scholarly journals Wind Resource Assessment of the Southernmost Region of Thailand Using Atmospheric and Computational Fluid Dynamics Wind Flow Modeling

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1899
Author(s):  
Jompob Waewsak ◽  
Chana Chancham ◽  
Somphol Chiwamongkhonkarn ◽  
Yves Gagnon
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
High Resolution ◽  
Power Plants ◽  
Resource Assessment ◽  
Wind Data ◽  
Wind Flow ◽  
Flow Modeling ◽  
Wind Resource Assessment ◽  
Wind Resource

This paper presents the wind resource assessment of the southernmost region of Thailand using atmospheric and computational fluid dynamics (CFD) wind flow modeling. The predicted wind data by the Weather Research and Forecasting (WRF) atmospheric modeling, assimilated to a virtual met mast, along with high-resolution topographic and roughness digital data, are then used as the main input for the CFD microscale wind flow modeling and high resolution wind resource mapping at elevations of 80 m, 100 m, 120 m, and 140 m agl. Numerical results are validated using measured wind data. Results show that the potential area where the wind speeds at 120 m agl are above 8.0 m/s is 86 km2, corresponding to a technical power potential in the order of 300 MW. The installation of wind power plants in the areas with the best wind resource could generate 690 GWh/year of electricity, thus avoiding greenhouse gas emissions of 1.2 million tonnes CO2eq/year to the atmosphere. On the other hand, developing power plants with International Electrotechnical Commission (IEC) Class IV wind turbines in areas of lower wind resource, but with easier access, could generate nearly 3000 GWh/yr of energy, with a CO2eq emissions avoidance of 5 million tonnes CO2eq on a yearly basis.

Distributed wind resource assessment: Comparing measured annual energy production with predictions from computational fluid dynamics

2019 ◽  
Vol 43 (6) ◽  
pp. 657-672
Author(s):  
Devon L Martindale ◽  
Thomas L Acker
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Wind Turbine ◽  
Energy Production ◽  
Resource Assessment ◽  
Energy Output ◽  
Wind Resource Assessment ◽  
Production Values ◽  
The Us ◽  
Wind Resource

The US Department of Energy’s Distributed Wind Resource Assessment Workshop identified predicting the annual energy production of a kilowatt-sized wind turbine as a key challenge. This article presents the methods and results for predicting the annual energy production of two 2.1 kW Skystream 3.7 wind turbines using computational fluid dynamics, in this case Meteodyn WT. When compared with actual production data, annual energy production values were uniformly underpredicted, with errors ranging from 1% to in excess of 30%, depending on the solver settings and boundary conditions. The most accurate of the simulations with errors consistently less than 10% were achieved when using recommended solver settings of neutral atmospheric stability, and roughness values derived from the US National Land Cover Database. The software was used to create an annual energy production map for the modeling domain, which could be a valuable tool in estimating the energy output and economic value of a proposed wind turbine.

Component Size Optimization of a Wind-Integrated Microgrid System With Dispatch Strategy and Resource Uncertainty

2014 ◽  
Author(s):  
Tzu-Chieh Hung ◽  
Kuei-Yuan Chan
Keyword(s):  
Alternative Energy ◽  
High Reliability ◽  
Design Procedure ◽  
Resource Assessment ◽  
Integrated System ◽  
Wind Data ◽  
Wind Model ◽  
Storage Devices ◽  
Wind Resource Assessment ◽  
Wind Resource

The global quest for energy sustainability has motivated the development of technology for efficiently transforming various natural resources into energy. Combining these alternative energy sources with existing power systems requires systematic assessments and planning. The present study investigates the conversion of an existing power system into one with a wind-integrated microgrid. The standard approach applies wind resource assessment to determine suitable wind farm locations with high potential energy and then develops specific dispatch strategies to meet the power demand for the wind-integrated system with low cost, high reliability, and low impact on the environment. However, the uncertainty in wind resource results in fluctuating power generation. The installation of additional energy storage devices is thus needed in the dispatch strategy to ensure a stable power supply. The present work proposes a design procedure for obtaining the optimal sizing of wind turbines and storage devices considering wind resource assessment and dispatch strategy under uncertainty. Two wind models are developed from real-world wind data and apply in the proposed optimization framework. Based on comparisons of system reliability between the optimal results and real operating states, an appropriate wind model can be chosen to represent the wind characteristics of a particular region. Results show that the trend model of wind data is insufficient for wind-integrated microgrid planning because it does not consider the large variation of wind data. The wind model should include the uncertainties of wind resource in the design of a wind-integrated microgrid system to ensure high reliability of optimal results.

scholarly journals Comparison of three probability distributions and techno-economic analysis of wind energy production along the coastal belt of Pakistan

2020 ◽  
pp. 014459872093158 ◽  
Author(s):  
Muhammad Sumair ◽  
Tauseef Aized ◽  
Syed Asad Raza Gardezi ◽  
Muhammad Mahmood Aslam Bhutta ◽  
Syed Muhammad Sohail Rehman ◽  
...  
Keyword(s):  
Wind Speed ◽  
Energy Production ◽  
Probability Distributions ◽  
Resource Assessment ◽  
Wind Data ◽  
Coefficient Of Determination ◽  
Resource Estimation ◽  
Wind Resource Assessment ◽  
Coastal Belt ◽  
Wind Resource

Continuous probability distributions have long been used to model the wind data. No single distribution can be declared accurate for all locations. Therefore, a comparison of different distributions before actual wind resource assessment should be carried out. Current work focuses on the application of three probability distributions, i.e. Weibull, Rayleigh, and lognormal for wind resource estimation at six sites along the coastal belt of Pakistan. Four years’ (2015–2018) wind data measured each 60-minutes at 50 m height for six locations were collected from Pakistan Meteorological Department. Comparison of these distributions was done based on coefficient of determination ( R2), root mean square error, and mean absolute percentage deviation. Comparison showed that Weibull distribution is the most accurate followed by lognormal and Rayleigh, respectively. Wind power density ( PD) was evaluated and it was found that Karachi has the highest wind speed and PD as 5.82 m/s and 162.69 W/m2, respectively, while Jiwani has the lowest wind speed and PD as 4.62 m/s and 76.76 W/m2, respectively. Furthermore, feasibility of annual energy production (AEP) was determined using six turbines. It was found that Vestas V42 shows the worst performance while Bonus 1300/62 is the best with respect to annual energy production and Bonus 600/44 is the most economical. Finally, sensitivity analysis was carried out.

scholarly journals Wind Resource Assessment for Alaska’s Offshore Regions: Validation of a 14-Year High-Resolution WRF Data Set

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2780
Author(s):  
Jared A. Lee ◽  
Paula Doubrawa ◽  
Lulin Xue ◽  
Andrew J. Newman ◽  
Caroline Draxl ◽  
...  
Keyword(s):  
High Resolution ◽  
Weather Prediction ◽  
Regional Climate ◽  
Wind Farms ◽  
Resource Assessment ◽  
Small Sample ◽  
Offshore Wind ◽  
Data Set ◽  
Wind Resource Assessment ◽  
Wind Resource

Offshore wind resource assessments for the conterminous U.S. and Hawai’i have been developed before, but Alaska’s offshore wind resource has never been rigorously assessed. Alaska, with its vast coastline, presents ample potential territory in which to build offshore wind farms, but significant challenges have thus far limited Alaska’s deployment of utility-scale wind energy capacity to a modest 62 MW (or approximately 2.7% of the state’s electric generation) as of this writing, all in land-based wind farms. This study provides an assessment of Alaska’s offshore wind resource, the first such assessment for Alaska, using a 14-year, high-resolution simulation from a numerical weather prediction and regional climate model. This is the longest-known high-resolution model data set to be used in a wind resource assessment. Widespread areas with relatively shallow ocean depth and high long-term average 100-m wind speeds and estimated net capacity factors over 50% were found, including a small area near Alaska’s population centers and the largest transmission grid that, if even partially developed, could provide the bulk of the state’s energy needs. The regional climate simulations were validated against available radiosonde and surface wind observations to provide the confidence of the model-based assessment. The model-simulated wind speed was found to be skillful and with near-zero average bias (−0.4–0.2 m s−1) when averaged over the domain. Small sample sizes made regional validation noisy, however.

An Empirical Study of Two Numerical Models for Wind Resource Simulation in Complex Terrain

2014 ◽  
Vol 535 ◽  
pp. 8-12 ◽  
Author(s):  
Zhen Wei ◽  
Yuan Chang Deng ◽  
Wei Zhang ◽  
Zheng Hao Yang
Keyword(s):  
Wind Speed ◽  
Complex Terrain ◽  
Resource Assessment ◽  
Wind Data ◽  
Simulation Accuracy ◽  
Wind Resource Assessment ◽  
Generation Capacity ◽  
Wind Resource ◽  
Simulated Wind ◽  
Simulated Wind Speed

The choice of wind measured data and numerical simulation method has an important impact on the results of wind resource assessment. This paper will take a wind farm, in Yangjiang City, Guangdong Province, for an example and discuss the simulation accuracy by linear model WAsP and nonlinear model based on simulation software Fluent. First of all, contrast mean absolute percentage error (MAPE) about simulated wind speed under four kinds of wind conditions, which are simulated by four sets of wind data in WAsP, and then select the wind data with the smallest . Then, using WAsP and CFD method simulates wind field by the optimal wind data. Compare simulated wind speed and annual generation capacity. In this paper, the simulated wind speed in the simulation model CFD based on Fluent is closer to the measured wind speed. The MAPE of wind speed and annual generation capacity by CFD model is smaller than that by WAsP. Therefore, for the wind resource assessment in the complex terrain, the nonlinear model CFD based on Fluent will be qualified to response the relationship between wind resource and terrain, simulation accuracy, and has higher simulation accuracy than the linear model WAsP.

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