A Product by WinDForce Management Services Pvt Ltd. A realistic, - PowerPoint PPT Presentation

A Product by WinDForce Management Services Pvt Ltd.

A realistic, integrated and independent wind simulation Package

Highlights §An integrated system used for calculating the Annual Energy Production (AEP) of a Wind Turbine/ Windfarm Based on atmospheric boundary layer theory and uses intricate and proprietary mathematical/ numerical techniques to predict energy yield with greater accuracy.

Why WinDForcer? • Dependency of conventional WRA models on other packages for generating input files? • Final Output depend upon resolution of geo data • High Processing time of many hours for creation of Resource Grid? • Highly cumbersome? …….. WinDForcer is the NextGen solution to WRA

Crisp answers which makes it a Go Minimized runtime  No dependency on other softwares  Easily accessible globally  Report Generation at single click  Flexibility and client customization  Ease in data handling and data modeling  Realistic Assessment  Varied outputs  Comprehensive & Customizable Reports 

Key Features  Web based application  Can be remotely accessed  No other software or platform required  User friendly computational interface  Efficient computing leading to run time of up to 30 minutes  In-built database on WTG  Detects site complexity and chooses appropriate computational methods accordingly  Examines Missing/absurd/discontinuous values and produces data summary  Follows holistic approach while treating the measured wind speed data for appropriate wind shear value.  Adjust wind flow at individual turbine locations  Conduct Uncertainty analysis

“ Why WinDForcer? Our Unique Value Proposition

Terrain 1 Classifying capability § The package has the capability to recognize site terrain and to classify it as flat, moderately complex and complex. The model selects an appropriate route to computation.

Integrated Software 2 Architecture § Conventional software packages highly cumbersome § Conventional softwares require tab files and multitude of programs to run.Large project may require waiting period of for 12 hours or more for the resource grid to be prepared. § WinDForcer is an integrated program that gives results within 15 minutes of inputting the data.

Data 3 Synthesis § We all know that wind speed data received from a measurement can be either has erroneous data or missing data. § Under most conditions, WinDForcer is able to fill the missing data, through the analysis of the time series.

Comprehensive 4 & Customizable reports § The program generates varied kinds outputs in CSV and XL format including a comprehensive report in PDF.

5 User Friendly Interface § WinDForcer has a user friendly interface with interesting visualization and graphics. § The software can be customized as per the client, if requested.

Module of WinDForcer : AEP Module with Uncertainty

Product list of the Module  Provide Annual wind speed of each WTGs  Hourly mean wind speed values of each month  Wind shear profile of each month  Hourly values of energy generation for each WTGs.  Peak energy generation values of each WTGs  Inter-turbine distances, elevation, wind speed & wind roses graphs etc.  Uncertainty on wide range of component i.e. historical wind speed, anemometry, topographic etc.  Gross AEP and Net AEP  Net PLF - P50, P75, P90 and P95 values

Framework Detects whether site is The system automatically The system automatically flat or complex and calculate elevation of Create Root Project and calculate elevation of sub-root project (if required) Upload WTGs details accordingly select respective WTGs and respective WTGs and appropriate computational gives a GUI of the site gives a GUI of the site method Calculate Annual Energy distance Report Upload data at two Calculation and Upload wind mast details between each Generation sensors height (m) Uncertainty Analysis WTGs

Report outlook Gross and Net PLF

Google Site Map

Wind Speed Profile

Uncertainty Values

Wind Rose

Monthly Generation

What derives accurate wind predictions ? Wind Resource Assessment  More accurate wind Bankable wind Reduces predictions leads to less uncertainty Accurate wind report Uncertainty and and risks predictions risks  A reduction of the error margin up to 7-10 % (compared to 12-15 % for P90), can reduce a project’s cost of funds by 0.5-0.75% (The Economist 2010).  This reduction in cost of funds would lead to an even higher impact on ROE

“ Our results are close to realistic figures

Comparative analysis between Generation from WinDForcer v/s other conventional models S001 S002 S003 S004 Site Name MP MP MP MP State IWL-2.0 S-97 V-87 G-97 Power Curve 25.4% 28.9% 27.8% 41.0% Conventional Models 19.2% 29.7% 27.9% 36.8% WinDForcer Site Name S008 Site Name S005 S006 S007 State GJ GJ GJ State TN Power Curve S-97 Power Curve V-87 V-87 E-53 Conventional Models 25.2% 30.9% 23.7% Conventional Models 33.6% WinDForcer 33.5% WinDForcer 25.4% 32.7% 26.5% Non-complex Terrain

Comparative analysis between Generation from WinDForcer v/s other conventional models Site Name S009 S010 S011 S012 State MH MH MH MH Power Curve K-110 K-110 LetWinD-77 IWL-2.0 28.5% 27.3% 36.7% 27.0% Conventional Models WinDForcer 23.8% 23.9% 32.6% 25.8% Site Name S013 S014 State KR KR Power Curve S-97 S-97 35.5% 42.0% Conventional Models WinDForcer 30.1% 41.9% Complex Terrain

Test : A case of Rajasthan, India Actual v/s Energy Generation from WinDForcer “ Site Name S015 S016 S017 S018 S019 S020 RJ RJ RJ RJ RJ RJ State Power Curve S-66 S-66 S-66 S-88 RRB-600 S-66 WinDForcer 19.19% 15.80% 19.61% 19.32% 21.95% 20.79% Actual Generation 19.34% 17.07% 19.88% 17.90% 20.50% 20.15%

Test Case : Actual Generation v/s Energy Generation from WinDForcer Monthly generation profile of S018 (each WTG) 1.00 1.00 1.00 0.80 0.80 0.80 0.60 0.60 “ 0.60 0.40 0.40 0.20 0.20 0.40 0.00 0.00 0.20 April May June July August September October November December January February March April May June July August September October November December January February March 0.00 Aug … Sep … Oct … Nov … Dec … Jan … Feb … April May June July March Site Name S018 1.00 1.00 0.80 0.80 State RJ 0.60 0.60 0.40 0.40 Power Curve S-88 0.20 0.20 0.00 Septe … Novem … Decem … WinDForcer 19.32% 0.00 Septe … Novem … Decem … April May June July August October January February March April May June July August October January February March Actual Generation 17.90% Monthly Energy Generation (GWhr) Energy Generation from WinDForcer Actual Generation

0.00 0.20 0.40 0.60 0.80 1.00 Monthly Energy Generation (GWhr) 0.00 0.20 0.40 0.60 0.80 1.00 April April Actual Generation Energy Generation from WinDForcer May May June June Test Case : Actual Generation v/s Energy Generation from WinDForcer July July August August September Septem … October October November November December December Monthly generation profile of S018 (each WTG) January January February February March March 0.00 0.20 0.40 0.60 0.80 1.00 0.00 0.20 0.40 0.60 0.80 1.00 April April May May June June July July August August “ Septem … September October October November November December December January January February February March March 0.00 0.20 0.40 0.60 0.80 1.00 0.00 0.20 0.40 0.60 0.80 1.00 April April May May June June July July August August September September October October November November December December January January February February March March

A wind-farm problem resolved !! Post Implementation- Energy Generation Site was planned with 1.65 MW WTG, the annual After the WPP was implemented, it  generation projected by various softwares was 49 was found it was giving a PLF of GWhr/year corresponding to PLF of 34% 22-23%. WinDForcer reassessed the site,  the generation is predicted with PLF of 24.12% at P50 which is very close to actual PLF.

Features Sub-features WinDForcer Other conventional “ models √ × Cloud based and web application System √ × No Dependency on other software's/platform architecture √ × Greater flexibility and Client customization √ × Efficient runtime of 30minutes for one project √ √ Buit-in database of Wind turbines and Power curves Database Management √ Built-in database of digital elevation model and × System orography

“ √ Consider multiple turbine types and height × Data Handling √ √ Define wind sector √ √ Adjust wind flow at individual turbine locations √ √ Display ground heights, terrain contours, slopes and background images

“ √ × Examine Missing/absurd/discontinous values Data Modeling √ Follows holisitc approach while treating absurd/missing values i.e. fill × data with preceding and suceeding years, treat with appropriate wind shear value √ √ Correlate overlapping time series data √ √ Employ directional correlation plots and statistics