APPLICATIONS OF RS AND GIS  FOR DEVELOPMENT OF SMALL HYDROPOWER PLANTS (SHP)
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APPLICATIONS OF RS AND GIS FOR DEVELOPMENT OF SMALL HYDROPOWER PLANTS (SHP)

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    APPLICATIONS OF RS AND GIS  FOR DEVELOPMENT OF SMALL HYDROPOWER PLANTS (SHP) APPLICATIONS OF RS AND GIS FOR DEVELOPMENT OF SMALL HYDROPOWER PLANTS (SHP) Presentation Transcript

    • DEEP BASU 131859 1
    • SMALL HYDRO POWER PROGRAMME (SHP) •Small Hydro Power (SHP) projects up to 25 MW station capacities serving a small community or industrial plant. •Available on small rivers, canal heads and canal drops. •Potential for power generation in the country from such plants is over 15,000 MW. 2
    • Fig:1 SHP 3
    • WHY GIS AND RS FOR HYDROPOWER DEVELOPMENT •Variation in terms of natural and socioeconomic settings. •Rivers have distinct catchments areas in different physiographic zones. •Rugged terrain of Himalayas requires thorough study of geology, topography, land use patterns, distribution patterns of biodiversity resources, infrastructure, socio-economic activities etc. 4
    • FIELDS OF APPLICATION •Digital mapping •Drainage database system •Terrain analysis •Watershed mapping •Integration of socio-economic variables 5
    • Fig:2 Layer Management in a GIS Database 6
    • Fig. 3. Analytical framework of the SHP 7
    • 8 LITERATURE REVIEW 8 •Todinini CL . (2002) discussed advantages of these tools and their capability to simulate water content vis-à-vis discharge within miniature spatial extent for three different flows viz., overland, surface and channel flows. •Pokharel S. (2000) performed spatial analysis using GIS to develop location specific energy resource and consumption profile in rural areas of Nepal. •Mackay DS et al. (2000) showed benefits of GIS integrated process based hydrological models. It also described that the requirement of large volume of data concerning land use, soil and climate has been one major limitation of hydrological modelling.
    • Case study on Assessment of small hydropower potential using remote sensing data for sustainable development in India Authors: Surekha Dudhania,, A.K. Sinhab, S.S. Inamdara 9 Journal: Energy Policy (2006) Area of study: Tehri, Garwal district
    • Proposed Methodology •Emphasis on satellite image interpretation and its application for identification and assessment of water resources and its association for the development of hydropower in a scientific method. •Satellite image obtained from IRS-1D LISS III Geocoded False Color Composite (FCC) data is used for extraction and mapping of water resources. •In image processing technique, input and output are still images, but output is an abstract representation of the input. •Work is carried out in two steps: (1) Image clustering and classification (segmentation), (2) Image interpretation. 10
    • Image clustering and classification 11 •Fuzzy-theoretic technique of pattern clustering and classification used. •The intensity in terms of distribution of R-G-B values of pixels together with the knowledge base of the features of the objects is used for image clustering and classification. •Fuzzy C-Means (FCM) algorithm is used in the analysis. The number of cluster and sub clusters (water, forest, inhabitation and snow) assumed to crisp in nature for identifying the water resources. •FCM uses the principle of fuzzy sets to evolve a partition matrix U(X) while minimizing the measure (Uik)mD2(Vi,Xk),  C i 1  C i 1  C i 1  C i 1
    • Image Interpretation 12 •Clear water absorbs relatively little energy having wavelengths less than about 0.6 mm. High transmittance typifies these wavelengths with a maximum in the blue-green portion of the spectrum. •An expert system is developed with computer-based program in Visual Basic that uses knowledge, facts and different reasoning techniques to solve visual interpretation of wide variety of remotely sensed data problems.
    • Fig 4: Domain specific expert system 13 User User Interface may employ: Question and Answer, Menu Driven, Natural Language, Graphic Interface Styles, Human Expert Knowledge Acquisition Literature and others Knowledge based editor Inference engine Explanation subsystem General knowledge based Case specific data
    • 14 Fig 5: (a) 0-level DFD, (b) 1-Level DFD, (c) 2-level DFD SATELLIT E IMAGE S I A 0 LANDUSE/LAND COVER/WATER (a) 0-level DFD SATELLITE IMAGE LOAD IMAGE 0.1 FCC FILTER 0.3 PRINT 0.6 SAVE 0.7 ZOOM 0.5 FEATURES 0.4 R G B 0.2 (b) 1-Level DFD
    • 15 LOAD IMAGE EXTRACTED IMAGE OF THE SELECT OBJECT ADD TO DATA BASE WATER 0.4.1 SNOW 0.4.2 INHABITATION 0.4.3 FOREST 0.4.4 (c) 2-level DFD
    • 16 Fig 6 Ganga River Fig 7 Alaknanda River .
    • Results 17 •Site location at 1 and 2 on Alaknanda river shows minimum coverage of forest/vegetation area but requires rehabilitation and resettlement. •Site location at 3 may not justify for the site and also being mountainous region it is difficult and expensive to lay the transmission lines to the load centers.
    • Case study on Tools for Small Hydropower Plant Resource Planning and Development: A Review of Technology and Applications 18 Authors: Petras Punys, Antanas Dumbrauskas, Algis Kvaraciejus and Gitana Vyciene Journal: Energies (2011)
    • 19 GIS Applications for Evaluating Hydropower Potential •DEM (Digital Elevation Model) enables the study of land forms and, can access many hydrological and morphometric characteristics of a river basin. •Analysing DEM together with other data layers (e.g., soil data, land use, and protected areas) accurate estimations of hydropower planning are obtained that take the already existing network of hydropower into consideration. •By overlaying a segmented river network over the DEM, the elevation drop for each river reach can be obtained easily. By integrating runoff time series, flow duration curves, and annual flow data in GIS based models, power and energy maps can be produced.
    • 20 Figure 8 : GIS hydropower assessment tool. General model process flowchart
    • 21 Detailed scheme of GIS application for hydropower estimation Input data: Hydrographic network and DEM of river basin Input data: Hydrographic network and river catchment area with DEM
    • 22
    • 23 •Suitable tools are ArcGIS Spatial Analyst and the recently developed ArcGIS extension, ArcHydro which allows the user to set a number of hydrological parameters used by hydrologic models as input data. •Using the DEM of the river basin, soils and land cover thematic layers and the river network, the number of required input data for the hydrological model, a sub- basin separation procedure can be quickly and efficiently calculated. •A separate case of GIS application is the development of the map with a spatial distribution of FDC (Flow Duration Curves) parameters.
    • Table 1 :GIS-based Small Hydropower Atlases on the Internet 24 Name Developer Applicable countries Accessibility NVE Atlas Norwegian Water Resources and Energy Directorate (NVE) Norway Open access, interactive Web-based maps Virtual Hydropower Prospector (VHP) Idaho National Laboratory US Open access, interactive Web-based maps RHAM Kerr Wood Leidal Associates Ltd (KWL) British Columbia, Canada Open access, interactive Web-based maps Hydrobot Nick Forrest Associates Ltd. et al. Scotland Limited access VAPIDRO - ASTE ERSE SpA, Italy Open access, interactive Web-based maps
    • Summary: 25 •Remote Sensing provides a systematic and comprehensive approach to extract information for identification and assessment of water resources. For hydropower project studies, remote sensing (e.g., LIDAR), which is becoming cost effective compared with conventional surveying •Saving of manpower and time required for surveying and updating the information of the potential sites will have significant impact on the cost. •A large step in SHP assessment was the integration of these software tools into the GIS environment, the penetration of GIS to the Web and the advent of remote sensing techniques.
    • 26 •GIS is often used for the presentation of results in the form of digital maps. •Possible to rapidly assess power potential on a widespread basis while maintaining a relatively high level of detail. In most countries, GIS data are free of charge. •Using DEM and regional hydrologic data, these software tools are able to calculate the amount of hydropower available on all streams in a study area, screening out sites within environmentally sensitive or excluded areas, and to estimate project costs.
    • References:  Klimpt, J.E., Rivero, C., Puranen, H., Koch, F.; Recommendations for sustainable hydroelectric development. International Journal of Energy Policy 30 (2002), 1305–1312.  Petras Punys , Antanas Dumbrauskas, Algis Kvaraciejus and Gitana Vyciene. Tools for Small Hydropower Plant Resource Planning and Development: A Review of Technology and Applications. Energies 2011,4; 26 August 2011.  Surekha Dudhania,, A.K. Sinhab, S.S. Inamdara. Assessment of small hydropower potential using remote sensing data for sustainable development in India. Elsevier; Energy Policy 34 (2006) 3195–3205; 28 July 2005. 27