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

Results and Discussion

4.1. Wind profile of Uttara Kannada

Wind speed is seasonal as well as dependent and is, typically, at its maximum during the monsoon.Throughout the year, wind speed varies from 1.9 m/s (6.84 km/hr) to 3.93 m/s (14.15 km/hr) resulting in its minimum in October and maximum in the months of June and July. An annual average wind speed in the district ranges from 2.54 ±0.04 m/s (9.144 ±0.144 km/hr) in Haliyal taluk to 2.70 ± 0.05 m/s (9.72± 0.18 km/hr) in Karwar taluk. Figure 3 gives a taluk¬wise annual average wind speed of the district. Ample amounts of electrical energy can be generated using blowing wind through wind farms which could meet a major fraction of the current electricity demand of the district through decentralized generation.

Figure 3 Average annual wind speed of uttara kannada

4.2. Seasonal variation of wind speed

Wind speed of Uttara Kannada is quite uncertain and dependent on ambient temperature and pressure, vegetation cover, elevation, topography of the site, etc. Uttara Kannada has a mixed topography, which includes the coastal belt, low and high elevation area with forest cover, as well as planes. From February to May,the district experiences summer with higher temperature in coastal areas (Karwar, Honnavar, Kumta, Bhatkal, and Ankola) and in planes (Mundgod and Haliyal), and a comparatively lower temperature in taluks of higher altitudes (Sirsi, Siddapur, Yellapur, and Supa). Figures 4 to 6 give the mean wind speed variability in the district during summer, winter, and monsoon months.

Figure 4 Wind speed variation during summer (m/s)
Figure 5 Wind speed variation during monsoon (m/s)
Figure 6 wind speed variation during winter(m/s)

4.3.Wind Energy Conversion System (WECS)

This is used to extract energy from wind which is in turn converted to mechanical and then electrical energy. Main components of WECS are blades, gears, turbines, generators, and pillars to mount all the equipment at the required height.Wind potential assessment is a prominent pre-installation procedure to assure a perfect selection of site and to harness maximum energy. In order to explore the potential of wind technologies at an increased hub height, hourly surface wind speed measurements at IMD stations were estimated and represented in Figure 7.1n almost all the taluks, more than 45% of the wind speed is above 2.5 m/s except Honnavar (39.58%). Over 20% of the measured hours crossed 3. Karwar, Kumta, and Supa, in which Karwar was the highest (27.38%). These findings along with relatively higher wind speeds (>2 m/s in high elevation zone) observed in seasonal wind profiles (based on CRU data) are indicative of the prospects of small and medium scale wind applications in Uttara Kannada which are technically achievable and economically viable. Some of these are listed in Table 3. Wind pump for drawing water is an attractive small scale wind technology for rural energy needs. The agriculture and horticulture intensive zones of Uttara Kannada may benefit by wind pumps that function at low wind speeds. The vertical axis wind turbine (VAWT) that can function in wind speeds as low as 1 m/s could be more effective during low wind speed seasons in the region. Reduction in wind speeds and duration could be compensated by hybridizing wind with available alternative resources. Assessment of solar energy potential substantiates that it receives monthly average global insolation (incoming solar radiation)> 5 kWh/m2/ day. Hence, wind solar hybrid systems could be considered for endured energy supply in the region. Small scale wind turbines could also be used in conjunction with biomass gasifies/ diesel generators, especially in remote areas, although diesel is not a clean option. Battery charging based on wind systems supplements the energy requirements during reduced wind speeds.

Figure 7 wind speed variation during winter(m/s)
Rated power, Prated(kW) Rotor swept area (m2) Subcategory
Prated <1 kW A <4.9 m2 Pico wind
1 kW < Prated<7 kW A < 40 m2 Micro wind
7 kW< Prated<50 kW A <200 m2 Mini wind
50 kW<Prated<100 kW A < 300 m2 (Not defined)

Table 3 Available small-scale wind turbines

4.4.Techno-economic feasibility

Power harnessed by the WECS can be expressed using expression as given below Wind potential available in the district is estimated using equation 3 given in Table 4.

Pavail = (1/2) * p * A * V3 * Cp       (3)
Estimation shows that Micro and Mini WEC systems are feasible for the district since minimum and maximum power that can be harnessed ranges from 1,611.49 kW to 2,091.91 kW for the swept area of 30 m2 (micro model) and from 8,629.82 kW to 11,202.58 kW for swept area of 160 m2 (mini model). Cost of the wind turbines depends on the size, since the transportation and installation difficulties increase with the size. Cost per kilowatt of typical wind turbine ranges from $1,050 to 1,350 in India. " As the capacity increases cost/ kW decreases, but the size of the turbine and blade length increases. Table 5 gives the cost estimation of the WEC system

Month Wind speed m/s Power harnessed at A= 30 m2 (kW) Power harnessed at A= 160 m2 (kW)
  Min Max Min Max Min Max
January 1.80 2.10 42.69 67.79 228.61 363.03
February 2.10 2.37 67.79 97.44 363.03 521.83
March 2.10 2.37 67.79 97.44 363.03 521.83
April 2.45 2.67 107.65 139.33 576.48 746.14
May 2.90 3.00 178.53 197.64 956.05 1058.40
June 3.50 3.88 313.85 427.57 1680.70 2289.71
July 3.60 3.93 341.52 444.31 1828.92 2379.38
August 3.20 3.50 239.86 313.85 1284.51 1680.70
September 2.40 2.50 101.19 114.38 541.90 612.50
October 1.90 2.01 50.21 59.44 268.87 318.33
November 1.90 2.07 50.21 64.93 264.87 347.69
December 1.90 2.10 50.21 67.79 268.87 363.03
Total 1611.49 2091.91 8629.85 11202.58

Table 4 Wind power potential estimation


Particulars Capacity of the turbine
  1.5 kW 10 kW
Manufacturing cost 1,950 13,000
Battery bank 237 1422
Civil work and installation 105 702
Inverter 79 527
Maintenance charge & others 263 1756
Total cost 2634 17407
Annual energy generated (kWh) 3500 30000
Unit cost of electricity (USD/ kWh) 0.75 0.58

Table 5 Cost estimation of WECS

4.5. Scope for renewable energy exploitation

Decentralized electricity generation through renewable sources is gaining importance due to environmental problems with supply oriented approaches in planning driven by conventional, centralized power generation and distribution. Dispersed generation based on renewable energy (RE) sources addresses issues related to reliability, voltage-profile management, and the associated economic aspects. Micro grids help in exploiting locally available RE sources, which are alsofundamental units of smart grid architecture. However, the region's available energy potential and seasonal variability assessment is the primary step to map the viable regions for power harvesting.

Decentralized generation (DG) is the electric energy production at the distribution side of the power supply network or closer to the load centre itself. Distributed energy generation can play a pivotal role to meet the electricity demand in a reliable and environment-friendly way. Dispersed generation exploits locally available energy resources which will reduce the exploitation of conventional energy resources and also the congestion of generating units. DG-based on RE sources promotes higher penetration of RE resources in the grid. DG plants have the unique advantage of operating in islanded mode (grid isolation mode), during the outage of the central grid. Grid connection can be restored as the grid is energized and electricity can either be transferred to the grid or drawn from the grid. Micro grids are the building units of dispersed generation, which essentially exploit locally available grids with higher reliability, limited greenhouse gas (GHG) emission, and reduced transmission and distribution (T&D) losses. Smart grid architecture is in the infancy stage which integrates renewable energy-based distributed generation with the conventional system using control strategies over a two-way communication link.

As Karnataka is facing severe energy and peak-power crisis, decentralied solar and wind energy integration to the grid would narrow down the supply-demand gap. Micro grids need to be promoted to meet the community-level demand through locally available energy resources. Wastelands in the interior taluks are best suited for grid connected hybrid energy generation, while, micro grids and rooftop generation can be promoted in metropolis and biodiversity-rich Western Ghat taluks.The share of energy sources in installed capacity can be decided depending on the variability and geographic location. Renewable energy exploitation with grid integration needs to be promoted through appropriate policy interventions to mitigate the GHG emission through reduced dependence on fossil fuels.

 

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