Simulation to Attain Optimal Composition of Power Plant Technology in Java-Madura-Bali up to year of 2026 11 Ronald Winardi 1 *, PY.TopoSuprihadi 2, and Sudi Ariyanto 3 Physics Department, Faculty Science and Mathematics, Universitas Pelita Harapan,, Tangerang, Indonesia 2 Physics Department, Faculty Science and Mathematics, Universitas Pelita Harapan,, Tangerang, Indonesia 3 Division for Preparatory Management of Nuclear Power Plant- BATAN, Jakarta, Indonesia, *E-mail: ronald.w.liem@gmail.com Abstract SIMULATION TO ATTAIN OPTIMAL COMPOSITION OF POWER PLANT TECHNOLOGY IN JAVA- MADURA-BALI UP TO YEAR OF 2026. Java, Madura, and Bali power generating system has been considered as one interconnected system. Bali-Java and Madura-Java are connected with underwater 150 KV transmission cable. While in land they are connected with 500KV above the ground transmission cable. Electricity demand in this area grows more than 7.5% annually. Total investment until 2025 is approximately US$ 45 billion (PEUI2006). With such large investment, it is essential to have well-planned power plant procurement by taking into account aspect of energy resources availability, economic, social, and environment. Analysis is done by using WASP. The result will show the optimal composition among available thermal technology alternatives (Nuclear, Coal, LNG, Geothermal, HSD) to meet the system s needs. By iterative mean WASP will perform the dynamic programming algorithm with our constraint. This simulation is conducted in three basic possible scenarios. First scenario does not concern about emission. Second scenario will include emission mitigation of the dominant type power plant as the result in the first scenario. The last scenario uses projected emission limitation each year. The result shows a rising in alternative energy urgency. To mitigate the emission and economic excess, the system has to start considering to use alternative energy such as geothermal and nuclear energy to at least 11% of the total energy produced. Keywords: Jamali (Java-Madura-Bali), WASP, Nuclear power, coal, LNG, geothermal, HSD, MFO. 1. Introduction Power generation system in Java-Madura-Bali (JAMALI) is considered as one interconnected system. It consume above 60% percent of all power generated in Indonesia. Good planning is needed to make sure such large investment is efficient and effective. The planning covers the quantity of a type of power plant that should be procured. Adequate capacity system planning will support 7.2% annual electricity demand growth in Java- Madura-Bali. The consequences will be good for economic and wealth of the people. JAMALI system is has to support the industrial need of electricity in Indonesia, so its reliability is having direct consequences to Indonesia GNP, for example. With this level of importance, it capacity need to be secured in quantity and in reliability. This project tries to fulfill the electricity demand by using existing competitive technology. They are coal, LNG, geothermal, HSD, MFO and Nuclear technology. Geothermal and nuclear technology represent alternative energy source. Although nuclear is not popular in Indonesia but it offers higher efficiency in delivering higher capacity with lower emissions. All the six alternative candidates are having plus and minus for power generations. To attain system s goals, the optimal linear combination of this plus and minus is needed to be found. Java, Madura, and Bali are also having the highest people density in Indonesia. So people factor need to be considered. The side effect of power generation to its people also needs to be reduced. Hence, despite capacity adequacy, lower emission system is also becoming the goal of this project. All 1 as undergraduate thesis in Physics Department, Faculty Science and Mathematics Universitas Pelita Harapan 2007 359
the existing plant and future projection related data are taken from PLN and government. It is not covering other captive power. Nevertheless it is still the majority of JAMALI Power generation capacity. 1.2 Electricity in Java, Madura, Bali Electricity demand data is built with assumption of 6.3% population growth in 2005-2025. Electrification ratio is projected as 93% in 2025[3]. Peak load will reach 64MW in 2026 by 7.2% average annual growth. Proportions of consumption per sector growth are: 1. Household 4% 2. Commercial 10% 3. Public 2.5% 4. Industry 8% The system s load characteristic will be inputted in form of load duration curve. Load duration curve is a normalized form of a year long half hour load data. For this study, a year long of data is divided into four quarterly periods, each with its own load duration curve (LDC). All combined existing power plant can produce up to 16 MW peak load, the location of the power plants is shown in fig 1.1-1.4 below. Figure 1.1. Location map of existing power plant in West Java, DKI Jakarta, and Banten 1 Muara Karang 1 13 Suralaya2 2 Muara Karang 2 14 Suralaya3 3 Muara Karang 3 15 Solok 1 4 Muara Tawar 1 16 Solok 2 5 Muara Tawar 2 17 Kamojang 1 6 Muara Tawar 3 18 Kamojang 2 7 Priok 1 19 Drajat 1 8 Priok 2 20 Drajat 2 9 Priok 3 21 Sunyaragi 1 10 Cilegon 22 Wayang Windu 11 Cikarang 23 Sunyaragi 2 12 Suralaya1 24 Cilacap 1 25 Cilacap 2 26 Tambaklorok 1 27 Tambaklorok 2 28 Tambaklorok 3 29 Dieng 30 Tanjung Jati Barat Figure 1.2. Location map of existing power plant in Central Java, DI Yogyakarta 360
Figure 1.3. Location map of existing power plant in East Java 30 Java Power 31 Paiton 32 PEC 33 Gresik 1 34 Gresik 2 35 Gresik 3 36 Gresik 4 37 Perak 38 Grati 1 39 Grati 2 40 Gilitimur 41 Gilimanuk 42 Bali 43 Pemaron 44 Bali 2 Figure 1.4. Location map of existing power plant in Bali 1.2 Energy Resources in Java Tabel 1.1. Energy resources potency Java Madura Bali. no Region Coal (millio n ton) LNG (BSCF) Crude Oil (juta Barel) Geothermal (lokasi) 1 DKI Jakarta 0 0 0 0 2 Banten 13 5190 738 50 3 West Java 0 0 0 40 4 Central Java 0,08 0,11 0 14 5 DI. Yogyakarta 0 0 0 1 6 East Java 0,08 4289 581 11 7 Bali 0 0 0 5 8 Madura n/a n/a n/a n/a source :[3] RUKN, 2005, pg 37 361
Java, Madura, and Bali have advantage of being having geothermal resources which is only exploitable on the site. From this table, the 121 location of geothermal size is having potential capacity of 10,000MW. While for other resource of energy, JAMALI still needs to be supplied from other area like Sumatera and Kalimantan. 2. Methodology This study is carried in three different scenarios. The three scenario is differentiated by it way to weight the emissions into consideration. The first scenario puts no consideration of emission into it optimization. The second scenario includes the mitigations of SO2 and CO2 into the dirtiest type of power plant production cost, to reduce the major sum of pollutant. The third scenario puts emission quota for each year of the study into optimization consideration. There are several technical aspects for consideration to fulfill the next 20 years of growth in Java-Madura-Bali, they are: 1. The electricity needs growth in Java-Madura-Bali until 2026 and availability of energy resources in Java-Madura-Bali. 2. The end of operational period of old power plants and additional unit that already be programmed before 2006. 3. Economic aspect for each type of alternatives power plant (coal, LNG, geothermal, nuclear, MFO), all economic data is assumed constant. 4. Emission factor of each type of power plant. 5. Reliability and maintenance factor for each alternatives type power plant. The result from the three scenarios optimization can be analyzed base on it composition, reliability and it produced emissions amount. The analysis will show qualitatively what the vision of the system s expansion plan. In order to mitigate these emissions the system can use Carbon Capture Storage (CCS) and Flue Gas Desulphurization (FGD) technology. Using these technologies will increase the cost of power generation [1]& [8]. Optimization to find best expansion plan is carried by WASP (Wien Automatic System Planning) program to execute bellman s dynamic programming algorithm. Dynamics programming work upon characteristic of the possible alternative type of power plant and the system s peak load characteristic. Process optimization in WASP can be considered into two major steps. First step is calculation of consequences part, the other is dynamic programming part. The first part must be firstly executed before the dynamic programming part. Every calculated consequences of the probable decision will became decision state in dynamic programming that need to be chosen to find optimal power plant procurement per year. The calculation of objectives functions also includes probabilistic aspect of power generation. It probabilistic aspects are represented by probability of power generator to be default and also its need to be off operational for maintenance [7]. Dynamic programming will determine optimum expansion path with backward induction method. After describe every possible decision, complete with it calculated consequences, dynamic programming will look for the best decision (smallest objective function) at the end 2026 than backwardly look for the best decision in 2025 and so on [5]. Figure 2.1. dynamic programming illustration Permutation of the possible decision state is produced by program module named CONGEN (configuration generation). For illustration, CONGEN will produce state A-J in figure 3.1. While other module named MERSIM (merge and simulate) will calculate the cost of each state transition (number between state in figure 3.1) 3. Result Simulation of the first scenario, with no constrain on emissions, shows that coal power plant is the most competitive type of power plant. It contributes up to 66% from all electricity produced for the Java- Madura-Bali system. Nuclear power is economical enough to contribute more than 8% from the system total production. The sort of contribution are coal (66.5%), LNG (5.2%), nuclear (8%), geothermal (5.2%), HSD and MFO (2.2%). Figure 3.1. Power contribution in the first scenario 362
In the second scenario, where emission mitigation is applied to the most polluting technology, LNG replaces coal as the most competitive type power plant. It produces 60% of the system. Nuclear power contribution also increases to 25 % share. So the rank of contribution size become LNG (60.7%), nuclear (25.2%), coal (8.9%), geothermal (3.2%), HSD and MFO (2%) From the emission side point the second scenario produce smallest amount among them all in the long term, it has smallest average increment year by year. While the third scenario s emission (SO 2 & CO 2 ), excel in the near future, until 2020. The first scenario s emission (SO 2 & CO 2 ) is considered the worst among the three either for the near future or in the long term. Figure 3.2. Power contribution in the second scenario In the third scenario, where the strict amount constraint on emissions is applied, the rank of the five alternatives power plant does not change from the second scenario. Start with LNG (56.9%), nuclear (17.2%), coal (16.7%), geothermal (7.2%), HSD and MFO (2.2%). Figure 3.5. Emission of CO 2 from each scenario Figure 3.3. power contribution in the third scenario For the first and the second scenario have comparable and relatively high reliability level (low loss of load probability). While the third scenario s result show very poor system reliability until 2018. Figure 3.6. Emission of SO 2 from each scenario Tonnage energy resource consumption for all scenario are dominated by LNG and Coal. Coal is peaking over LNG in the 1 st scenario. While in two other scenario, LNG is peaking over coal. Figure 3.4. Lost Of Load Probability (reliability) of the three scenarios. Figure 3.7. Fuel consumption in scenario 1 363
Figure 3.8. Fuel consumption in scenario 2. Figure 3.9. Fuel consumption in scenario 3 put restriction on accumulative pollution amount then load factor of most existing power plant. Comparing the entire emissions charts, it can be concluded that the second scenario is giving the best low emission solution. But it should be analyzed from our nation ability to supply needed fuel for second scenario. In the sense of energy resource consumption, our primary concern is with LNG and Coal production. Both are the highest consumption in tonnage for every scenario. The question remains, is Indonesia s production capable to fulfill the coal and the LNG for JAMALI system. Unfortunately the answer is not good base on the production data of 2006. Coal production is about 64 million ton while LNG production trend is declining from 1995-2005[10] data from 28 million ton to 23 million ton. Coal consumption is peaking at about 53 million ton in scenario 1, or nearly 82% of our nation production (if we assume production is not increasing significantly). LNG consumption in both, scenario 2 and 3, is peaking at 20 million ton or 87% of 2005 total production. These numbers mean that JAMALI really needs alternative energy solution. As in it is impossible to plunge most of national production into primary energy sector where the margin is very low and even subsidized. 4. Analysis The coal first place in the first scenario implies coal fired power plant as the most economical type of power plant. But its mitigation technology is not yet economical. It caused coal type power plant rank down to the third place just before the nuclear type in the second place. Although LNG have higher price than the coal, but it have higher heat value compare and lower emissions. With higher efficiency in combine cycle technology, it can be the backbone for the system s base load with lower emissions compared to coal, as in the second scenario result. The nuclear type power plant turns out always have significant percentage of contribution in every scenario (8%-25%). It even survives higher economic challenge in the first scenario. Increasing in geothermal contribution in third scenario (3.2%-7%) result turns out able to reduce significant amount of emission. But drastic emission limitation in the third scenario has bad effect on system reliability. So it high LOLP is not direct consequence from increasing geothermal power plant unit. Low reliability in third scenario result is related how the old system is executed. The old system depend mainly on fossil fuel, either oil or coal. Both are very polluting technologies in origin. So where we 5. Conclusion Geothermal has the lowest risk among all other alternative. All the 10,000mw in Java-Madura- Bali should be operational to support clean alternative energy potential. Nuclear power technology is worth to be utilized in Java Madura-Bali system. The result shows that in pessimistic scenario, 8% contribution is needed from nuclear technology. The use of coal and LNG need to be cautioned. Coal energy using can be increased side by side with innovation of cheaper emission mitigations processes. But even when cheaper emission mitigation process is attained the proportions of coal (and LNG) in the future have to be reduced to a certain level (<<80%of national production), to supply other energy feedstock s need. This problem would elevate the emergency of development in good and economical type of alternative energy for Indonesia such as geothermal, nuclear, economized wind, and economized tidal. Acknowledgment Special thanks to Ir. Edi Sartono-BATAN 364
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