm is compared to a variety of exiting “cooperative” PSO algorithms in terms of noted benchmark functions.

Optimization of Smart Wells in the St. Joseph Field

2010 ◽  
Vol 13 (04) ◽  
pp. 588-595 ◽  
Author(s):  
G. M. van Essen ◽  
J. D. Jansen ◽  
D. R. Brouwer ◽  
S. G. Douma ◽  
M. J. Zandvliet ◽  
...  
Keyword(s):  
Optimization Technique ◽  
Gas Injection ◽  
Optimal Number ◽  
Control Parameters ◽  
Operational Strategies ◽  
Sector Model ◽  
Optimization Study ◽  
Smart Wells ◽  
Gradient Based ◽  
Reservoir Simulator

Summary The St. Joseph field has been on production since September 1981 under natural depletion supported by crestal gas injection. As part of a major redevelopment study, the scope for waterflooding was addressed using "smart" completions with multiple inflow control valves (ICVs) in the wells to be drilled for the redevelopment. Optimal control theory was used to optimize monetary value over the remaining producing life of the field, and in particular to select the optimal number of ICVs, the optimal configuration of the perforation zones, and the optimal operational strategies for the ICVs. A gradient-based optimization technique was implemented in a reservoir simulator equipped with the adjoint functionality to compute gradients of an objective function with respect to control parameters. For computational reasons, an initial optimization study was performed on a sector model, which showed promising results.

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