Photovoltaic Deployment Experience and Technical Potential in Indonesia's Java-Madura-Bali Electricity Grid
Abstract and Figures
The largest and most established electricity grid in Indonesia, the Java-Madura-Bali (JAMALI) interconnected system, accounts for around 60% of the country's total electricity demand. Given continuing high demand growth and the slow addition of major generators in recent years, energy users served by the JAMALI grid are experiencing inadequate and unreliable electricity supply. There is growing interest in the potential of renewable energy to help mitigate the risks of continued fossil fuel dependence, improve system reserve margins, and diversify energy sources to enhance supply security, as well as improve environmental outcomes. The Indonesian government's vision to increase the renewable energy contribution to Indonesia's energy mix to 23% by 2025, raises the question of what role utility-scale photovoltaic (PV) generation might play in meeting these challenges and opportunities. Indonesia has an excellent solar resource, while PV costs have fallen markedly over recent years. Still, the JAMALI's present generation mix is dominated by low cost and relatively abundant coal and gas. This paper reviews the current status and future potential of utility PV in the JAMALI area. Given limited existing studies on solar irradiation and PV mapping for the Indonesian context, we first present a detailed spatial mapping of PV output potential for the JAMALI region including hourly temporal behavior-a key factor for assessing PV integration challenges and opportunities. This proposed spatial PV output mapping is provided at a 5 km 2 resolution, using weather data derived from the NASA MERRA-2 satellite database and the Global Solar Energy Estimator model. The mapping provides a preliminary indication of appropriate utility-scale PV locations in the JAMALI context. An open-source generation mix model, NEMO, is then used to assess the potential role of utility PV in least cost future generation portfolios for JAMALI. Results suggest that PV could play a useful role, depending on future technology, fuel and carbon prices, and demand growth. On this basis, current policies and regulations relevant to deployment of large scale PV are described and a number of key challenges for PV deployment and possible opportunities for reform are identified.
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... In this regard, the solar PV output temporal dataset is critical; for example, assessing potential PV contributions in electricity industry generation capacity planning (Tanoto et al., 2020) or analyzing the reliability-cost trade-offs for electricity industry planning with high PV penetrations in emerging economies (Tanoto et al., 2021). Understanding the long-term temporal variability of solar PV modelling is crucial for system planners and operators who analyze system ramp-up and ramp-down capabilities, particularly at high solar penetration levels (Kumar et al., 2022;Tanoto et al., 2017). ...
This study presents clustering-based assessments of solar attributes for locating potential solar photovoltaic (PV) power plant sites using k-means and density-based spatial clustering of applications with noise (DBSCAN) by examining the yearly average single-attribute and three-attribute clustering on a dataset of long-term hourly-based direct and diffuse irradiation, ambient temperature, and solar PV power output from 2005 to 2022. Three-attribute clustering enables stakeholders to better understand the characteristics of a cluster by collectively identifying three solar attributes and the magnitude of each attribute in an area or cluster. The presence of this information, which constitutes the clusters, suggests that these attributes have different effects on solar PV output power in different clusters. Although k-means is an effective method for investigating potential locations for PV power plant placements, DBSCAN offers users an alternative method for accomplishing a similar goal. In the case of three-attribute clustering of direct irradiation with k-means and DBSCAN, the 18-year mean value of clusters with the highest yearly average value is achieved at very similar values of 0.305 kW/m2 and 0.310 kW/m2, respectively. It turns out that only six years of direct irradiation had an annual mean value of less than 0.305 kW/m2. This finding implies that in the long run, the solar resources in terms of direct irradiation will typically surpass 0.3 kW/m2/MW installed capacity over all areas suitable for PV power plants. While focusing on the Java-Bali region, Indonesia, the findings, and methods appear to be of broader interest to policymakers, particularly in developing countries where solar PV is considered an option for sustainable energy generation.
... The solar PV system used for the calculation process was large-scale ground-mounted at a PV azimuth of 0 • and a PV tilt of 12 • . The monthly capacity factor data is collected for December with the value of 13.9% [37], [38]. A megapack by Tesla was used in the battery system to store excess electricity. ...
Renewable-power-assisted CO2 capture and utilization (CCU) for methanol synthesis has gained significant attention. This study assesses the techno-enviro-economics of methanol synthesis via CO2 hydrogenation using renewable hydrogen from photovoltaic (PV)-based electrolysis and CO2 originating from natural gas field processing. The study was performed under two scenarios: PV electrolysis with a battery and without a battery, using grid electricity. The proposed process system was simulated using Aspen HYSYS v11. A proton exchange membrane (PEM) electrolyzer was chosen for electrolysis. Methanol synthesis via CO2 hydrogenation was modeled using kinetic models by considering both CO and CO2 as carbon sources. An economic analysis using a levelized cost process and an environmental assessment of CO2-eq emissions were performed. The results show that the overall energy efficiency of integrated hydrogen production and methanol synthesis before and after the heat integration process using a heat exchanger network (HEN) were 48.39% and 55.16%, respectively. From an economic perspective, the methanol production cost was 1040.17 and 1669.56 $/tonne-MeOH for the PV–grid and PV–battery scenarios, respectively. From an environmental perspective, the CO2-eq emissions from the whole process were 0.244 and − 0.016 kg-CO2-eq/MJ-MeOH for the PV–grid and PV–battery scenarios, respectively.
... The data is obtained from Renewables Ninja (RN), an online renewable energy simulation tool, from which an hourly PV output trace can be obtained, based on the NASA MERRA2 weather dataset [17]. A PV trace is then provided to NEMO for six selected locations across the Java-Bali grid, one in each province, following a methodology used in earlier studies [18,19]. ...
This study examines the performance of a solar power plant with a total capacity of 125 KWp, which operates for one year in Blora, Central Java. The ability of this power plant is a total of PV modules with 20 kWp, ten kWp, and five kWp capacities spread across eight locations. The annual performance of the rooftop solar power plant is measured automatically by the converter installed in each module. The resulting data from inverters are compared to the meteorological conditions from the meteorological agency.
This research will investigate the influence of climate on the power generated, the efficiency of the equipment in a power plant, and the effect of pseudo motion of the sun. It was found that there were variations in energy output throughout the year, and it was concluded that the maximum annual energy was produced in July-August. In addition to weather, other factors need to be investigated further to determine the causes of variations in solar PV output.
Electricity industries in emerging economies face particular challenges in delivering affordable, environmentally sustainable, and secure power given growing demand and limited financial resources. While supply reliability is often poor and emission reductions given lower priority, solar and wind are now amongst our cheapest supply options but highly variable. Our study seeks to demonstrate the potential value of trading-off reliability standards against higher renewables and lower industry costs in future generation planning. We use an open-source, evolutionary programming-based, capacity expansion planning tool, NEMO, to solve least cost generation mixes for Indonesia’s Java-Bali grid in 2030. We explicitly test the cost and emission impacts of reliability targets of 0.005% to 5% unserved energy (USE), modelled as both a hard optimization constraint and a penalty price on USE in the cost function. Our results highlight that lower reliability targets can increase solar and wind penetrations, reducing CO2 emissions while reducing industry costs. Both methods of incorporating reliability delivered similar outcomes but pricing USE had some advantages for optimization over hard constraint setting. While the impacts of lower reliability on consumers requires careful consideration, our study highlights the potential cost and emission implications of arguably unrealistic reliability targets in generation planning for emerging economies.
Wind and solar are increasingly cost-competitive as well as environmentally less harmful alternatives to the fossil-fuel generation that dominates most electricity industries. However, their highly variable and somewhat unpredictable output still requires high levels of dispatchable plants to ensure demand can be met at times of low renewables availability. While this capacity overhead has associated costs, it does offer potentially useful outcomes for dynamic operating reserves. We present a method for assessing these potential outcomes in electricity industry planning. We use an evolutionary programming-based capacity expansion model, NEMO, that solves least-cost generation mixes through full operational dispatch of candidate solutions, using high-temporal resolution demand and wind and solar profiles, over a year or more. We apply our method through a case study of the Java-Bali grid, considering future scenarios both with and without variable renewables, and under different carbon pricing scenarios, reliability targets, and minimum operating reserves requirements. Our study suggests that not only might high renewable penetrations reduce industry costs and emissions, their inclusion provides significantly higher operating reserves over most of the year, hence the ability to cover unexpected plant failures and other disruptions. Lower reliability targets reduce this capacity overhang but still see improved operating reserves.
Solar PV is rapidly growing globally, creating difficult questions around how to efficiently integrate it into national electricity grids. Its time-varying power output is difficult to model credibly because it depends on complex and variable weather systems, leading to difficulty in understanding its potential and limitations. We demonstrate how the MERRA and MERRA-2 global meteorological reanalyses as well as the Meteosat-based CM-SAF SARAH satellite dataset can be used to produce hourly PV simulations across Europe. To validate these simulations, we gather metered time series from more than 1000 PV systems as well as national aggregate output reported by transmission network operators. We find slightly better accuracy from satellite data, but greater stability from reanalysis data. We correct for systematic bias by matching our simulations to the mean bias in modeling individual sites, then examine the long-term patterns, variability and correlation with power demand across Europe, using thirty years of simulated outputs. The results quantify how the increasing deployment of PV substantially changes net power demand and affects system adequacy and ramping requirements, with heterogeneous impacts across different European countries. The simulation code and the hourly simulations for all European countries are available freely via an interactive web platform, www.renewables.ninja.
The first objective of this study is to determine the theoretical potential of solar irradiation in Indonesia by using artificial neural networks (ANNs) method. The second objective is to visualize the solar irradiation by province as solar map for the entire of Indonesia. The geographical and meteorological data of 25 locations that were obtained from NASA database are used for training the neural networks and the data from 5 locations were used for testing the estimated values. The testing data were not used in the training of the network in order to give an indication of the performance of the system at unknown locations. In this study, the multi layer perceptron ANNs model, with 9 inputs variables i.e. average temperature, average relative humidity, average sunshine duration, average wind speed, average precipitation, longitude, latitude, latitude, and month of the year were proposed to estimate the monthly solar irradiation as the output. Statistical error analysis in terms of mean absolute percentage error (MAPE) was conducted for testing data to evaluate the performance of ANN model. The best result of MAPE was found to be 3.4% when 9 neurons were set up in the hidden layer. As developing country and wide islands area, Indonesia has the limitation on the number of meteorological station to record the solar irradiation availability; this study shows the ANN method can be an alternative option to estimate solar irradiation data. Monthly solar mapping by province for the entire of Indonesia are developed in GIS environment by putting the location and solar irradiation value in polygon format. Solar irradiation map can provide useful information about the profile of solar energy resource as the input for the solar energy system implementation.
The solar radiation climate of Indonesia was surveyed from 1969 to 1976 as part of a project of the Meteorological and Geophysics Centre, Jakarta. Summaries of this survey have been presented in reports of the Centre for Meteorological and Geophysics primarily from the point of view of climatic studies. The study reported in the present paper has processed this data into computer compatible form and generated representative data years for use in the analysis of the performance of solar energy collecting systems. Comparison of irradiation conditions in Indonesia and neighbouring countries is also presented.
This study evaluates the incremental costs of higher levels of renewable energy (RE) supply using an optimisation tool to find least cost electricity generation portfolios. The Australian National Electricity Market (NEM) in 2030 is used as a case study for exploring various generation portfolios from low to high shares of RE, low to high greenhouse gas emissions caps, and low to high carbon prices. Incremental costs are found to increase approximately linearly as the RE share grows from zero to 80%, and then demonstrate a small degree of non-linear escalation, related to the inclusion of more costly renewable technologies such as solar thermal electricity. Similarly, costs increase approximately linearly as a greenhouse gas emissions cap is lowered from 150 megatonnes (Mt) to 30 Mt, and then demonstrate a small degree of non-linear escalation for caps below 30 Mt. However, in both cases this escalation is moderate, and does not appear to provide a strong argument for long-term policies that aim for RE shares lower than 100%, or electricity sector emissions caps higher than zero as one option for rapid decarbonisation.
Photovoltaic (PV) energy could play a large role in increasing the electrification ratio and decreasing greenhouse gas emissions in Indonesia, especially since Indonesia comprises over 17,000 islands which is a challenge for the distribution of fuels and modern grid connection. The potential of grid-connected PV depends on, a.o. population, electrification ratio, irradiance, electricity demand, electricity generation costs and the urbanization ratio. Large spatial differences exist for these factors in Indonesia, therefore this study aims to assess the energetic potential and cost-effectiveness of grid-connected PV in Indonesia on a provincial level. Taking restrictions of the electricity demand during day-time and a minimal base load of conventional power systems into account, the total potential of grid-connected PV systems is about 27 GWp, generating 37 TWh/year, which is about 26% of the total electricity consumption in Indonesia over 2010. In the eastern provinces of Indonesia the LCOE of PV in grid-connected urban areas is lower than the cost of present electricity generation and could be a viable alternative if excluding high subsidies for electricity production.
Worldwide interest in the deployment of photovoltaic generation (PV) is rapidly increasing. Operating experience with large PV plants, however, demonstrates that large, rapid changes in the output of PV plants are possible. Early studies of PV grid impacts suggested that short-term variability could be a potential limiting factor in deploying PV. Many of these early studies, however, lacked high-quality data from multiple sites to assess the costs and impacts of increasing PV penetration. As is well known for wind, accounting for the potential for geographic diversity can significantly reduce the magnitude of extreme changes in aggregated PV output, the resources required to accommodate that variability, and the potential costs of managing variability. We use measured 1-min solar insolation for 23 time-synchronized sites in the Southern Great Plains network of the Atmospheric Radiation Measurement program and wind speed data from 10 sites in the same network to characterize the variability of PV with different degrees of geographic diversity and to compare the variability of PV to the variability of similarly sited wind. The relative aggregate variability of PV plants sited in a dense 10 x 10 array with 20 km spacing is six times less than the variability of a single site for variability on time scales less than 15-min. We find in our analysis of wind and PV plants similarly sited in a 5 x 5 grid with 50 km spacing that the variability of PV is only slightly more than the variability of wind on time scales of 5-15 min. Over shorter and longer time scales the level of variability is nearly identical. Finally, we use a simple approximation method to estimate the cost of carrying additional reserves to manage sub-hourly variability. We conclude that the costs of managing the short-term variability of PV are dramatically reduced by geographic diversity and are not substantially different from the costs for managing the short-term variability of similarly sited wind in this region.
In this paper the monthly average daily global solar radiation correlation applicable to the Indonesian climatic region is presented. The correlation developed is based on the meteorological data collected from seven meteorological stations, namely: Banjarbaru, Denpasar, Jakarta, Kupang, Manado, Palembang and Semarang. The correlation developed evolves from the Sayigh's “Universal Formula” with a slight modification in the form of a correction factor (ICF) to suit the Indonesian climatic conditions.
As a part of a program to explore technological options for the transition to a renewable energy future, we present simulations for 100% renewable energy systems to meet actual hourly electricity demand in the five states and one territory spanned by the Australian National Electricity Market (NEM) in 2010. The system is based on commercially available technologies: concentrating solar thermal (CST) power with thermal storage, wind, photovoltaic (PV), existing hydro and biofuelled gas turbines. Hourly solar and wind generation data are derived from satellite observations, weather stations, and actual wind farm outputs. Together CST and PV contribute about half of total annual electrical energy supply.
The total solar energy radiation and sunshine duration data collected by the Indonesian Institute of Meteorology and Geophysics (IMG) during 14 years are discussed (1965–1979). For further analysis, it is supported by the measurement of the total radiation and the diffuse radiation on the horizontal surface and also the total radiation on the tilted surface in the Physics Department of the University of Indonesia.By using the data, we calculated and constructed the diffuse solar radiation, clearness index histogram, space insolation distributions, daily, monthly and yearly diagrams on the basis of reports by M.C. Pereira [1].Other aspects of using flat plate collector concentrators, and also the methods of global solar radiation estimation in Indonesia by using the 14 years data available are discussed in this paper.
Solar resource and photovoltaic power potential of Indonesia
- Solargis
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DC: World Bank (ESMAP).