Optimizing the Unrestricted Placement of Turbines of Differing Rotor Diameters in a Wind Farm for Maximum Power Generation

2010 ◽  
Author(s):  
Souma Chowdhury ◽  
Achille Messac ◽  
Jie Zhang ◽  
Luciano Castillo ◽  
Jose Lebron
Keyword(s):  
Power Generation ◽  
Wind Farm ◽  
Pso Algorithm ◽  
Total Power ◽  
Wake Effect ◽  
Swarm Optimization ◽  
Wind Farm Layout Optimization ◽  
Farm Efficiency ◽  
Wake Model ◽  
Velocity Deficits

This paper presents a new method (the Unrestricted Wind Farm Layout Optimization (UWFLO)) of arranging turbines in a wind farm to achieve maximum farm efficiency. The powers generated by individual turbines in a wind farm are dependent on each other, due to velocity deficits created by the wake effect. A standard analytical wake model has been used to account for the mutual influences of the turbines in a wind farm. A variable induction factor, dependent on the approaching wind velocity, estimates the velocity deficit across each turbine. Optimization is performed using a constrained Particle Swarm Optimization (PSO) algorithm. The model is validated against experimental data from a wind tunnel experiment on a scaled down wind farm. Reasonable agreement between the model and experimental results is obtained. A preliminary wind farm cost analysis is also performed to explore the effect of using turbines with different rotor diameters on the total power generation. The use of differing rotor diameters is observed to play an important role in improving the overall efficiency of a wind farm.

scholarly journals Economic load dispatch solutions considering multiple fuels for thermal units and generation cost of wind turbines

2021 ◽  
Vol 11 (5) ◽  
pp. 3718
Author(s):  
Anh Tuan Doan ◽  
Dinh Thanh Viet ◽  
Minh Quan Duong
Keyword(s):  
Power Generation ◽  
Particle Swarm Optimization ◽  
Wind Farm ◽  
Particle Swarm ◽  
Wind Farms ◽  
Total Power ◽  
Economic Load Dispatch ◽  
Swarm Optimization ◽  
Generation Cost ◽  
Constriction Factor

In this paper, economic load dispatch (ELD) problem is solved by applying a suggested improved particle swarm optimization (IPSO) for reaching the lowest total power generation cost from wind farms (WFs) and thermal units (TUs). The suggested IPSO is the modified version of Particle swarm optimization (PSO) by changing velocity and position updates. The five best solutions are employed to replace the so-far best position of each particle in velocity update mechanism and the five best solutions are used to replace previous position of each particle in position update. In addition, constriction factor is also used in the suggested IPSO. PSO, constriction factor-based PSO (CFPSO) and bat optimization algorithm (BOA) are also run for comparisons. Two systems are used to run the four methods. The first system is comprised of nine TUs with multiple fuels and one wind farm. The second system is comprised of eight TUs with multiple fuels and two WFs. From the comparisons of results, IPSO is much more powerful than three others and it can find optimal power generation with the lowest total power generation cost.

scholarly journals Wind Farm Layout Optimization with Different Hub Heights in Manjil Wind Farm Using Particle Swarm Optimization

2021 ◽  
Vol 11 (20) ◽  
pp. 9746
Author(s):  
Menova Yeghikian ◽  
Abolfazl Ahmadi ◽  
Reza Dashti ◽  
Farbod Esmaeilion ◽  
Alireza Mahmoudan ◽  
...  
Keyword(s):  
Power Generation ◽  
Particle Swarm Optimization ◽  
Wind Turbines ◽  
Wind Farm ◽  
Particle Swarm ◽  
Primary Objective ◽  
Wake Effect ◽  
Optimal Arrangement ◽  
Swarm Optimization ◽  
Wind Farm Layout

Nowadays, optimizing wind farm configurations is one of the biggest concerns for energy communities. The ongoing investigations have so far helped increasing power generation and reducing corresponding costs. The primary objective of this study is to optimize a wind farm layout in Manjil, Iran. The optimization procedure aims to find the optimal arrangement of this wind farm and the best values for the hubs of its wind turbines. By considering wind regimes and geographic data of the considered area, and using the Jensen’s method, the wind turbine wake effect of the proposed configuration is simulated. The objective function in the optimization problem is set in such a way to find the optimal arrangement of the wind turbines as well as electricity generation costs, based on the Mossetti cost function, by implementing the particle swarm optimization (PSO) algorithm. The results reveal that optimizing the given wind farm leads to a 10.75% increase in power generation capacity and a 9.42% reduction in its corresponding cost.

scholarly journals Wind farm layout optimization to maximize total power production

2018 ◽  
Vol 57 ◽  
pp. 03005
Author(s):  
I Ulku ◽  
C Alabas-Uslu
Keyword(s):  
Energy Demand ◽  
Alternative Energy ◽  
Wind Farm ◽  
Energy Resource ◽  
Power Production ◽  
Total Power ◽  
Nonlinear Mathematical Model ◽  
Wake Effect ◽  
Wind Farm Layout Optimization ◽  
Wake Effects

With the rapid increase in energy demand, renewable energy has been considered as an alternative energy resource around the world. A new nonlinear mathematical model is developed in the presented study and a comparison is obtained with a mathematical modelling study from the literature. The results superior according to power generation under a single wind direction. Jensen’s wake decay model is used to state multiple wake effect among the turbines. The power production is maximized in terms of the minimization of wake effects. Mathematical formulations are represented and compared with the model from the literature. The generated layouts are presented and expected power among the Introduction turbines are significantly improved.

scholarly journals Comparisons of the accuracy of different wake models in wind farm layout optimization

2020 ◽  
Vol 38 (5) ◽  
pp. 1725-1741 ◽  
Author(s):  
Xiaoxia Gao ◽  
Yue Li ◽  
Fei Zhao ◽  
Haiying Sun
Keyword(s):  
Power Generation ◽  
Wind Farm ◽  
Layout Optimization ◽  
Wind Condition ◽  
Wind Farm Layout ◽  
Wind Farm Layout Optimization ◽  
Cost Of Energy ◽  
Generation Cost ◽  
Wake Model ◽  
Population Genetic Algorithm

Accurate wake model in wind farm layout optimization can help extracting maximum power generation, minimizing cost of energy and prolonging wind turbines’ lifetime as well. With the development of different wake models, the wind farm layout optimization results based on the models should be updated. This paper investigates the performances of four wake models in wind farm layout optimization using multi-population genetic algorithm (MPGA) with the wind farm power generation, COST/AEP and wind farm efficiency been reported. Comparison of results between typical wake models’ performance shows that Jensen’s wake model reported a higher wind farm power generation and efficiency because it underestimates the velocity deficit in the wake, and to the contrary, in the Frandsen wake model, the velocity in the wake is underestimated, resulting in a deceased power generation. The expression of 2D_k model shall be out of work in complicated wind condition. The 2D Jensen–Gaussian wake model performed better in the wind farm layout optimization using the MPGA program which can be promoted in real-world wind farm micrositing.

scholarly journals Analysis of Wind Turbine Aging through Operation Data Calibrated by LiDAR Measurement

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2319
Author(s):  
Hyun-Goo Kim ◽  
Jin-Young Kim
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Farm ◽  
Free Stream ◽  
Turbine Blades ◽  
Wind Farms ◽  
Lidar Measurement ◽  
Wind Turbine Blades ◽  
Wake Effect

This study analyzed the performance decline of wind turbine with age using the SCADA (Supervisory Control And Data Acquisition) data and the short-term in situ LiDAR (Light Detection and Ranging) measurements taken at the Shinan wind farm located on the coast of Bigeumdo Island in the southwestern sea of South Korea. Existing methods have generally attempted to estimate performance aging through long-term trend analysis of a normalized capacity factor in which wind speed variability is calibrated. However, this study proposes a new method using SCADA data for wind farms whose total operation period is short (less than a decade). That is, the trend of power output deficit between predicted and actual power generation was analyzed in order to estimate performance aging, wherein a theoretically predicted level of power generation was calculated by substituting a free stream wind speed projecting to a wind turbine into its power curve. To calibrate a distorted wind speed measurement in a nacelle anemometer caused by the wake effect resulting from the rotation of wind-turbine blades and the shape of the nacelle, the free stream wind speed was measured using LiDAR remote sensing as the reference data; and the nacelle transfer function, which converts nacelle wind speed into free stream wind speed, was derived. A four-year analysis of the Shinan wind farm showed that the rate of performance aging of the wind turbines was estimated to be −0.52%p/year.

Reliability Modeling of Wind Farm Considering the Outages of Connection Cables

2013 ◽  
Vol 291-294 ◽  
pp. 461-466
Author(s):  
Guo Bing Qiu ◽  
Wen Xia Liu ◽  
Jian Hua Zhang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Power Output ◽  
Complex Terrain ◽  
Wind Farm ◽  
Sequential Monte Carlo ◽  
Reliability Model ◽  
Wake Effect ◽  
Reliability Modeling ◽  
Wake Model

Considering the randomness of wind speed and wind direction, the partial wake effect between wind turbines (WTs) in complex terrain was analyzed and a multiple wake model in complex terrain was established. Taking the power output characteristic of WT into consideration, a wind farm reliability model which considered the outages of connection cables was presented. The model is implemented in MATLAB using sequential Monte Carlo simulation and the results show that this model corrects the power output of wind farm, while improving the accuracy of wind farm reliability model.

A Comparative Study of the Influence of Different Wake Models on Wind Farm Layout Optimization

2021 ◽  
Author(s):  
Puyi Yang ◽  
Hamidreza Najafi
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Vital Role ◽  
Layout Optimization ◽  
Zone Model ◽  
Wind Farm Layout ◽  
Yaw Control ◽  
Wind Farm Layout Optimization ◽  
Wake Model ◽  
Large Wind

Abstract The accuracy of analytical wake models applied in wind farm layout optimization (WFLO) problems plays a vital role in the present era that the high-fidelity methods such as LES and RANS are still not able to handle an optimization problem for large wind farms. Based on a verity of analytical wake models developed in the past decades, FLOw Redirection and Induction in Steady State (FLORIS) has been published as a tool integrated several widely used wake models and the expansions for them. This paper compares four wake models selected from FLORIS by applying three classical WFLO scenarios. The results illustrate that the Jensen wake model is the fastest one but the defect of underestimation of velocity deficit is obvious. The Multi Zone model needs to be applied additional tunning on the parameters inside the model to fit specific wind turbines. The Gaussian-Curl wake model as an advanced expansion of the Gaussian wake model does not perform an observable improvement in the current study that the yaw control is not included. The default Gaussian wake model is recommended to be used in the WFLO projects which implemented under the FLROIS framework and has similar wind conditions with the present work.

scholarly journals Fast Processing Intelligent Wind Farm Controller for Production Maximisation

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 544 ◽  
Author(s):  
Tanvir Ahmad ◽  
Abdul Basit ◽  
Juveria Anwar ◽  
Olivier Coupiac ◽  
Behzad Kazemtabrizi ◽  
...  
Keyword(s):  
Turbulence Intensity ◽  
Wind Farm ◽  
Control Strategies ◽  
Wind Farms ◽  
Coordinated Control ◽  
Medium Size ◽  
Farm Production ◽  
Fast Processing ◽  
Farm Efficiency ◽  
Wake Model

A practical wind farm controller for production maximisation based on coordinated control is presented. The farm controller emphasises computational efficiency without compromising accuracy. The controller combines particle swarm optimisation (PSO) with a turbulence intensity–based Jensen wake model (TI–JM) for exploiting the benefits of either curtailing upstream turbines using coefficient of power ( C P ) or deflecting wakes by applying yaw-offsets for maximising net farm production. Firstly, TI–JM is evaluated using convention control benchmarking WindPRO and real time SCADA data from three operating wind farms. Then the optimised strategies are evaluated using simulations based on TI–JM and PSO. The innovative control strategies can optimise a medium size wind farm, Lillgrund consisting of 48 wind turbines, requiring less than 50 s for a single simulation, increasing farm efficiency up to a maximum of 6% in full wake conditions.

Wind farm layout optimization with a three-dimensional Gaussian wake model

2020 ◽  
Vol 159 ◽  
pp. 553-569 ◽  
Author(s):  
Siyu Tao ◽  
Qingshan Xu ◽  
Andrés Feijóo ◽  
Gang Zheng ◽  
Jiemin Zhou
Keyword(s):  
Wind Farm ◽  
Three Dimensional ◽  
Layout Optimization ◽  
Wind Farm Layout ◽  
Wind Farm Layout Optimization ◽  
Wake Model
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