Energy Options for Uttara Kannada Prospects of Wind Energy

Prof. T V Ramachandra and Mr Ganesh Hegde

Energy & Wetlands Research Group, Center for Ecological Sciences [CES], Indian Institute of Science, Bangalore, Karnataka, 560 012, India
Web: http://ces.iisc.ernet.in/energy, http://ces.iisc.ernet.in/foss   E Mail: emram.ces@courses.iisc.ac.in , tvr@iisc.ac.in ; ganesh@ces.iisc.ernet.in
Corresponding Author: T.V. Ramachandra

Study area and methods

3.1.Study area

Uttara Kannada, located between 13°55' and 15°31'N and 74°9' and 75°10'E, is the fourth biggest district of Karnataka state, located between 13°55' and 15°31'N and 74°9' and 75°10'E. Total population of the district is 1,436,847 and more than 70% of the people live in rural areas or in semi-urban areas. The district is located in the Western Ghats shelters ranges sheltering abundant flora and fauna. More than 75% of the total area is forest covered and has with 140km of costal belt.6 Figure 1 illustrates the topographic undulations of the region. Topographically, the district lies in three distinct zones, namely, narrow and flat coastal zone, abruptly rising ridge zone, and an elevated, flatter eastern zone. The coastal zone is thickly populated with coconut- clad villages.The ridge zone is a part of the main range of the Western Ghats, which runs north to south, parallel to the coast. The flat eastern zone joins the Deccan plateau. The taluks, which comprise the narrow flat coastal zone, are: Karwar, An kola, Kumta, Honnavar, and Bhatkal. Similarly, taluks, which comprise the ridge zone, are: Supa, Haliyal,Yellapur, western Sirsi, and western Siddapur.The flatter eastern zone includes Mundgod, eastern Sirsi, and eastern Siddapur. Four agro-climatic zones based on geography and climate are coastal, evergreen, dry deciduous, and moist deciduous. There are 1,291 villages, 7 towns, 5 city municipal corporations/town municipal corporations/outward growth/census towns, and 2 reservoirs in the district (http://uttarakannada.nic.in/, last retrieved on March 14, 2017).

Figure 1 Digital Elevation Model of Uttara Kannada, Karnataka

3.2. Data and Method

Synthesized wind data: This wind data available from various sources provide a preliminary understanding of the wind regime of a specific region. Depending on the physiographical features and climatic conditions, these data help in assessing wind potential in the region of interest validated by long- term surface wind measurements.

There are many wind speed data sets that are available of different time periods, such as National Aeronautical and Space Agency (NASA), Surface Meteorology and Solar Energy (SSE), National Oceanic and Atmospheric Administration (NOAA-CIRES), Climate Research Unit (CRU), etc. However, previous studies have evidently showed that CRU data are reliable and are closer to the Indian Meteorological Department (IMD) surface data, and hence used in the present study.CRU at the University of East Anglia maintains climatic average datasets of meteorological variables which contains wind speed data for the period of 1961-1990 compiled from different sources. Further, inter- and intra variable consistency checks are performed to minimize data consolidation errors.The Global Land One-km Base Elevation Project (GLOBE) data of the National Geophysical Data Center (NGDC) were re-sampled to 10'x10' (ten- minute spatial resolution) elevation grids where every cell with more than 25% land surface (those below 25% being considered water bodies) represents the average elevation of 100-400

GLOBE elevation points.The climatic average of wind speeds measured at 2 to 20 m anemometer heights (assumed to be standardized during collection) collated from 3,950 global meteorological stations together with the information on latitude, longitude, and elevation were interpolated based on a geo-statistical technique called thin plate smoothing splines. Elevation as a co-predictor considers topographic influence on the wind speed and proximity of a region to the measuring station improves the reliability of the interpolated data. During interpolation, inconsistent data was removed appropriately.This technique was identified to be steadfast in situations of data sparseness or irregularity.' The 10'x10' spatial resolution wind speed data as climatic averages were available for all global regions (excluding Antarctica).

Data from IMD stations located in the district are also acquired for respective locations and which gave the satisfactory results comparing with CRU data set.There are four IMD stations in the districts which are listed in Table 1. Cup counter anemometers with hemispherical cups measuring 7.62 cm in diameter were used in Indian Meteorological Department (IMD) observatories until 1973. During 1973-1979, these anemometers were are replaced with three cup anemometers with 127 mm diameter conical cups, which are placed at 10 m above ground level, over open terrain, in conformity with international practice.

Data from the meteorological observatories at Karwar (for the period 1952-1989), Honnavar (for the period 1939-1989), and Shirali (for the period 1974-1989) obtained from the Indian Meteorological Department, Government of India, Pune, and daily wind data for the period 1990-1993 for these observatories, from the IMD, Bangalore.The primary data obtained by installing a cup counter anemometer with mechanical counter fixed on a 5 m tall guyed masts at Sirsi and Kumta. The anemometer readings were noted down every three hours during the day and mean wind speeds were obtained.

Anemometeres at different meteorological stations are set at different heights levels.The wind speed recorded at each station has to be adjusted to any constant height prior to analysis. The standard height according to the World Meteorological Organization is 10 m above the ground level which is used for the analysis.1° The horizontal component of the wind velocity varies a great deal with height under the influence of frictional and impact forces on the ground. The most common model for the variation of horizontal velocity with height is given by the logarithmic wind profile equation 2:

(V1/V2)=(H1/H2)           (2)
Where V1 is a wind speed at height of 10 m above ground level, V2 is a wind speed at height H2`1 above ground level, and is the roughness factor which is determined by substituting the wind speed data obtained with anemometer height in various wind directions, and found to be 0.30. Table 2 gives the month- wise average wind speed in the respective locations.

Figure 2 shows the comparison of mean wind speed in five IMD stations. At higher elevations in the district as well as in coastal regions, mean wind speed is comparatively higher and also in coastal region. Wind speed recorded at Honnavar and Shirali stations are lower which are placed at an elevation of 26 m and 45 m, respectively.

Location Latitude Longitude Elevation (m)
Karwar 14° 47' 74° 08' 4
Kumta 14°26' 74° 25' 8
Honnavar 14° 17' 74° 27' 26
Shirali 14° 05' 74° 32' 45
Sirsi 14° 62' 74° 85' 610

Table 1 IMD stations in Uttara Kannada

Figure 2 Monthly variations in wind speed

 

Citation: Prof. T V Ramachandra and Mr. Ganesh Hegde, 2017, Energy Options for Uttara Kannada Prospects of Wind Energy, Energy Insights
* Corresponding Author :
  Dr. T.V. Ramachandra
Energy & Wetlands Research Group, Centre for Ecological Sciences, Indian Institute of Science, Bangalore – 560 012, India.
Tel : 91-80-23600985 / 22932506 / 22933099,      Fax : 91-80-23601428 / 23600085 / 23600683 [CES-TVR]
E-mail : emram.ces@courses.iisc.ac.in , tvr@iisc.ac.in , energy.ces@iisc.ac.in,     Web : http://wgbis.ces.iisc.ernet.in/energycontact