International Journal of Applied Engineering Research, ISSN 0973-4562 Vol. 9 No.23 (2014) pp. 7940-7945 © Research India Publications; http://www.ripublication.com/ijaer.htm
MAPPING THE POTENTIAL OF MICROHYDRO POWER GENERATION IN MALUKU, INDONESIA Lory Marcus Parera1, Rini Nur Hasanah2, and Wijono3 1
State Polytechnic of Ambon, Ambon, Maluku, Indonesia, E-mail:
[email protected] Electrical Engineering Department, Faculty of Engineering, Brawijaya University, Indonesia E-mail:
[email protected],
[email protected]
2,3
ABSTRACT Mapping water energy potential is one of the important aspects in the management of renewable energy sources. In Maluku region in Indonesia, it was recorded that there had been a total potential of 621 kW of micro-hydro power generation, but some plants having been exploited are not functioning anymore nowadays. If being fully exploited, the microhydro power plants (MHP) could account for approximately 1.93% of the total generating capacity nowadays existing, i.e. 31542 kW, in the region. This demand supply is currently carried out by using diesel generators. On the other hand, Maluku is geographically endowed with water energy potential in the form of 166 rivers being potential for microhydro power plants development. In order to explore the electrical energy potential in Maluku, mapping of the water energy potential for power generation has been undertaken four regencies, namely Central Maluku, West Seram, North Buru and South Buru. The mapping is done by measuring water flow rate and river head directly in 13 villages, as well as through the use of rainfall data and watershed area being combined with the elevation data estimated using Geographical Information System (GIS) and Google Earth Map in 216 villages. Among 371 villages as the object under consideration, water power generation capacity in 229 villages has been obtained from the relationship between the water flow rate and river head, while that of the remaining 142 villages has been obtained using statistical analysis. The results of mapping indicate the total potential capacity of 61.11 MW for generation of micro hydro electricity, with the possible largest generator output of 374.50 kW, the smallest output of 17.20 kW, and the average output of 165.85 kW. These results also demonstrate the potential for reducing the dependence on electricity generation originating from fossil fuels currently dominating in Maluku region. Based on the projection of electricity demand in the next 5 years performed by the national electricity provider in Indonesia (PT PLN), the resulted mapped potential could contribute to fulfillment 64.4% of the total electrical energy needs in Maluku region. Keywords: mapping, microhydro, generation capacity. 1. INTRODUCTION In Indonesia, the demand for electrical energy is fulfilled by the state-owned electricity company, the PT PLN (Persero), using a variety of sources such as fossilefuelled diesel, steam, gas, and also hydroelectric power. However, there still exist communities with no access to electricity, especially those people who live in areas being far from the centre of power generation [1], including some areas in Maluku region, particularly the Seram and Buru islands. The electricity demand in this area so far is supplied using some diesel generators with a total capacity of 31542 kW, which is still far from being adequate. Geographically Maluku region is endowed with water energy potential in the form of 166 rivers being potential for micro-hydro power plants development. These rivers are distributed over in four regencies, namely Central Maluku, West Seram, North Buru and South Buru [2]. Data of the Ministry of Energy and Mineral Resources (ESDM) show that that there is a total potential of 621 kW [3] of micro-hydro power generation. Ninety kilowatts of the potential have been obtained from MHPs in three locations, but now they are not functioning anymore. If being fully utilized, the potential could account for approximately 1.93% of the total generating capacity nowadays existing, i.e. 31542 kW, in the region. Based on the electricity power supply business plan of PT PLN (Persero), the increase of power generation need in the next five years of the 4 regencies in Maluku would be fulfilled
with a total generating capacity of about 95.5 MW [4]. Considering the huge water power potential being compared to that already being identified in Maluku by ESDM, there open the possibility of developing microhydro power generation to meet the needs which are still not fulfilled. On the other hand, the exploitation of the potential is often constrained by the unavailability of sufficient data because of the limited number of conducted studies and researches. This paper presents the results of water potential mapping in four regencies in Maluku region, i.e. Central Maluku, West Seram, North Buru and South Buru. 2. METHOD OF WATER ENERGY POTENTIAL MAPPING The area under consideration in this study covers 371 villages being spread over four regencies in Maluku region, i.e. Central Maluku, West Seram, North Buru and South Buru. Among these villages, direct measurement has been carried out to obtain the head and water flow debit in 13 villages using widely known methods [5]. The head and water flow discharge in 216 villages have been obtained with the help of site elevation, rainfall data on the location and the watershed area. The site elevation has been obtained from the data available on the Google Earth system, the rainfall data from the Indonesian Agency for Meteorological, Climatological and Geophysics (or simply called BMKG), whereas the watershed area has been obtained from the local government institution dealing with
International Journal of Applied Engineering Research, ISSN 0973-4562 Vol. 9 No.23 (2014) © Research India Publications; http://www.ripublication.com/ijaer.htm river data in Maluku region. Before using the Google Earth Map systems, the coordinate of villages whose names are provided by the local government, has been determined using Geographical Information Systems (GIS) software. This method is necessary because direct measurements in the field are not possible to carry out in the whole villages, considering the number of villages under consideration, the geographical position of the Maluku region and the limitations of time and research costs. 2.1 Determining village location using ArcGIS software Considering that not all the village names under consideration have been included in the Google Earth map, their location coordinates should be determined in advance using the GIS software based on the available village names. The process of determining the villages’ location is done by using a map in JPG or PNG graphical formats provided by the Maluku province office. The map is then converted into spatial data through the digitization process/trace, so that the obtained map data are correlated to the earth map’s coordinates (X,Y). Further process of transformation to obtain geographical coordinates (georeferencing) results in data file in .shp extension. The next step is to incorporate the resulted map into the GIS software, as shown in Figure-1.
Identification process of village location is done for each village name under consideration, so that an Excel file format table data containing the village names and coordinates can be obtained for further processing. 2.2 Determining site elevation using Google Earth Map Site elevation determination in Google Earth Map system is done with the help of data resulted from GIS software. Figure-4 shows how to add village names and coordinates data into the GIS software. Data table file in Excel format containing the village names and coordinates is imported in GIS software. The resulted spatial data will contain geographical orientation as well as a particular coordinate system as the basis of reference. These data are different from others in the fact that they contain location information (spatial) and descriptive information (attribute/ non-spatial).
Figure-3. Village location information in GIS
Figure-1. Process of inputting map file into GIS software The result of inputting Maluku province map into the GIS is shown in Figure-2.
Figure-4. Process of importing Excel file containing village names and coordinates in GIS Figure-5 indicates the actual position of villages on earth. In order to get this view, the Add Data process as shown in Figure-4 must be done on the appropriate file extension, i.e. Excel file format. Finally, the corresponding earth-projected coordinates (X,Y) will be resulted in accordance with the actual position on the earth. The dots on the map indicate the village locations.
Figure-2. Display result of incorporating Maluku map into GIS software As shown in Figure-3, Tool Identity is enabled to display the coordinates of the village location needed.
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International Journal of Applied Engineering Research, ISSN 0973-4562 Vol. 9 No.23 (2014) © Research India Publications; http://www.ripublication.com/ijaer.htm site elevation can be done at each coordinates point, as can be seen in Figure-8.
Figure-5. Projected coordinates x, y on earth In the Layer properties, coordinate points which make up the map, e.g. maps of the Buru and Seram islands, are added with symbols and village names as location identities, as shown in Figure-6.
Figure-8. The position of village location on Google E hM 2.3 Determining water flow discharge (Q) Determination of water flow discharge at specified location based on the GIS and Google Earth Map data is done with the help of rainfall and watershed area data in the Maluku region. The maximum daily rainfall data are obtained from the highest daily rainfall in a year at two stations, i.e. the Kairatu station in Seram island and the Mako station in Buru island. Water flow discharge is calculated using the following equation [6].
Q 0.002778.C .I . A ( m3 / s ) Figure-6. Map accordance Symbol and Name of Village It is indicated in Figure-6 that Buru island consists of two regencies, i.e. Nort Buru and South Buru, and that it has 56 villages. Seram island contains 2 regencies, i.e. Central Maluku and West Seram, consisting of 160 villages. The map containing symbols and village names is then stored as a new data, and then being displayed again for further conversion into Google Earth map as shown in Figure-7.
where: Q = water discharge (m3/s) C = run-off coefficient = 0.15 (steep-slope sand type) I = intensity of rainfall (mm) A = watershed area (km2) 2.4 Calculation of generation capacity The calculation of the capacity of micro-hydro power generation is done by using water flow discharge (Q) and head (H) data, which have been directly measured onsite of 13 villages and determined based on rainfall data, watershed area and elevation by using GIS and Google Earth Map in 229 villages. The generation capacity is calculated using the following formula [7]. Pt 9,81 * t * H net *Q net [ kW ]
where: t = turbine efficiency Qnet = water flow discharge (m3/s) Hnet = head (m)
Figure-7. Conversion process of GIS data into Google Earth map system
Generator output to be used can be calculated using the following equation.
As shown in Figure-7, bringing layer to KML is done to change the features or raster layer in memory into a KML file containing the translation of ESRI geometry (ArcGIS). The obtained file is of .KMZ extension and can be read by Google Earth Map, so that the determination of
Pel g * t * g * H net * Q [ kW ] net
where:
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International Journal of Applied Engineering Research, ISSN 0973-4562 Vol. 9 No.23 (2014) © Research India Publications; http://www.ripublication.com/ijaer.htm g
= generator efficiency
Calculation of the generator capacity can be done using the following equation [8]. Generator Power PG
Output Power kW AxB xC xD
where: A - Temperature Factor Altitude B - Altitude Factor C - ELC Correction Factor D - Power Factor Parameters A, B, C, and D are predetermined factors based on the condition under consideration. Parameters A, B, C and D are determined by the height in the study area is 4000 m with a room temperature of 50oC , so that the value of A = 0.92, B = 0.80, C = 0.88 and D = 0.8. In the remaining 142 villages the generating capacity calculations have been performed using statistical methods. The overall condition of the research object is measured based on the variables of the whole object under consideration, such as the average size of the used variables, i.e. the output of the generator, turbine output, head and discharge. Estimation of the variables valueof the whole research is not always as accurate as the actual value, so that the estimation results are to be expressed in the form of a certain level of accuracy indicating certain chance of α of making mistakes [9]. The accuracy level or confidence range SK, indicating the estimation range which covers the whole objects under consideration, can be obtained using (2.5). s s x t / 2 SK x t / 2 (2.5) n n where:
3. RESULTS AND DISCUSSION Mapping of the micro-hydro energy potential has been carried out in 4 districts in the Maluku region, namely Central Maluku, West Seram, North Buru and South Buru. Direct survey has been done on site of 13 villages, whereas data of the remaining locations have been obtained with the help of coordinate data of location generated using Geographic Information System and elevation data retrieval on the Google Earth Map system. This latter method is taken based on the consideration of time and cost availability. GIS proves to provide benefits in the determination of location of 216 villages in this study. 3.1 Calculation results of power generation potential based on direct survey in 13 villages The calculation results of power generation potential based on direct survey at 13 villages under study are shown in Table-1. Table-1. The power generation potential in 13 villages
Village name Rohomoni Tamilow Morela Saleman Piliana Niniari Waesala Rumahkay Uneth Waekatin Fatmite Nanali Ilath Total Average
(sample) S : standard deviation : average value of the overall object of research : error tolerance s : tolerance limits of the accuracy level t t / 2
n
: statistics t table w.r.t. the error degree of α
The number of samples can be determined based on the desired level of error , e.g. 1%, 5%, or 10%. [10]. In this study, the error rate (α) is determined based on the relationship between the total number of objects of the study (N) and the number of samples (n). Number of samples (n) is a direct result of research in 13 villages and captured elevations in Google Earth Map in 216 villages, bringing the total samples of 229 villages. The overall number of the objects of study (N) in the four regencies is 371 villages. Error tolerance is determined based on the equation (6).
(
n*N
where: N = the total number of objects of research n = number of samples Based on [10], a level of accuracy with an error tolerance of 4% or by 96% of confidence level has been presumed for estimating the average output of the generator, turbine output, head and discharge of the objects under study.
x : average value of the part of the overall object of study
/2
N n
HNet (m) 11.75 5.48 18.80 21.17 5.17 7.52 11.28 9.12 7.52 4.23 6.58 11.28 7.99
Qnet (m3/s) 0.81 0.63 0.64 0.39 0.51 1.82 0.76 1.06 1.39 1.20 1.01 0.81 0.59
9.84
0.89
PT (kW) 71.71 26.18 90.82 62.47 19.77 103.56 64.99 72.72 79.08 38.41 50.36 68.78 35.72 784.53 60.35
Pe (kW) 62.39 22.77 79.01 54.35 17.20 90.09 56.54 63.26 68.80 33.41 43.82 59.82 31.07 682.54 52.50
Calculation of the power generation potential of 13 villages has been done using (2.1) and (2.2). Turbine output power and the generator output are derived from the river flow rate and head which had been measured on site directly. The total generated power potential in 13 villages is 682.54 kW, with an average of 52.50 kW, the largest power of 90.09 kW and the smallest power of 17.20 kW. The head values vary between 4.23 m and 21.17m, while the river discharge between 0.39 m3/s and 1.82 m3/s.
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International Journal of Applied Engineering Research, ISSN 0973-4562 Vol. 9 No.23 (2014) © Research India Publications; http://www.ripublication.com/ijaer.htm 3.2 Calculation results of power generation potential based on GIS and Google Earth Map data retrieval of 216 villages The head has been calculated using the elevation data retrieved from GIS and Googel Earth Map. The water flow rate has been obtained from the local rainfall data and watershed area. Calculation of power generation potential based on the obtained values of head and water flow rate in 216 villages under study shows a total power potential of 36193.48 kW, with an average of 333.58 kW, the largest power of 374.50 kW and the smallest power of 36.15 kW. The head average is 11.34 m and the average of water flowflow rate is 2.23 m3/s.
potential in the remaining 142 villages has been estimated to vary between 21240.786 kW up to 24491.592 kW Exploiting the of micro-hydro power potential previously known would only contribute to 1.93% of the total power need fulfillment, while the mapping result of this study shows the huge potential of reducing current dependence on fossil-fueled power plants. Total power calculation using all the three methods under consideration in this study results in the total generation potential of 61.11 MW. Based on the projection of the electric energy supply by PLN in the next 5 years in Maluku region, which is of 95.5 MW, this potential accounts for fulfilling about 64.4% of the total electrical power needs.
3.3 Analysis results of power generation potential of 142 villages using statistical methods The analysis of power generation potential of the remaining 142 villages under consideration was performed with statistical methods. The parameters used in this analysis is the average value of generator output power, turbine output, head and discharge, while the standard deviation is obtained based on the number of samples used, i.e. 229. Based on the presumed level of accuracy with an error tolerance of 4% or by 96% of confidence level, the estimation of the average output of the generator, turbine output, head and water discharge id sone as follows. - Analysis of the turbine output power:
4. CONCLUSION Based on the analysis of data and calculation results, some conclusions can be drawn as follow: The total generated power potential in 13 villages is 682.54 kW, with an average of 52.50 kW, the largest power of 90.09 kW and the smallest power of 17.20 kW; The total generated power potential in 216 villages is 36193.48 kW, with an average of 333.58 kW, the largest power of 374.50 kW and the smallest power of 36.15 kW; At 96% of confidence level or an error tolerance of 4%, the total generated power potential in 142 villages is estimated to vary between 21240.786 kW and 24491,592 kW; The total microhydro power generation potential in 4 regencies of Maluku region, i.e. Central Maluku, West Seram, South Buru and North Buru, is equal to 61.11 MW; Exploiting the full potential of microhydro energy previously known would fulfill only 1.93% of the total needs, while the results of mapping show the contribution of 64.4% of the total electrical power needs in Maluku region, based on the projection of the electric energy supply by PLN in the next 5 years, amounting to 95.5 MW; The results of microhydro power generation mapping indicate a potential reduction of dependence on electricity generation from fossil fuels, currently dominating in the Maluku region.
85 , 265 85 , 265 185 ,09 2,330 228 228
SK ( 96 %) 185 ,09 2 ,330
SK ( 96 %) 171,932 198 , 247
-
Analysis of the generator output power: 74 ,181 74 ,181 161, 03 2 ,330 228 228
SK ( 96 %) 161, 03 2,330
SK ( 96 %) 149 ,583 172 , 476
-
Analysis of water flow discharge : 0 ,370 0 ,370 SK ( 96 %) 2 ,16 2 ,330 2 ,16 2 ,330 228 228 SK ( 96 %) 2 .102 2 , 217
-
Analysis of head value:
REFERENCES
4,604 4,604 SK ( 96 %) 11, 26 2,330 11, 26 2,330 228 228 SK ( 96 %) 10 ,549 11,970
The obtained turbine output power varies from 171.932 kW to 198.247 kW, whereas the generator power output varies between 149.583 kW and 172.476 kW, with the required generator capacity varies between 332.871 kVA and 288.688 kVA. The water discharge varies between 2.102 m3/s and 2.217 m3/s, whereas the head varies between 10.549 m and 11.970 m. At 96% of confidence level with 4% of error tolerance, the power generation
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International Journal of Applied Engineering Research, ISSN 0973-4562 Vol. 9 No.23 (2014) © Research India Publications; http://www.ripublication.com/ijaer.htm Hydropower Potential for Micro Hydro”, Maluku, 2012. [4] PT. PLN (Persero), “Electricity Power Supply Business Plan (RUPTL) for 2010 - 2019”, Jakarta, 2010, pp 650-653. [5] http://bisda.dpu.ntbprov.go.id/index.php?option=com_ content&view=article&id=156&Itemid=160, being accessed on September, 18, 2014. [6] Asdak, C., ”Hydrology and Watershed Management”, Yogyakarta: Gadjahmada University Press, 2002. [7] Javed, A. C.,”Design of a cross-flow turbine for micro-hydro power application”, Proceedings of ASME 2010 Power Conference, Chicago, Illinois, USA, July 2010.
[8] Sitompul, R., “Training Manual on the Right Application of Renewable Energy Technology in Rural Communities”, Jakarta, 2011. [9] Walpole, Ronald E., Raymond H. Myers, Sharon L. Myers, and Keying Ye, “Probability and statistics for engineers and scientists”. Vol. 5. New York: Macmillan, 1993. [10] Sevilla, Consuelo G., Jesus A. Ochave, Twila G. Punsalan, Bella P. Regala, and Gabriel G. Uriarte, "Research Methods", Jakarta: UI Press, 1993. [11] http://analisisstatistika.blogspot.com/2012/09/menentukan-jumlahsampel-dengan-rumus.html, being accessed on May 25, 2014.
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