Finding Potential Sites for Small-Scale Hydro Power in Uganda: a ...

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ivers are seasonal, since the hydro power station will then not work during the wholeyear. The permanent rivers were then rasterized using the function LINEGRID inArcWorkstaion. We classified all river cells to contain the value of one and all non-rivercells a value of zero. The classified raster layer was then multiplied by the DEM to applythe height values of the DEM to the river cells by using Raster Caculator in ArcGIS -Spatial Analyst (see Figure 4.5).Permanent Rivers DEM Rivers with elevationFigure 4.5 Raster Calculation of Permanent Rivers and the DEM in order to receivea layer with Permanent Rivers with height values. Grey cells represent river cellsand the values in the DEM represents height values in meters.4 .2.5 AlgorithmTo find the sites suitable for building small-scale hydropower stations we designed analgorithm in the software Matlab 7.0, see Appendix 9.4. It is designed to search amaximum of ten connected river cells (if a cell size of 10 meters is used), whichPenstockapproximately equals 100 meters, to see if≤100 metersthe criterion of 20 meter accumulatedHead20 metershead is fulfilled. These cells will then besaved into an output raster. According toMaher and Smith (2001) a head of 20 Figure 4.6 Head and penstock.meters is recommended to produceenough power for the kind of small-scale hydropower stations that our study focus on.The distance of 100 meters corresponds to the length of the penstock in which the waterflows down to the turbine. There is no absolute measure of how long the penstock mustbe, since it can vary greatly depending on the appearance of the terrain. However, thepenstock is one of the most expensive parts in the construction of small-scalehydropower stations, which imply that a short penstock is preferable. Maher and Smith(2001) recommend a penstock of 100 meters, which together with a 20-meter head areset to be the criteria in our algorithm (see Figure 4.6).40
To get an overview of how the algorithm is designed, Figure 4.7 shows the differentsteps on which the algorithm is based on.The needed input data for the algorithm is a raster in floating data format, containingriver cells where the cell values illustrate absolute elevation. The algorithm begins byreading the input data into a matrix called “DATA”, where the number of rows andcolumns depends on the resolution and the size of the area of interest. An example isshown in Figure 4.8a.The next step in the algorithm is to extract all cellscontaining a value other than zero, and save theminto the array “RIVERCELLS” (see Figure 4.8b).These values are then ranked by height and storedinto another array called “ORDER”, see theexample in Figure 4.8c. The arrays consist of threecolumns, containing the river cell’s coordinatesand height values. The number of rows in thesearrays is equal to the number of river cells in“DATA”. This operation is done in order to makeour algorithm more time effective, since sortingone column (“RIVERCELLS”, z) is done muchfaster than alternative solutions.In order to find a head of 20 meters over adistance of 100 meters, the algorithm locates ten ina row connected cells and calculates theiraccumulated height difference. It is possible forthe river cells to connect diagonally, which meansthat the accumulated distance of ten cells canreach a maximum of 141 meters.Figure 4.7 Flowchart showing thechain of processes in the algorithm.41
Page 1: Seminar series nr 121Finding Potent
Page 5: AbstractOver 2 billion people, most
Page 9: AcknowledgmentsFirst of all, we wou
Page 12 and 13: 5 Result ..........................
Page 14 and 15: For the specific case of Uganda, a
Page 17 and 18: 2 Study AreaThe main reason for us
Page 19 and 20: In the 1960’s Uganda was one of t
Page 21 and 22: 2.1.3 TopographyMost of Uganda is s
Page 23: Figure 2.4 The highest volcano in K
Page 26 and 27: e able to manually write the data,
Page 28 and 29: Depending on the appearance of the
Page 30 and 31: o Then the water flows from the for
Page 32 and 33: and generator is 65% and 80% effici
Page 34 and 35: Table 3.2 Capacity and production o
Page 36 and 37: Table 3.5 Small-scale hydropower ca
Page 38 and 39: technology was supplied to an area
Page 40 and 41: component to all of these issues, g
Page 42 and 43: The Rural Electrification project t
Page 44 and 45: The closer the interviewer is to th
Page 46 and 47: Over this area we bought the follow
Page 48 and 49: The primary erosive force determini
Page 50 and 51: There are a set of tolerances used
Page 54 and 55: (a) (b) (c)Figure 4.8 An example sh
Page 56 and 57: 4.2.6 Post Processing of Output Dat
Page 58 and 59: A = ( b ⋅ h)2(4.3)Where A equals
Page 60 and 61: elinquish because of too expensive
Page 62 and 63: The first step when performing the
Page 64 and 65: more obvious in their geographic co
Page 66 and 67: By using a smaller area it is possi
Page 68 and 69: 5.3 Summary of Resultso The general
Page 70 and 71: projects are supposed to be finance
Page 72 and 73: Sinks are a reoccurring problem whe
Page 74 and 75: UTM Zone 36N projection. The study
Page 76 and 77: As described in chapter 3.3.3 all r
Page 78 and 79: and if good financing possibilities
Page 80 and 81: Hutchinson M. F., Dowling T. I., 19
Page 83 and 84: 9 Appendix9.1 Interview: Rural Elec
Page 85 and 86: 9.3 Digital DataAll data layers are
Page 87 and 88: Frame creationThis is made in order
Page 89 and 90: time2=clock;%starts timer on clock
Page 91 and 92: next(1,2)=(y-1);cell_height=(highes
Page 93 and 94: endendif height>=20;%if the accumul
Page 95: Site 16 (147486,78619)Site 20 (1560

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