July Interim Report. National Institute of Wind Energy (NIWE) Wind Resource Assessment & Offshore Unit Chennai, India.

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1 Interim Report (First Offshore Lidar wind data analysis) July 2018 Prepared by National Institute of Wind Energy (NIWE) Wind Resource Assessment & Offshore Unit Chennai, India.

2 W I N D R E S O U R C E A S S E S S M E N T & O F F S H O R E U N I T, CHENNAI, INDIA Table of Contents Page No. 1. Introduction 3 2. First Offshore wind resource assessment at Gulf of 4 Khambhat 2.1 Site Information a) LIDAR Measurement 2.2 Lidar data Analysis a) Time Series Profile b) Wind Frequency Distribution c) Wind Shear Profile d) Wind Rose 3. Automatic weather station a) Data Analysis b) Wind Rose 4. Jafrabad Mast a) Data Analysis b) Wind Rose 5. Data synthesis Annexure I. Validation of Lidar 28 II. Specification of Wind Cube LiDAR 29 III. Correlation - Lidar vs Jafrabad mast measurement 31 Disclaimer This report has been prepared for the benefit of the offshore wind farm developers & other stakeholders. The contents of the report (Graph/Photographs) etc., should not be used elsewhere without prior permission/approval from NIWE (National Institute of Wind Energy), Chennai. Page 2 of 32

3 W I N D R E S O U R C E A S S E S S M E N T & O F F S H O R E U N I T, CHENNAI, INDIA 1. Introduction The MNRE/NIWE has made consistent efforts to create a conducive environment for the development of offshore wind in the country. During the preparation of the Indian Wind Atlas, RISO DTU Denmark, along with NIWE indicated some offshore wind potential in the eastern shore compared to the western shore of South India. A preliminary estimation of the offshore potential was carried out by Scottish Development International (SDI) and NIWE for Tamil Nadu region in NIWE has also installed masts along the coastline for preliminary estimates on the offshore potential. Besides this, agencies like Indian National Centre for Ocean Information Services (INCOIS) have given some estimates based on the secondary data available with them. With the preliminary assessment showing good promising offshore wind potential in the southern tip and west coast of India, the National Offshore Wind Energy Policy was announced by the Government of India in October 2015 to establish the policy framework for tapping the offshore wind potential in the country. Further, FOWIND (Facilitating offshore wind energy project in India) consortium led by GWEC with NIWE as knowledge partner has prepared the Prefeasibility report in which 8 zones have been identified for Gujarat and Tamil Nadu coast. Based on the satellite data/desktop analysis offshore potential needs to be re-checked by long-term measurements to take better decision for identifying & notifying the zones/sub-zones as per offshore policy. Accordingly, a Lidar based offshore measurement campaign, first of its kind in the country was initiated in Gulf of Khambhat, Off Gujarat coast. Page 3 of 32

4 W I N D R E S O U R C E A S S E S S M E N T & O F F S H O R E U N I T, CHENNAI, INDIA 2. First Offshore wind resource assessment at Gulf of Khambhat 2.1 Site Information MNRE/NIWE in association with FOWIND, initiated Lidar based measurements to validate the wind potential at the preliminary demarcated zones. The first site was selected at Gulf of Khambhat for carrying out the Lidar based measurements. The Lidar location is situated approx. 23km from the Gujarat coast (Pipavav Port) in South-East direction. Figure 1 shows the Satellite images marking the Lidar location overlapped with FOWIND identified zones. The site details are tabulated in Table 1. Table 1: Site Description Site Name Taluk/District / State Lidar location Water Depth Distance from coast Nearest Village Nearest Town Nearest Railway Station Nearest Airport Nearest Port Nearest Electrical Substations onshore CRZ (as per 2011 notification) Gulf of Khambhat (Zone B as identified by FOWIND) Jaffrabad/Amerli / Gujarat 20 45'19.10"N, 71 41'10.93"E -15m depth (based on NHO* chart) 23km Pipavav Jaffrabad Rajula Junction Diu Pipavav/ Jaffrabad Ultratech 220kV Zone IV Page 4 of 32

5 W I N D R E S O U R C E A S S E S S M E N T & O F F S H O R E U N I T, CHENNAI, INDIA Figure 1: Lidar location overlapped with FOWIND identified zones The monopile (platform + sub structure) has been installed together with Automatic weather station comprising Anemometer, wind vane, Temperature & Pressure at 17m level on March 2017 and subsequently the LiDAR was installed and commissioned successfully on 31 st October 2017 after the withdrawal of sea ban imposed by Gujarat Maritime Board. Prior to the offshore installation, the LIDAR instrument (Wind cube) was validated against the 120m high met mast at NIWE s test station at Kayathar, Tamil Nadu. The verification study has shown good correlation coefficients with meteorological mast data (wind speed & wind direction) at inspected height (60m, 90m & 120m) and the details of the study are given in annexure I. a) LIDAR measurement Windcube V2 LiDAR is programmable for 12 various heights with minimum height 40m and maximum height 200m. The remaining 10 levels heights have been configured towards matching the hub heights of currently available offshore wind turbines in the present market. Table 2 depicts the Lidar measurement Page 5 of 32

6 W I N D R E S O U R C E A S S E S S M E N T & O F F S H O R E U N I T, CHENNAI, INDIA characteristics. Figure 2 illustrates the different configured heights & vertical wind shear profile. The details of the specifications of installed Windcube V2 LiDAR are attached in Annexure II. Table.2. Lidar measurement characteristics Measurement Type WindCube V2 LIDAR Structure height (monopile) 17m LAT * LIDAR Measurement heights 40,60,80,87,100, 107,120,140,160, 180 & 200m(MSL) # Location coordinates (UTM WGS 84, 42Q) Easting, Northing Date of Commissioning 31/10/2017 Measurement Period 01/11/ /06/2018 ( 8 months) (Duration) Measurement interval 10-minute Parameters Wind Speed, Wind direction, Temperature $, Pressure $ & RH (Relative Humidity) $ *LAT-Low Astronomical Tide, # MSL-Mean Sea Level, $ -measured at 17m platform level. Figure 2: Configuration of LiDAR at different heights & vertical wind shear profile Page 6 of 32

7 W I N D R E S O U R C E A S S E S S M E N T & O F F S H O R E U N I T, CHENNAI, INDIA 2.2 Lidar Data Analysis The wind and related weather data were logged as 10 minute averages. Analysis was performed with 10 minutes average data as per standard practice of wind energy sector. After due quality check of the available data, mean values of wind speed (WS) and Wind power density (WPD) have been calculated for each level. The wind data analysis summary can be obtained from Table 3. Table 4 represents the mean wind speed and WPD (Wind Power Density) values and Table 5 represents the month-wise wind speed values (mean, minimum & maximum). The air density values are calculated based on the measured temperature and pressure sensors installed at platform level (17m). Table 3. Details of Gujarat-LiDAR wind monitoring station Station District State Latitude Longitude Depth Offshore Gulf of Khambhat - LiDAR Amreli Gujarat 20 o N 71 o E -15m depth (As per NHO chart) Period of Data taken for Analysis November 2017 June 2018 Duration Length of the time step Data Recovery (%) 8 months 10 minutes 81.9% all heights Page 7 of 32

8 W I N D R E S O U R C E A S S E S S M E N T & O F F S H O R E U N I T, C H E N N A I, I NDIA Height (m) Table 4. Wind Speed & Wind Power Density (November June 2018) Nov-17 Dec-17 Jan-18 Feb-18 Mar-18 Apr-18 May-18 Jun-18 WS WPD WS WPD WS WPD WS WPD WS WPD WS WPD WS WPD WS WPD WS - Mean Wind Speed (m/s) WPD - Wind Power Density (W/m 2 ) Page 8 of 32

9 W I N D R E S O U R C E A S S E S S M E N T & O F F S H O R E U N I T, C H E N N A I, I NDIA Table 5. Mean, Minimum and Maximum (November June 2018) Heig ht (m) Mea n Nov-17 Dec-17 Jan-18 Feb-18 Mar-18 Apr-18 May-18 Jun-18 Mi n Max Mea n Mi n Max Mea n Mi n Max Mea n Mi n Max Mea n Mi n Max Mea n Mi n Max Mea n Mi n Max Mea n Mi n Max Mean - Wind Speed (m/s) Min Minimum of Wind Speed (m/s) Max- Maximum of Wind Speed (m/s) Page 9 of 32

10 W I N D R E S O U R C E A S S E S S M E N T & O F F S H O R E U N I T, CHENNAI, INDIA The Table 6. shows the month-wise data availability at the different levels of Lidar measurement. Based on the data analysis, the data recovery from the LIDAR instrument seems to be low during November 2017 to January 2018, owing to the power supply issues. However, the data gaps pertaining to this period have been filled with the support of MCP (Measure-Correlate-Predict) method by correlating the Lidar measurement (87m & 100m) with the Jafrabad coastal 100m high met mast (detailed in section 4.0). The process of synthesis and the characteristics of such synthesized data sets are detailed in section 5.0. Table 6. Month-Wise Data Availability (November June 2018) Month Nov Dec Jan Feb Mar Apr May Jun AVG a) Time Series Profile A time series profile will be much helpful to understand the variation of parameters within the measured duration in detail and handy in the identification & removal of the erroneous data. The time series profile for the wind speed measurement at various heights for available data are shown in Figure 3. Similarly, Figure 4, Figure 5 & Figure 6 illustrates the daily, monthly and diurnal mean wind speed profiles and Figure 7 illustrate the month wise diurnal pattern for visualization. Page 10 of 32

11 W I N D R E S O U R C E A S S E S S M E N T & O F F S H O R E U N I T, CHENNAI, INDIA Figure 3: Time Series (10minute) Profile of Wind Speed (40m to 200m) Figure 4: Daily Mean Wind Profile (Nov Jun 2018) Page 11 of 32

12 W I N D R E S O U R C E A S S E S S M E N T & O F F S H O R E U N I T, CHENNAI, INDIA Figure 5: Monthly Wind Profile (Nov 2017 June 2018) Figure 6: Diurnal Wind Profile (Nov 2017 June 2018) Page 12 of 32

13 W I N D R E S O U R C E A S S E S S M E N T & O F F S H O R E U N I T, CHENNAI, INDIA Nov-17 Dec-17 Jan-18 Feb-18 Mar-18 Apr-18 May-18 Jun-18 Figure 7: Month-wise diurnal pattern Page 13 of 32

14 W I N D R E S O U R C E A S S E S S M E N T & O F F S H O R E U N I T, CHENNAI, INDIA b) Wind Frequency Distribution The distribution of the wind speed data is presented by histogram plots, which is a common method of displaying a year of wind data. It is also known as wind frequency distribution, which shows the percentage of time each wind speed occurs. Figure 8 shows the measured frequency distribution as well as the Weibull distribution for wind speed measurements at various heights recorded. Weibull distribution is commonly used to approximate the wind speed frequency distribution. Table 7 depicts the 1 m/s binned percentage frequency distribution at different heights. Page 14 of 32

15 W I N D R E S O U R C E A S S E S S M E N T & O F F S H O R E U N I T, CHENNAI, INDIA Figure 8: Wind Speed Histogram (November 17 - June18) Page 15 of 32

16 W I N D R E S O U R C E A S S E S S M E N T & O F F S H O R E U N I T, C H E N N A I, I NDIA Table 7: Percentage Frequency Distribution Table (November 17 June 18) Bin (m/s) Percentage Frequency Distribution (%) Lower Upper Point Point 40m 60m 70m 80m 87m 100m 107m 120m 140m 160m 180m 200m Page 16 of 32

17 CHENNAI c) Wind Shear Profile The wind shear profile at the site is useful to understand the wind speed variation with respective height. Table 8 represents the month-wise power law and log law values. Figure 9 shows the nature of wind shear at Gulf of Khambhat, off Gujarat Coast based on the measured data using log law and power law. Table 8: Vertical Wind Shear Profile Table Month Power Law (alpha) Log Law (z0) Nov Dec Jan Feb Mar Apr May Jun Figure 9: Vertical Wind Shear Profile Page 17 of 32

18 CHENNAI d) Wind Rose Based on the data, it is revealed that the primary prevalent wind direction is SSW (south of south west) with a wind speed occurrence of 20% and secondary prevalent wind direction is North (wind speed occurrence in North direction is about 15%). The wind rose indicating all measured heights is given in Figure 10. The 16 sector wind roses based on wind direction data available at various heights (40m to 200m) are shown in Figure 11. Figure 10. Wind Rose (Nov 2017 June 2018) Page 18 of 32

19 CHENNAI Page 19 of 32

20 CHENNAI Figure 11: Wind Rose 40m to 200m Page 20 of 32

21 CHENNAI 3. Automatic Weather Station Automatic weather station was also deployed during the installation of offshore structure (Monopile & platform) in March The Station consists of one anemometer and one wind vane, which will measure the wind speed and wind direction at platform level i.e., 17m. The measured wind data is directly monitored by NIWE server using GSM modem. This will be useful for better correlation and standby mode of measuring instruments. Figures 12 depicts the arrangement of instrumentation. a) Data analysis Figure 12. First class thesis Anemometer and Wind vane In the data logger, wind speed and directions were sampled at 10 minutes average values was logged. Analysis was performed with 10 minutes average data as per standard practice of wind energy sector. After due quality check, the information about wind speed and WPD are further segregated into month-wise values in Table 9. The air density values calculated at the station are based on the measured temperature and pressure. Page 21 of 32

22 CHENNAI Month Temp ( C) Table 9. Monthly Mean Wind Speed Pressure (mb) Air Density (Kg/m 3 ) WS (m/s) WPD (W/m 2 ) No.of data available (10 minutes Interval) Data Recovery % Apr May Jun Jul Aug Sep Oct Nov Dec * 9.66 Jan ** Feb Mar Average Note: 1) *Data not recorded from 03/12/ :40 to 03/01/ :10 due to ockhi storm 2) **Data missing from 07/01/ :00 to 12/01/ :10 & 16/01/ :00 to 22/01/ :40 b) Wind Rose The 12 sector wind roses based on wind directions available are shown in Figure 13. It indicates that SSW direction is prominent wind direction. Figure 13: Wind Rose Page 22 of 32

23 CHENNAI 4. Jafrabad Mast (coastal mast) NIWE also installed the 100m height meteorological mast at Jafrabad coast in the line of sight with the LiDAR at a distance of approximately 25km, for the purpose of correlation & validation with the LIDAR measurement. The measurement was commenced on November 2017 in concurrence with the Lidar measurement. Figure 14 shows the geographical location of the 100m meteorological mast. The reference geographical coordinates for 100m mast location (Jafrabad) are as follows: Latitude: N Longitude: E Altitude: 9m agl UTM coordinates- WGS84, 42Q zone m E, m N Figure 14: Coastal mast 100m height at Jafrabad Page 23 of 32

24 CHENNAI a) Data analysis The information about wind speed and WPD are further segregated into month-wise values and tabulated in Table 10. The air density values are calculated based on the measured temperature and pressure sensors. Table 10. Monthly Mean Wind Speed Month Air Density (kg/m 3 )* 100m North 100m South 80m 50m 20m WS (m/s) WPD (W/m 2 ) WS (m/s) WPD (W/m 2 ) WS (m/s) WPD (W/m 2 ) WS (m/s) WPD (W/m 2 ) WS (m/s) WPD (W/m 2 ) Prevailing Wind Direction 98m 78m 48m No. of Data Available Nov NNE NNE N 4264 Dec NNE NNE NNE 4464 Jan NNE NNE N 4464 Feb NNE N NNE 4032 Mar N N N 4321 Apr W W W 3991 May WSW WSW WSW 4388 Page 24 of 32

25 CHENNAI b) Wind Rose The 12 sector wind roses based on wind directions available are shown in Figures 15a, 15b and 15c. Figure 15a: 98m Annual Wind Rose Figure 15b: 78m Annual Wind Rose Figure 15c: 48m Annual Wind Rose 5. Data synthesis Based on the data analysis, the data recovery from the LIDAR instrument seems to be low during November 2017 to January 2018, owing to the power supply issues. However, the data gaps pertaining to this period have been filled with the support of MCP (Measure-Correlate-Predict) method by correlating the Lidar measurement (87m & 100m) with the Jafarabad coastal 100m high met mast. The Lidar measurement of about seven months (November 17 to June 18) has been correlated with the concurrent wind data measured from the Jafarabad mast. Under the MCP method, sector-wise time series wind speed data (12 sectors) from the LiDAR measurement at 87m (87+17=104m amsl) were correlated with the Jafrabad 100m data by using linear least square (LLS) series correlation algorithm. The correlation between actual and model data yielded a Page 25 of 32

26 CHENNAI value of The synthesized data at 87m & 100m is detailed in Table 11. Further details related to correlation are available at annexure III. Table 11. Synthesized data at 87m & 100m Month 87 m 100 m Nov Dec Jan Feb Mar Apr May Jun Page 26 of 32

27 CHENNAI Annexures Page 27 of 32

28 CHENNAI VALIDATION OF LiDAR Annexure : I The Wind Cube Offshore LIDAR was validated with 120m height met mast, which was installed at a distance of 40m apart in parallel to the meteorological tower (120m height) which is used as reference mast located at Wind Turbine Test Station, Kayathar, Tirunelveli district, Tamil Nadu. The terrain of the selected area is a homogeneous terrain, which is already known for its wind potential. Data have been collected for 52 days ( ) from the met mast and from the LIDAR instruments. The LIDAR data was validated by comparing it with measurements from the met mast in order to determine the correlation of the wind data from both LIDAR and Mast for determining the correlation coefficient. The actual site images of met mast and LIDAR is shown in Figure 1 & 2. Figure 1: LiDAR set up Page 28 of 32

29 CHENNAI Figure 2: 120m Met Mast Based on the analysis, it was found that the LIDAR gives good correlation coefficients with the metrological mast wind speed & direction at inspected heights (60m, 90m, 120m) as shown below. Correlation Coefficient (R2) for Wind Speed Description 120m 90m 60m Mast v/s Lidar Correlation Coefficient (R2) for Wind Direction Description 120m 90m 60m Mast v/s Lidar Page 29 of 32

30 CHENNAI Specifications of Installed Windcube V2 LiDAR Annexure : II Technical Specification-Windcube v2 LIDAR Page 30 of 32

31 CHENNAI Correlation- Lidar vs Jafrabad mast measurement Annexure : III Page 31 of 32

32 CHENNAI Regression analysis-sector wise Page 32 of 32

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