SCOPE FOR RENEWABLE ENERGY IN HIMACHAL PRADESH, INDIA - A STUDY OF SOLAR AND WIND RESOURCE POTENTIAL Gautham Krishnadas and Ramachandra T V Energy & Wetlands Research Group, Centre for Ecological Sciences, Indian Institute of Science Bangalore 560 012 E Mail: cestvr@ces.iisc.ernet.in ABSTRACT Burgeoning human population and industrialization has put immense pressure on fossil fuel based sources like petroleum and coal. In this context, renewable resources assure energy security while addressing the issues of pollution, global warming and unemployment among others. Renewable energy sources unlike petroleum and coal are locally distributed and closely linked to the human lives, necessitating the need for regional level assessment of its potential to provide sustainable energy. This study has been done to estimate the potential of solar and wind resources in Himachal Pradesh, India. Considering the importance of spatial and temporal variations in distribution of renewable resources, geospatial techniques such as remote sensing and GIS has been used to quantify and understand the spatiotemporal changes. The global insolation (solar radiation) received by the land surface, is computed using the 22 year average datasets from National Aeronautical and Space Administration (NASA). Results reveal that, except for the winter months of December and January, Himachal Pradesh gets insolation above 4kWh/m 2 /day which is reasonably good for solar based applications. Wind energy potential is assessed using available on-site wind speed data procured from Indian Meteorological Department (IMD). High temporal resolution wind speed dataset from Climate Research Unit (CRU) has been used to produce a wind atlas for Himachal Pradesh, which is comparable to on-site measurements in spatial variations according to topography but not in magnitude. However results indicate that the region can minimally support electricity generation and applications such as water pumps. This investigation highlights the need for renewable energy potential assessment towards addressing the regional energy demand in a sustainable way. KEYWORDS Renewable energy, solar, wind, Himachal Pradesh 22 nd -24 th December 2010 Page 1
INTRODUCTION Renewable energy is gaining wide popularity around the globe. India has already taken steps to shift to the low carbon economy with essential public and private participation. It has a target of 20,000 MW of solar based power generation and nearly 45000 MW of wind energy potential is already assessed. [1] Solar energy can be converted to electricity using photovoltaic (PV) panels or concentrators. It is observed that, incoming solar radiation (insolation) above 4.5kWh/m2/day supports PV and concentrator based electricity generation. Applications like solar water heaters and cookers augment the domestic needs of cooking and water heating. Regions with wind speed above 15 kmph (~4m/s) support commercial electricity generation while those with 7-15kmph (~2-4m/s) support agricultural applications like wind pumps. Resource availability of solar and wind energy varies with geographic location, topography, microclimate and many other factors. Hence understanding the regional availability of resources is essential for the design of conversion devices which could effectively utilize the potential. This also helps in the regional level energy planning. The study area of Himachal Pradesh lying in the western Himalayas is one of the hill states in India. It has a geographical area of 55673 km 2. The elevation varies from 300m to 6700m from the west to east providing a variety of climatic conditions and resulting in diverse vegetation [2]. The solar and wind resource availability has been assessed for the study area taking into consideration their wide spatial variability. Wherever available, data have been obtained from ground based measurements. High temporal and spatial resolution remote sensing data supplements the study. Geographical Information Systems (GIS) implements the representation of collateral data in comprehensible resource maps for Himachal Pradesh. METHODOLOGY Solar potential assessment Insolation received is measured with pyranometers at radiation stations. India has 45 radiation stations which measures global insolation. This radiation network is insufficient to capture the regional insolation variation. Different interpolation and extrapolation models based on meteorological parameters like rainfall, cloud cover and temperature have been developed to estimate the insolation at data scarce regions. These models provide a near approximation of insolation with Root Mean Square Error (RMSE) below 10% when compared with ground data for distances within 34km [3]. As the distance increases, RMSE increases and these models stand inefficient in accuracy. Hence satellite imagery based physical and statistical models have been developed since 1980 s with better resolution and acceptable accuracy. 22 nd -24 th December 2010 Page 2
We have used the Surface Meteorology and Solar Energy (SSE) datasets from the National Aeronautical and Space Agency (NASA). The NASA SSE datasets for global horizontal insolation have been developed based on a physical model using 3 hourly satellite images taken for 22 years [4]. The monthly average global insolation data is obtained for thirteen 1⁰X1⁰ optimum grids covering Himachal Pradesh as shown in Table 1. Using Inverse Distance Weighted (IDW) interpolation in GIS tool, we generated the monthly global insolation maps with contours showing regional variation. Long Lat Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 77.5⁰E 29.5⁰N 3.68 4.56 5.80 6.84 7.31 6.71 5.57 4.93 5.25 5.05 4.26 3.54 76.5⁰E 30.5⁰N 3.57 4.61 5.71 6.81 7.42 7.12 5.89 5.46 5.62 5.29 4.32 3.45 77.5⁰E 30.5⁰N 3.66 4.55 5.75 6.92 7.53 6.93 5.65 5.08 5.43 5.40 4.44 3.57 78.5⁰E 30.5⁰N 3.75 4.50 5.64 6.76 7.42 6.73 5.36 4.83 5.25 5.42 4.49 3.69 76.5⁰E 31.5⁰N 3.41 4.31 5.45 6.68 7.43 7.17 5.68 5.29 5.55 5.30 4.23 3.36 77.5⁰E 31.5⁰N 3.58 4.26 5.38 6.49 7.21 6.87 5.59 5.15 5.41 5.41 4.42 3.52 78.5⁰E 31.5⁰N 2.85 3.37 4.28 5.09 6.03 6.10 5.63 5.33 5.15 4.89 3.88 2.97 79.5⁰E 31.5⁰N 3.10 3.62 4.41 5.26 6.57 7.02 6.64 6.09 5.80 5.15 4.04 3.11 75.5⁰E 32.5⁰N 3.25 4.15 5.22 6.55 7.32 7.33 5.86 5.48 5.75 5.29 4.13 3.18 76.5⁰E 32.5⁰N 3.23 3.84 4.98 6.02 6.85 6.87 5.66 5.22 5.40 5.16 4.11 3.21 77.5⁰E 32.5⁰N 2.67 3.29 4.23 5.05 5.80 6.33 6.01 5.53 5.19 4.67 3.55 2.66 78.5⁰E 32.5⁰N 3.17 3.86 4.66 5.44 6.42 7.02 6.67 6.20 5.78 5.11 3.86 3.01 76.5⁰E 33.5⁰N 2.59 3.20 4.04 4.88 5.83 6.49 6.10 5.76 5.35 4.58 3.41 2.57 Table 1 : Monthly average insolation (kwh/m 2 /day) data collected for the study Wind resource assessment For wind based energy generation, the wind regime has to be understood with the wind speed distribution as well as the wind power density [5]. The wind speed is measured using anemometers installed at meteorological stations. We obtained the wind speed data for 11 sites- Bilaspur (587m), Mandi (761m), Sundernagar (861m), Nahan (959m), Chamba (996m), Bhuntar (1096m), Dharmshala (1211m), Dalhousie (1959m), Manali (2039m), Simla CPRI (~2202m) and Shimla (2202m), from the Indian Meteorological Station (IMD). These sites are representative of elevations below 2500m while no sites above that have recorded wind speed data. Hence a 10 X10 spatial and 30 years temporal resolution wind speed dataset obtained from the Climate Research Unit (CRU) has been utilized to 22 nd -24 th December 2010 Page 3
understand the relative wind speed at elevations above 2500m. As in the case of solar dataset, the CRU monthly average wind speed data is interpolated with IDW in GIS to produce wind maps. RESULTS AND DISCUSSION Solar energy potential The solar energy potential in Himachal Pradesh has been assessed and can be inferred from the monthly average global insolation maps shown in Figures 1a-b. Considering the seasonal influence, Himachal Pradesh receives an average insolation of 5.99 kwh/m²/day in the warm summer months of March, April and May; 5.89 kwh/m²/day in the wet monsoon months of June, July, August and September; 3.94 kwh/m²/day in the colder winter months of end October, November, December, January and February. For the period from March to October the entire physiographic zones of Himachal Pradesh receives insolation above 4 kwh/m²/day, favouring commercial as well as domestic applications of solar energy. With the onset of winter by the end of October, the insolation in Himachal Pradesh drops down and a low insolation period prevails till the end of February. This confines the exploitation of the incident solar energy to domestic appliances like solar cookers, solar water heater etc in winter. 22 nd -24 th December 2010 Page 4
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Figure 1a: Monthly average global insolation from January to June 22 nd -24 th December 2010 Page 6
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Figure 1b: Monthly average global insolation from July to December Wind energy potential Wind speed collected for the 11 sites (Figure 2) shows wind speed increase for two occasions in a year. The first rise in wind speed happens during March which resides by June/July and again rises in September/October after the rainy season. This trend is not seen for Bhuntar where there is a single rise in wind speed reaching its peak in July/August. Nahan records the highest wind speed with a monthly average of 6.5±1.1 kmph followed by Bhuntar with 4.2±1.6 kmph and Dharamsala with 4.2±1.3 kmph. As observed from the wind speed variations, all other sites recorded less than a monthly average of 3.4 kmph. Figure 2: Monthly average wind speed for 11 sites The wind maps (Figure 3) obtained from CRU dataset, represent the monthly average wind speed variation for Himachal Pradesh. It is observed that, wind speed increases during the summer month of April and tallies with the on-site data. Since no on-site measurements are available for higher elevations (above 2500m), the wind maps could be relied upon to conclude that wind speed is relatively higher for regions like Lahaul-Spiti, Kinnar and Eastern Kullu, when compared to lower elevations. From the application point of view, Himachal Pradesh can minimally support wind energy based agricultural pumps and electricity generation. 22 nd -24 th December 2010 Page 8
Figure 3: Monthly average wind speed variation based on synthesized data from CRU CONCLUSION This study is an attempt to appreciate the renewable energy potential in Himachal Pradesh with focus on solar and wind resources. The regional level availability of solar and wind resources is measured with reliable ground as well as remote sensing data. A high influence of seasons, topography and climate on the spatial resource variability is observed in the study area. Solar energy received by Himachal Pradesh could be effectively utilized for commercial applications like PV/concentrator based electricity in the period of March to October. The other months essentially support domestic applications like solar cookers and water heaters. Wind speed measured at the sites as well as the synthesized data from CRU shows that the region can minimally support wind energy based applications, while elevations above 2500m deserve better observation. The scope for renewable energy is vast. A closer study of the available renewable resources like the one presented helps in the effective regional energy planning and achieving ambitious targets already set. 22 nd -24 th December 2010 Page 9
REFERENCES [1] Ministry of New and Renewable Energy, Government of India, Viewed on October 15 2010, <http://www.mnre.gov.in/> [2] Statistical Data of Himachal Pradesh upto 2009-10, Himachal Pradesh Planning Department, Govt. of Himachal Pradesh, Viewed on October 15, 2010, <http://hpplanning.nic.in/statistical data of Himachal Pradesh upto 2009-10.pdf> [3] Richard Perez, Robert Seals, Antoine Zelenka, Comparing satellite remote sensing and ground network measurements for the production of site/time specific irradiance data, Solar Energy, f50, (1997) 89-96 [4] NASA, Surface Meteorology and Solar Energy Release 6.0 Methodology, Viewed October 8 2010, <http://eosweb.larc.nasa.gov/sse/documents/sse6methodology.pdf> [5] Anna Mani, D.A. Mooley, Wind Energy Data for India, Allied Publishers, New Delhi, 1983 22 nd -24 th December 2010 Page 10