Spatial optimization of the economic benefits of the potential hydropower locations: study case upper citarum river

. Hydropower is a renewable energy source that provides clean energy services and contributes to climate change mitigation by replacing fossil fuel energy production sources. The Upper Citarum Watershed in West Java, Indonesia, is described as a giant basin known as the Bandung Basin, which is type by mountainous relief with an elevation of 750-2300 meters above sea level, a slope of 30-90%, and a radiating river flow pattern. This study focuses on the potential of small hydropower with a run-of-river scheme that acts as a filler for the study of hydropower potential with a pump storage scheme by the Australian National University. Climate data in the study area were analyzed using the SWAT model to obtain Cumulative Discharge Frequency and identify potential discharge by adopting the method of previous studies. The results identified 7 SHPs with P exceeding 500 kW and below 2000 kW. BHUMI ATR BPN can predict land value and land cover in areas designated for hydropower development. The findings suggest improvements in aspects such as proper forecasting, on-the-ground valuation, and calculations relating to economically viable sustainability.


Introduction
The IPCC in 2018, reported that the challenge of keeping the Earth's temperature rise below 1.5°C is becoming increasingly serious.At the current rate, warming will continue to increase until 2040 [1], causing both hydrological and other aspects of climate change [2].These changes are also due to continued population and economic growth, which increases the demand for sustainable renewable energy as an alternative measure in the conventional use of fossil fuel reserves [3].Renewable energy sources can provide clean energy services and contribute to climate change mitigation by replacing fossil fuel energy production sources.The importance of renewable energy is associated with all future climate change scenarios, as results the penetration of renewable energy on a significant scale in the energy network [4].
The Upper Citarum Watershed in West Java, Indonesia (Figure 1) is described as a giant basin known as the Bandung Basin, characterized by a mountainous relief with an elevation of 750-2300 m above sea level, an upper slope of 30-90%, and radiating river flow pattern [5].The Upper Citarum River has potential for small hydropower development, with potential of 700 megawatt.A result of population growth, government continues to receive requests for additional capacity of up to 1,400 megawatt (MW) [5].The Indonesian government stated in PLN's 2021-2030 RUPTL that hydropower will be one of the backbones of the national net zero strategy, expected to be the main source with 25.6% of the national electricity supply by including mini-hydropower, whose potential is currently estimated at 95 gigawatt (GW) [3].Small hydropower can contribute significantly to meeting global renewable energy targets [6].The Australian National University (ANU) has analyzed the potential for large hydropower with pump storage schemes.The purpose of this study is to obtain the potential of small hydropower with a run-of-river (ROR) scheme that acts as a filler for the study of hydropower potential with a pump storage scheme conducted by ANU.Thus, river segments that are not included in pump storage can be known for their ROR potential.
Due to hydropower development there are often complaints regarding inadequate and unfair compensation also the difficult resettlement site [7].For this reason, this study focuses on land use in selecting potential hydropower sites and economic data as input to estimate the cost of planning potential hydropower sites to avoid potential social and cultural problems and create economic benefits.

Study location
The Upper Citarum River is located between 107 o 10' -108 o 00' E and 6 o 40' -7 20' S, covering an area of about 1700 km 2 (Fig. 1).Administratively, it covers the area of West Bandung Regency, Bandung City, Cimahi City, and Sumedang Regency [8].The Citarum River contributes greatly to the economic activities of the people of Bandung Regency with various activities especially land use such as agricultural, tourism, and industrial activities [9].As part of the Bandung Basin, which has a rainfall of 2,300 mm per year, the Upper Citarum River West Java with a length of 6,614 km 2 and a width of 269 km has a meander relief shape with 4 existing hydropower plants [5,10].The high human population is feared to affect riverbank land use and add constraints as a potential hydropower development area.Therefore, identifying potential hydropower points in residential areas and rice fields affects the prediction of the research.

Rainfall data
Satellite-based rainfall estimates provide complement measurement over a wide area having few or even no in situ data [11].In Kardhana et al [12], climate data used Climate Forecast System Analysis (CFSR) for 10 years from January 1st 2004 until December 31st 2011.The CFSR grid data is corrected by observation data in 31 rainfall station from BMKG, PLN, and PUSAIR utilized as data input to predict water balance in a watershed.

Land used data
The land use data utilized in this study was sourced from Peta Rupa Bumi Indonesia by the Geospatial Information Agency (BIG) with scale 1:25.000 in 2011.It is open source, can accessing on http://tanahair.indonesia.go.id (accessed on 25 August 2023).The content and classification of RBI map data types are standardized by scale, thus that uniformity of data and information can be maintained [13].

Topography data
Topographic data is digital data from remote sensing, commonly called Digital Elevation Model (DEM).In this research used as input for hydrological analysis, the DEM used comes from the NASA Shuttle Radar Topographic Mission (SRTM) with a resolution of 90 m at the equator.With data availability of ± 80% of the earth's surface, SRTM DEM is one of the reliable global data and is distributed free of charge [12].

Economic data
The land value of land parcels and information according to the layers listed can be obtained.The information about the value of land in a field from a Web GIS-based land big data, namely www.bhumi.atrbpn.go.id.The information provided is the result of a super impose of two layers, namely land parcels and ownership information, type of rights, NIB, use and land area.Meanwhile, to find out the value of a land parcel, the web provides a data set of the value of a zone [14].

Multi optimization
Determination of hydropower potential locations calculated by diversion algorithm in Python programming.Adopting Kardhana [12], river grid were sampled every 30 pixel, each sample has one selected pixel spot which has maximum P. The value data land used from ATR BPN helps select feasible choices among potential hydropower locations for land compensation cost.This work proposes a framework to guide the multi-objective optimal design of a small run-of-river hydropower plant, which simultaneously maximizes its economic value and minimizes its impact on hydrological connectivity.Determining variables in the optimization are the maximum power from flow processed by the plant capacity (Q) with reliable discharge and the possible location [6].

Methodology
This research focuses on the Upper Citarum Watershed to expect the initial representation in planning the potential location of hydropower plants with considering land used and economic benefits analysis.The step of this method can be seen as follows below.The schematic workflow follows 4 step: collecting data, utilized diversion algorithm for determining initial potential hydropower location, applied spatial data overlay to land cover and land value zone in BHUMI ATR BPN, and results benefits cost analysis for final potential location (Fig. 2).The data obtained were analyzed using the diversion algorithm in Python programming.The analysis results show the location of potential hydropower plants and the potential power that can be generated, the points are then layered into BHUMI ATR BPN to calculate the cost of hydropower development based on land value as shown in Figure 3.a.Furthermore, based on electricity production and electricity selling value, the amount of hydropower profit can be obtained.

Results
The diversion algorithm is implemented within a Python program that utilizes collected DEM (Digital Elevation Model) and discharge data.Climate data from the study area is analyzed using the SWAT model to calculate cumulative discharge frequency (CDF) and identify potential firm flow.Following this, the carrier channel tracing begins by generating a grid at the river's intake, employing 90 m DEM SRTM data for each pixel size.The tail race location is determined by selecting the river pixel with the lowest elevation among its neighbors.The horizontal penstock length is the predefined distance between this neighboring river pixel and the head pond.The process entails sequentially picking lower pixels from the head pond to establish the route, halting when no further lower pixel is available.These chosen pixels constitute the headrace.The river pixel's potential head is established by selecting the highest head from the available alternatives in the head pond, with routing disallowing loops.Meanwhile, predicting potential hydropower locations requires resampling procedures, which may yield similar spots but differing probabilities (P) due to reasonable changes in CDF [12].To enhance feasibility, selected spots with P below 100 kW are discarded.The outcome identifies 7 SHPs with P exceeding 500 kW with nearly half possessing firm power surpassing 1600 kW which is located in large tributaries as shown in Figure 3.b the layer data applied on https://re100.eng.anu.edu.au/global/accessed on (September 1, 2023).The study for diverting flow to generate hydropower from these locations will require significant cost and thus be unlikely feasible also requires additional variables.When the point results have been placed in the BHUMI data, the addition of data catalogues in the form of protected paddy fields, raw paddy fields, land use, and land value zones.During the overlay process, potential locations located in residential areas and rice fields are said to be eliminated.The filtered locations have land values that will be used as economic data for estimating the cost of hydropower development.In addition, it can also be calculated the profit of hydropower from the value of annual production against the cost of buying and selling electric power which refers to the amount of the cost of supplying electricity generation in the decision of the Minister of Energy and Mineral Resources of the Republic of Indonesia Number 169.K / HK.02 / MEM.M in 2021.From both aspects of the calculation, the feasibility level of hydropower potential points can be determined.

Conclusions
This research focuses on improving the methodology in finding potential hydropower locations with the appropriate ROR scheme.The diversion algorithm can develop analysis study to predict suitable locations for hydropower potential.The findings from the analysis of potential hydropower sites based on ROR considerations address the deficiency in available locations compared to the ANU global renewable energy map, which focuses on pump storage (shown in Figure 3.b) To get clear results after doing the layer, unfortunately the BHUMI web still does not have a feature to download the image of the layer results.Moreover, the BHUMI ATR BPN has the capability to predict the land value in the designated areas for hydropower development.Evaluations suggest enhancements in aspects like precise forecasting, on-site assessments, and calculations of economically viable sustainability.