Optimalisasi Mode Sliding Pressure Beban Rendah Terhadap Kinerja Boiler pada Unit 600 MW PLTU X di BantenNurul Chandra Purnama1*, Silviana1,2, Widodo Agung Suedy1,3*Email corresponding author: Nurulchandra@students.undip.ac.id1Magister of Energy, Diponegoro University, Indonesia2Department of Chemical Engineering, Faculty of Engineering, Diponegoro University, Indonesia3Departmen of Biology, Faculty of Science and Mathematic, Diponegoro University, IndonesiaArticle history: Received: 4 Mei 2026 | Revised: 9 Juni 2026 | Accepted: 11 Juni 2026Abstract. Optimizing electrical energy production at coal-fired power plants (PLTU) remains a challenge in Indonesia. The sliding pressure mode is one approach to operating power plant boilers more efficiently. This study aims to investigate the optimization of the sliding pressure mode on boiler efficiency at PLTU X in Banten. This research method used property data from the Distributed Control System (DCS) which was tested at loads of 300 MW, 450 MW, 510 MW, and 600 MW. The results revealed discrepancies between the design sliding pressure mode graph and the simulation using Gate Cycle software. The Gate Cycle simulation was deemed more relevant as an operational reference, yielding a boiler efficiency of 80%. Keywords - Optimization; Sliding Pressure; Boiler Efficiency; Gate Cycle SimulationAbstrak. Optimalisasi energi listrik oleh pembangkit listrik tenaga uap (PLTU) yang berasal dari batu bara masih menjadi tantangan di Indonesia. Mode sliding pressure (tekanan geser) merupakan salah satu langkah untuk mengoperasionalkan boiler pada pembangkit listrik menjadi lebih efisien. Penelitian ini bertujuan untuk mengetahui optimalisasi mode sliding pressure terhadap efisiensi boiler di PLTU X di Banten. Metode penelitian ini menggunakan data properti dari Distributed Control System (DCS) yang diuji pada beban 300 MW, 450 MW, 510 MW, dan 600 MW. Hasil penelitian menunjukkan adanya perbedaan antara grafik mode sliding pressure desain dengan simulasi menggunakan Software Gate Cycle. Simulasi Gate Cycle dinilai lebih relevan sebagai acuan operasi, dengan efisiensi boiler yang diperoleh sebesar 80%.Kata Kunci - Optimalisasi; Tekanan Geser; Efisiensi Boiler; Simulasi Gate CyclePendahuluan Elektrifikasi dan penghematan energi di sektor listrik merupakan isu penting yang menjadi persoalan global untuk mencapai pasokan energi secara berkelanjutan pada tahun 2035. Pemerintah Indonesia berkomitmen untuk meningkatkan porsi Energi Baru dan Terbarukan (EBT) dalam bauran energi nasional dengan menandatangani Paris Agreement to the United Nations Framework Convention on Climate Change (Persetujuan Paris atas Konvensi Kerangka Kerja Perserikatan Bangsa-Bangsa Mengenai Iklim) di New York tanggal 22 April 2016 untuk mengurangi emisi GRK (Gas Rumah Kaca) sebesar 21-41% dan menjaga temperatur global di bawah 2°C ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"author":[{"dropping-particle":"","family":"Deon","given":"Arinaldo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mursanti","given":"Erina","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Tumiwa","given":"Fabby","non-dropping-particle":"","parse-names":false,"suffix":""}],"id":"ITEM-1","issued":{"date-parts":[["2019"]]},"number-of-pages":"1-12","title":"Implikasi Paris Agreement terhadap Masa Depan Pembangkit Listrik Tenaga Uap (PLTU) Batubara di Indonesia","type":"report"},"uris":["http://www.mendeley.com/documents/?uuid=6ea1b08e-0a13-4cb7-924d-166e6ae57fed"]}],"mendeley":{"formattedCitation":"[1]","plainTextFormattedCitation":"[1]","previouslyFormattedCitation":"[1]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[1]. Meskipun prospek energi terbarukan telah meningkat secara substansial dalam beberapa tahun terakhir, batu bara masih menjadi sumber listrik yang signifikan hingga tahun 2040 khususnya di wilayah Asia ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/j.egypro.2019.01.228","ISSN":"1876-6102","author":[{"dropping-particle":"","family":"Tu","given":"Yaojie","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yang","given":"Wenming","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Siah","given":"Keng Boon","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Prabakaran","given":"Subbaiah","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Energy Procedia","id":"ITEM-1","issued":{"date-parts":[["2019"]]},"page":"898-903","publisher":"Elsevier B.V.","title":"Effect of Different Operating Conditions on the Performance of a 32 MW Woodchip-Fired Grate Boiler","type":"article-journal","volume":"158"},"uris":["http://www.mendeley.com/documents/?uuid=33ee9fd3-948b-4c61-a84b-532f85466a0a"]}],"mendeley":{"formattedCitation":"[2]","plainTextFormattedCitation":"[2]","previouslyFormattedCitation":"[2]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[2]. Hal ini dikarenakan bahan bakar fosil seperti batu bara masih menyumbang 75% dari gabungan energi yang tersedia ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"https://doi.org/10.1007/s10973-019-08871-9","author":[{"dropping-particle":"","family":"Yang","given":"Mei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhou","given":"Yun-Long","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wang","given":"Di","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Han","given":"Jiayu","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yan","given":"Yujia","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Journal of Thermal Analysis and Calorimetry","id":"ITEM-1","issue":"1","issued":{"date-parts":[["2020"]]},"page":"83-94","title":"Thermodynamic Cycle Analysis And Optimization To Improve Efficiency In A 700 °C Ultra-Supercritical Double Reheat System","type":"article-journal","volume":"141"},"uris":["http://www.mendeley.com/documents/?uuid=289cb4ca-77c2-4328-8fe7-1dc84856f6c3"]}],"mendeley":{"formattedCitation":"[3]","plainTextFormattedCitation":"[3]","previouslyFormattedCitation":"[3]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[3]. Badan Energi Internasional menekankan bahwa permintaan listrik oleh masyarakat akan menjadi dua kali lebih cepat dibandingkan dengan ketersediaan energi yang ada ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"author":[{"dropping-particle":"","family":"Petroolum","given":"British","non-dropping-particle":"","parse-names":false,"suffix":""}],"id":"ITEM-1","issued":{"date-parts":[["2024"]]},"title":"BP Energy Outlook 2024 Edition","type":"book"},"uris":["http://www.mendeley.com/documents/?uuid=eddd367d-016a-47e9-a94c-145f0d1bae17"]}],"mendeley":{"formattedCitation":"[4]","plainTextFormattedCitation":"[4]","previouslyFormattedCitation":"[4]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[4]. Beberapa unit PLTU (Pembangkit Listrik Tenaga Uap) di Indonesia juga memperluas rentang beban operasi dari 30-100% sesuai dengan pengiriman jaringan listrik ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1088/1757-899X/677/5/052019","author":[{"dropping-particle":"","family":"Zheng","given":"Wei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Shang","given":"Panfeng","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Guo","given":"Junshan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Han","given":"Yue","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhu","given":"Lingkai","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Lao","given":"Jinxu","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Li","given":"Li","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ding","given":"Junqi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Ma","given":"Yihe","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"IOP Conference Series: Materials Science and Engineering","id":"ITEM-1","issued":{"date-parts":[["2019"]]},"page":"052019","title":"Experimental Study on Low-load Sliding Pressure Operation of Supercritical Unit","type":"article-journal","volume":"677"},"uris":["http://www.mendeley.com/documents/?uuid=11613ff0-529d-4e21-9f59-fe0a95baffdd"]}],"mendeley":{"formattedCitation":"[5]","plainTextFormattedCitation":"[5]","previouslyFormattedCitation":"[5]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[5]. Berdasarkan keadaan tersebut diperlukan efisiensi penggunaan energi dengan meningkatkan suhu dan tekanan panas menggunakan material yang hemat biaya. Pada realitasnya efisiensi energi dapat mengalami kendala karena parameter uji yang terbatas. Hal ini dapat membuat semakin sulit dalam mengajukan uji karakteristik beban dan parameter kontrol. Uji karakteristik pada alat pembangkit akhirnya akan dilakukan dengan metode eksperimen dan cenderung bergeser menyesuaikan unit yang sering digunakan. Selain itu, transformasi energi karena penetrasi yang tinggi pada beban pembangkit listrik berbahan bakar batu bara juga harus sering diubah untuk meningkatkan fleksibilitas operasional ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"https://doi.org/10.1016/j.energy.2021.121048","author":[{"dropping-particle":"","family":"Wang","given":"Zhu","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Liu","given":"Ming","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yan","given":"Junjie","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Energy","id":"ITEM-1","issued":{"date-parts":[["2021"]]},"page":"121048","title":"Flexibility And Efficiency Co-Enhancement Of Thermal Power Plant By Control Strategy Improvement Considering Time Varying And Detailed Boiler Heat Storage Characteristics","type":"article-journal","volume":"232"},"uris":["http://www.mendeley.com/documents/?uuid=1bac442d-3e43-41cd-9c39-b5d72ef6e94f"]}],"mendeley":{"formattedCitation":"[6]","plainTextFormattedCitation":"[6]","previouslyFormattedCitation":"[6]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[6]. Di sisi lain, Komisi Pengembangan dan Reformasi Biro Energi Nasional dalam sistem perencanaan sistem energi modern ke-14 juga berupaya untuk meningkatkan fleksibilitas unit pembangkit tenaga batu bara lebih dari 200 juta kilowatt hingga tahun 2025. Salah satu controllable loss yang berperan pada efisiensi siklus uap dan air yaitu tekanan uap utama (main steam pressure). Menurut konsep hukum termodinamika, semakin tinggi main steam pressure maka efisiensi siklus uap dan airnya juga akan semakin tinggi. Dalam pengoperasian main steam pressure pada sebuah PLTU terdapat tiga buah mode yakni mode tekanan konstan (constant pressure), mode tekanan bergeser penuh (full sliding pressure), dan mode tekanan gabungan (hybrid pressure) ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"author":[{"dropping-particle":"","family":"Santoso","given":"Budi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Dwiyantoro","given":"Bambang Arip","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"JMES The International Journal of Mechanical Engineering and Sciences","id":"ITEM-1","issue":"2","issued":{"date-parts":[["2022"]]},"page":"91-99","title":"Numerical Study of Heat Transfer Characteristics in High Pressure Steam Turbine during Stop Unit Process with Sliding Pressure","type":"article-journal","volume":"6"},"uris":["http://www.mendeley.com/documents/?uuid=52050694-aa07-4b76-a2c6-e0021a7df744"]}],"mendeley":{"formattedCitation":"[7]","plainTextFormattedCitation":"[7]","previouslyFormattedCitation":"[7]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[7]. Adapun mode operasi tekanan geser gabungan memiliki efisiensi termal siklus terbaik serta beban yang lebih fleksibel dibandingkan mode main steam pressure yang lain. Menurut penelitian Qasem et al ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"https://doi.org/10.3390/su14138039","author":[{"dropping-particle":"","family":"Qasem","given":"Mohammad","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mohamed","given":"Omar","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Elhaija","given":"Wejdan Abu","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Sustainability","id":"ITEM-1","issued":{"date-parts":[["2022"]]},"page":"8039","title":"Parameter Identification and Sliding Pressure Control of a Supercritical Power Plant Using Whale Optimizer","type":"article-journal","volume":"14"},"uris":["http://www.mendeley.com/documents/?uuid=815eae24-4650-48ad-8beb-f31a13c88e5d"]}],"mendeley":{"formattedCitation":"[8]","plainTextFormattedCitation":"[8]","previouslyFormattedCitation":"[8]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[8] mode sliding pressure memungkinkan penyesuaian tekanan uap sesuai dengan bahan operasional. Hal ini sangat berguna untuk mengurangi penggunaan bahan bakar dan emisi gas rumah kaca. Selain itu, mode sliding pressure dapat menjadi pilihan terbaik untuk mengontrol dan memperoleh efisiensi beban parsial yang lebih tinggi serta pengoperasian yang bersih.Mode sliding pressure dari rangkaian generator turbin uap ditentukan oleh metode perbandingan eksperimental laju panas dan metode analisis kehilangan tekanan geser. Adapun, hal tersebut dilakukan dengan menentukan tekanan optimal (titik rendah laju panas) yang didasarkan pada perubahan pendapatan selisih konsumsi total sebagai dasar optimasi tekanan geser ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"https://doi.org/10.1109/MLBDBI58171.2022.00022","author":[{"dropping-particle":"","family":"Kong","given":"Dean","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Liu","given":"Jiangshan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Shen","given":"Zhongxin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhen","given":"Xin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kang","given":"Pengpeng","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhao","given":"Wenqing","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhai","given":"Wenhui","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"2022 4th International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI)","id":"ITEM-1","issued":{"date-parts":[["2022"]]},"page":"84-88","title":"Research on Optimization of Sliding Pressure Curve of 300MW Unit Based on Data Mining","type":"paper-conference"},"uris":["http://www.mendeley.com/documents/?uuid=876d8c15-3d07-403b-afbf-70ee41b12333"]}],"mendeley":{"formattedCitation":"[9]","plainTextFormattedCitation":"[9]","previouslyFormattedCitation":"[9]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[9]. Akan tetapi, kedua metode tersebut memiliki kekurangan terkait beban kerja yang berat disebabkan oleh adanya berbagai macam parameter, indeks optimasi yang hanya melibatkan salah satu turbin, dan perolehan hasil yang sulit untuk mencakup semua aspek ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"https://doi.org/10.1016/j.applthermaleng.2017.07.059","author":[{"dropping-particle":"","family":"Biencinto","given":"Maria","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Montes","given":"María José","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Valenzuela","given":"Loreto","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"González","given":"Lourdes","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Applied Thermal Engineering","id":"ITEM-1","issued":{"date-parts":[["2017"]]},"page":"735-745","title":"Simulation And Comparison Between Fixed And Sliding-Pressure Strategies In Parabolic-Trough Solar Power Plants With Direct Steam Generation","type":"article-journal","volume":"125"},"uris":["http://www.mendeley.com/documents/?uuid=3400438f-888d-432d-bd5f-ca74ba29afac"]}],"mendeley":{"formattedCitation":"[10]","plainTextFormattedCitation":"[10]","previouslyFormattedCitation":"[10]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[10]. Dalam beberapa tahun terakhir, penelitian mengenai penerapan mode sliding pressure umumnya berfokus pada peningkatan sistem kontrol dan fleksibilitas operasi sistem. Penelitian Qasem et al ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"https://doi.org/10.3390/su14138039","author":[{"dropping-particle":"","family":"Qasem","given":"Mohammad","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Mohamed","given":"Omar","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Elhaija","given":"Wejdan Abu","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Sustainability","id":"ITEM-1","issued":{"date-parts":[["2022"]]},"page":"8039","title":"Parameter Identification and Sliding Pressure Control of a Supercritical Power Plant Using Whale Optimizer","type":"article-journal","volume":"14"},"uris":["http://www.mendeley.com/documents/?uuid=815eae24-4650-48ad-8beb-f31a13c88e5d"]}],"mendeley":{"formattedCitation":"[8]","plainTextFormattedCitation":"[8]","previouslyFormattedCitation":"[8]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[8], berfokus pada strategi pengendalian sliding pressure melalui optimasi sistem kontrol dan kestabilan tekanan operasi. Sedangkan, penelitian Suhaily et al ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.47001/irjiet/2024.811026","abstract":"The 610 MW subcritical power plant was originally designed to operate at a constant base load with fixed boiler steam pressure. However, due to grid oversupply conditions, the plant frequently operates at partial loads, resulting in increased inefficiencies caused by throttle losses, particularly during minimum load operations, which significantly reduce high-pressure (HP) turbine efficiency. This study investigates the impact of sliding pressure operation, which involves varying boiler steam pressure with load, on overall plant efficiency compared to constant pressure operation. A virtual plant simulation was employed to model the heat and mass balance of the power plant and simulate operational scenarios under varying steam pressures. The optimal simulation results were validated through direct testing on the plant, followed by performance analysis. The results reveal that sliding pressure operation improves HP turbine efficiency by 5-7%, reduces the net plant heat rate (NPHR) by 57 kcal/kWh, and enhances overall thermal efficiency by 0.35% at 57% load (350 MW).","author":[{"dropping-particle":"","family":"Suhaily","given":"Hamam","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Kiono","given":"Berkah Fajar Tamtomo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Suedy","given":"Sri Widodo Agung","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"IRJIET (International Research Journal of Innovations in Engineering and Technology)","id":"ITEM-1","issue":"11","issued":{"date-parts":[["2024"]]},"page":"211-218","title":"Analysis of the Impact of Sliding Pressure Operation on the Efficiency of a 610 MW Subcritical Steam Power Plant Boiler","type":"article-journal","volume":"08"},"uris":["http://www.mendeley.com/documents/?uuid=c46c7f5f-3b4e-4425-b00f-0d3254fcb4ec"]}],"mendeley":{"formattedCitation":"[11]","plainTextFormattedCitation":"[11]","previouslyFormattedCitation":"[11]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[11] mengkaji penerapan mode sliding pressure pada unit pembangkit, namun belum mengevaluasi penentuan tekanan operasi optimum secara mendalam. Di sisi lain, penelitian mengenai operasi beban rendah yang dilakukan oleh Chong et al ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.3390/pr12112496","ISSN":"22279717","abstract":"Under the background of achieving carbon dioxide peaking and carbon neutrality, the rapid development of renewable energy power generation poses new challenges to the flexible adjustment capabilities of traditional power plants. To explore the furnace combustion stability and optimal operation modes during deep peak shaving, a simulation of the combustion process under low-load conditions for a 600 MW wall-fired boiler is performed utilizing computational fluid dynamics (CFD) analysis. The impact of burner combination modes on the combustion process within the furnace is explored at 25% and 35% boiler maximum continuous ratings (BMCRs). This study investigates two configurations of burner combinations. One mode operates burners in layers A, B, and C, which include the lower layers of burners on the front and rear walls of the boiler, as well as the middle-layer burners on the rear wall, referred to as OM1. The other mode operates burners in layers A and C, which include the lower layers of burners on the front and rear walls of the boiler, referred to as OM2. The results indicate that OM2 exhibits superior capabilities in orchestrating the distribution of the airflow velocity field and temperature field under the premise of ensuring no more than a 1% decrease in the pulverized coal burnout rate. When OM1 is employed, the airflow ejected from the middle-level burners hinders the upward movement of pulverized coal sprayed from the lower-level burners, causing a larger proportion of pulverized coal to enter the ash hopper for combustion. Consequently, the ash hopper attains a peak mole fraction of CO2 at 0.163. OM2 delays the blending of pulverized coal with air by enhancing the injection quantity of pulverized coal per burner. As a result, the generation of CO in the ash hopper reaches a notable mole fraction of up to 0.108. The decreased furnace temperature promotes the formation of fuel-based NOx during low-load operation. Taking the 25% BMCR as an example, the NOx emissions measured at the furnace outlet are 743 and 1083 ppm for OM1 and OM2, respectively. This study focuses on the impact of combustion combinations on the combustion stability when the boiler is operating at low loads. The findings could enrich previous research on combustion stability and contribute to the optimization of combustion schemes for power plant boilers operating at low loads.","author":[{"dropping-particle":"","family":"Chong","given":"Peian","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Li","given":"Jianning","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Zhu","given":"Xiaolei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Jing","given":"Dengke","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Deng","given":"Lei","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Processes","id":"ITEM-1","issued":{"date-parts":[["2024"]]},"page":"2496","title":"Numerical Study on Combustion Characteristics of a 600 MW Boiler Under Low-Load Conditions","type":"article-journal","volume":"12"},"uris":["http://www.mendeley.com/documents/?uuid=94ad0f05-15a1-4c74-b6c1-82daf5a13399"]}],"mendeley":{"formattedCitation":"[12]","plainTextFormattedCitation":"[12]","previouslyFormattedCitation":"[12]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[12] dan Tang et al ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"10.1016/j.applthermaleng.2025.125859","ISSN":"13594311","abstract":"To cope with the problems caused by the integration of new energy into the grid, self-sustaining internal combustion (SSIC) burners are introduced for flexible peaking of coal-fired units. However, there is still a lack of research on the combustion characteristics of power plant boilers utilizing SSIC burners under low load conditions. This paper presents a retrofit study of a boiler for low load by an SSIC burner with the aim of improving boiler combustion efficiency and reducing pollutant emissions. The combustion characteristics of a 600 MW power station boiler at 30 %-48 % of the maximum continuous rating (MCR) are analyzed by numerical simulation methods, and the effects of SSIC burner on the flow field, temperature distribution, NOx emission and thermal efficiency of the boiler are investigated. The results show that after the SSIC burner modification, the enhancement of flue gas jet rigidity improves the combustion stability. The pyrolysis gas concentration in the furnace is much higher than that of conventional combustion, which helps to reduce NOx. Pyrolysis gas and high-temperature char can promote combustion. When the boiler load is at 36 %–48 % MCR, the initial NOx emission is less than 50 mg/Nm3 and the emission standards are met by combustion alone. Initial NOx emission is reduced by 69 % at 30 % MCR. The thermal efficiency of the boiler increases by 2.96 % and 2.56 % at 36 % and 42 % MCR, respectively. The study shows that the SSIC burner can significantly improve the combustion stability of coal-fired units, reduce NOx emissions and improve the thermal efficiency of the boiler, which provides technical support for the low-load peaking of coal-fired power plants.","author":[{"dropping-particle":"","family":"Tang","given":"Hong","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yao","given":"Guojia","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Wang","given":"Zhenbang","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Yang","given":"Jing","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Han","given":"Xiaoju","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Sun","given":"Lingfang","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Xu","given":"Zhiming","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Applied Thermal Engineering","id":"ITEM-1","issued":{"date-parts":[["2025"]]},"page":"125859","publisher":"Elsevier Ltd","title":"Study on Low-Load Combustion Characteristics of a 600 MW Power Plant Boiler with Self-Sustaining Internal Combustion Burners","type":"article-journal","volume":"267"},"uris":["http://www.mendeley.com/documents/?uuid=1a6ebf31-d7aa-4e99-8e39-fafdce87a866"]}],"mendeley":{"formattedCitation":"[13]","plainTextFormattedCitation":"[13]","previouslyFormattedCitation":"[13]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[13] lebih banyak mengkaji terkait aspek karakteristik pembakaran, stabilitas nyala api, dan distribusi temperatur dalam boiler. Oleh karena itu, penelitian yang mengintegrasikan operasi beban rendah dengan penerapan mode sliding pressure berdasarkan data operasi aktual pada PLTU masih relatif terbatas.Berdasarkan kesenjangan tersebut, penelitian ini menawarkan kebaruan melalui analisis pengaruh penerapan mode sliding pressure pada kondisi beban rendah terhadap kinerja boiler berdasarkan data operasi aktual Unit 600 MW PLTU. Selain menganalisis perubahan kinerja boiler, penelitian ini juga melakukan analisis termodinamika melalui simulasi Software Gate Cycle yang telah divalidasi terhadap data komisioning. Pendekatan tersebut diharapkan mampu memberikan gambaran yang lebih komprehensif mengenai dampak perubahan tekanan operasi terhadap kinerja boiler. Berdasarkan permasalahan tersebut, penelitian ini bertujuan untuk menganalisis dan mengoptimalkan penerapan mode sliding pressure untuk meningkatkan kinerja boiler pada Unit 600 MW PLTU X di Banten. Hasil penelitian diharapkan dapat memberikan rekomendasi operasional yang mendukung peningkatan efisiensi kinerja boiler pada kondisi beban rendah serta mengurangi kerugian energi (energy losses). Selain memberikan manfaat terkait teknis operasional, hasil penelitian juga diharapkan dapat mendukung upaya peningkatan fleksiblitas operasi PLTU dalam menghadapi perubahan pola beban sistem kelistrikan yang semakin dinamis.MetodePenelitian ini dilakukan pada Unit 600 MW PLTU PT X di Banten. PLTU PT X merupakan pembangkit tenaga listrik tenaga uap berbahan bakar batu bara (pulverized coal) yang terdiri atas tujuh unit dengan total kapasitas terpasang sebesar 3.400 MW, meliputi empat unit berkapasitas 400 MW dan tiga unit berkapasitas 600 MW. Sistem pembangkit menggunakan boiler tipe Radiant Boiler. Penelitian ini termasuk penelitian observasional analitik dengan desain studi potong lintang (cross-sectional study). Data operasi yang diperoleh pada periode pengamatan dianalisis untuk mengevaluasi pengaruh penerapan mode sliding pressure terhadap kinerja pembangkit.Gambar SEQ Gambar \* ARABIC 1. Diagram Alir Penelitian PLTU X di BantenGambar 1. menunjukkan diagram alir penelitian yang diawali dengan pengumpulan data properti dari Distributed Control System (DCS). Pengumpulan data dalam penelitian ini dilakukan dengan melakukan pengujian 2 jam dengan pola operasi normal yaitu:Pengambilan parameter operasi berlangsung selama 2 jam dengan beban gross 600 MW dengan melakukan pengambilan parameter gas buang pada sisi Air Heater. Pengambilan data logger parameter operasi melalui DCS dengan beban gross 600 MW selama 2 jam. Selama proses pengujian, dilakukan monitoring dan pencatatan parameter operasi dan pengambilan sampel bahan bakar di coal feeder, fineness bahan bakar di coal pipe, bottom ash di submerged scrapper conveyor dan fly ash di ESP hopper untuk diuji di laboratorium.Pada saat uji coba tara kalor, dilakukan pengambilan beberapa parameter operasi melalui DCS di control room dan REOC. Parameter yang dipantau saat pengujian adalah data trending beban, pressure dan temperature boiler, pressure-temperature-flow steam, exhaust temperatre, serta pengambilan sampel batu bara, fly ash dan bottom ash. Selama periode pengujian dilakukan prosedur sebagai berikut:Data operasi dari DCS diambil setiap 15 menit.Pengambilan sampel bahan bakar dilakukan 1 kali untuk setiap beban yaitu pada akhir pengujian.Pengambilan sampel fly ash dan bottom ash diambil sekali pada akhir pengujian.Data hasil pengujian digunakan sebagai baseline untuk dibandingkan dengan data komisioning. Untuk memastikan validitas perbandingan, batu bara yang digunakan pada pengujian adalah jenis batu bara yang mempunyai karakteristik sama. Selanjutnya, data operasi yang telah terkumpul dianalisis secara numerik untuk menghitung efisiensi boiler pada berbagai kondisi operasi. Gambar SEQ Gambar \* ARABIC 2. Simulasi Software Gate CycleHasil analisis kemudian diolah menggunakan Software Gate Cycle untuk melakukan simulasi kinerja pembangkit secara menyeluruh. Software Gate Cycle merupakan perangkat lunak yang berfungsi untuk membantu perhitungan desain PLTU. Perhitungan ini dilakukan dengan kondisi sesuai dengan aktual ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"https://doi.org/10.56190/jree.v1i1.8","author":[{"dropping-particle":"","family":"Djabal","given":"Harlan","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Djafar","given":"Romi","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Djamalu","given":"Yunita","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Liputo","given":"Burhan","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Journal Of Renewable Energy Engineering (JREE)","id":"ITEM-1","issue":"1","issued":{"date-parts":[["2023"]]},"page":"20-23","title":"SIMULASI SISTEM PLTU ANGGREK 2 X 25 MW MENGGUNAKAN SOFTWARE CYCLE TEMPO DENGAN VARIASI BEBAN TURBIN 25%, 50%, 75% DAN 100%","type":"article-journal","volume":"1"},"uris":["http://www.mendeley.com/documents/?uuid=aa505ee2-1750-437e-b7b5-d685293c1b4c"]}],"mendeley":{"formattedCitation":"[14]","plainTextFormattedCitation":"[14]","previouslyFormattedCitation":"[14]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[14]. Selama proses simulasi, terdapat beberapa data pendukung, seperti parameter operasi aktual, karakteristik bahan bakar, spesifikasi peralatan utama dan pendukung, serta data perpipaan dan instrumentasi pembangkit. Setelah seluruh data berhasil dimasukkan dan model sistem tervalidasi, dilakukan proses simulasi untuk memperoleh parameter kinerja utama, seperti net thermal efficiency, net power output, dan net heat rate ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"author":[{"dropping-particle":"","family":"Mahmuddin","given":"","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Apriadi","given":"Hairun","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Habiba","given":"Syahrir","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"INNOVATIVE: Journal Of Social Science Research","id":"ITEM-1","issue":"2","issued":{"date-parts":[["2024"]]},"page":"4907-4918","title":"Studi Termodinamika Pengaruh Hidden Capacity pada Pembangkit Listrik Tenaga Uap dengan Permodelan GateCyle","type":"article-journal","volume":"4"},"uris":["http://www.mendeley.com/documents/?uuid=e4ffbbec-9bef-4b45-9ee2-b54f05cb2c3a"]}],"mendeley":{"formattedCitation":"[15]","plainTextFormattedCitation":"[15]","previouslyFormattedCitation":"[15]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[15]. Tahap selanjutnya adalah validasi model dengan membandingkan hasil simulasi Gate Cycle dengan nilai pada heat balance yang tersedia. Apabila hasil simulasi menunjukkan nilai yang relatif sama dengan data acuan, maka model dianggap mampu merepresentasikan kondisi aktual pembangkit. Model yang telah tervalidasi selanjutnya digunakan untuk melakukan analisis lebih lanjut melalui variasi parameter operasi yang diteliti. Tahapan ini bertujuan untuk mengevaluasi pengaruh perubahan kondisi operasi terhadap efisiensi boiler, konsumsi energi, dan heat rate.Tahap terakhir yaitu penarikan kesimpulan mengenai kondisi kinerja boiler serta penyusunan rekomendasi perbaikan yang berfokus pada pengurangan faktor-faktor penyebab loses. Rekomendasi tersebut diharapkan dapat mendukung upaya peningkatan efisiensi boiler, menurunkan heat rate, dan mengoptimalkan kinerja pembangkit secara keseluruhan.Hasil dan PembahasanPada pengoperasian boiler PLTU tekanan uap yang dibutuhkan untuk memutar turbin tidak membutuhkan tekanan yang besar terutama saat beban yang digunakan rendah. Berdasarkan keadaan tersebut dibutuhkan tekanan uap yang sesuai dengan kondisi pembebanan unit. Adapun pengoperasioan boiler menggunakan mode sliding pressure dapat mengurangi konsumsi sebesar 2-3% dibandingkan dengan mode tekanan konstan.Gambar SEQ Gambar \* ARABIC 3. Hubungan Sliding Pressure dengan Efisiensi BoilerBerdasarkan referensi panduan perbaikan heat rate PLTU, pembebanan pada PLTU dapat dibedakan menjadi 4 fase, yaitu: 50% (300 MW), 75% (450 MW), 85% (510 MW), 100% (600 MW). Pada Gambar grafik 6. dapat diketahui bahwa terdapat hubungan yang signifikan antara efisiensi boiler dengan perubahan mode sliding pressure. Adapun hasil tersebut diperoleh setelah data di running pada software gate cycle dengan mengoptimalkan mode sliding pressure untuk menghasilkan efisiensi boiler dan memperoleh hasil cenderung tetap, yakni: 80,34%, 80,34%, 80,98%, 80,98%. Hal ini membuktikan bahwa mode sliding pressure dapat mempengaruhi output efisiensi boiler. Pengoptimalan pola operasi pada PLTU dengan tekanan yang lebih rendah dapat dilakukan dengan rekomendasi tekanan pada beban 50% (300 MW) 138,06 bar, 75% (450 MW) 153,96 bar, 85% (510 MW) 156,95 bar, dan 100% (600 MW) 156,95 bar.Gambar SEQ Gambar \* ARABIC 4. Hubungan Sliding Pressure dengan NPHRSejalan dengan hasil dari efisiensi boiler yang cenderung optimal pada nilai 80%, mode sliding pressure juga memiliki dampak yang signifikan terhadap Net Plant Heat Rate (NPHR) dan menunjukkan nilai yang optimal. Pada tekanan 138,06 bar dengan beban 50% (300 MW) didapatkan nilai NPHR sebesar 3719,366 kCal/kWh. Kemudian, pada pressure 153,96 bar di beban 75% (450 MW) didapatkan nilai NPHR sebesar 2479,577 kCal/kWh. Selanjutnya, pada pressure 156,95 bar di beban 85% (510 MW) didapatkan nilai NPHR sebesar 2170,608 kCal/kWh. Terakhir, untuk pressure (tekanan) yang sama dengan beban 100% (600 MW) didapatkan nilai NPHR sebesar 1845,017 kCal/kWh. Hasil dari NPHR tersebut tidak sepenuhnya dipengaruhi oleh mode sliding pressure, namun ada beberapa parameter lain yang mempengaruhi seperti laju alir uap, nilai kalor batu bara, suhu uap, dan kondisi pembakaran pada boiler.Tabel SEQ Tabel \* ARABIC 1. Hubungan Mode Sliding Pressure dengan Kinerja BoilerNoModeBebanMs. PressureHeat LossMWBarEfisiensi Boiler (%)NPHR (kCal/kWh)1.Sliding Pressure300138,0680,341963719,3662.45015480,341962479,5773.51015780,980582170,6084.60015780,980581845,017Pada tabel 1. menunjukkan bahwa mode sliding pressure pada beban 300 MW dengan rekomendasi pressure sebesar 138,06 bar menghasilkan efisiensi boiler sebesar 80,34% dan NPHR sebesar 3719,366 kCal/kWh. Pada mode sliding pressure pada beban 450 MW direkomendasikan pressure sebesar 154 bar menghasilkan efisiensi boiler sebesar 80,34% dengan perbaikan NPHR sebesar 2479,577 kCal/kWh. Di samping itu, untuk mode sliding pressure pada beban 510 MW dan 600 MW direkomendasikan pressure sebesar 157 bar menghasilkan efisiensi boiler sebesar 80,98% dengan perbaikan NPHR sebesar 2170,608 kCal/kWh dan 1845,017 kCal/kWh. Sejalan dengan penelitian Yuan et al (2023) ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"https://doi.org/10.1016/j.energy.2022.126184","author":[{"dropping-particle":"","family":"Yuan","given":"Zhenhua","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Chen","given":"Zhicao","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Hang","given":"Bo","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Gao","given":"Xuelin","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Li","given":"Jiawei","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Qiao","given":"Yanyu","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Li","given":"Zhengqi","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Energy","id":"ITEM-1","issued":{"date-parts":[["2023"]]},"page":"126184","title":"Study On The Slagging Trends Of The Pre-Combustion Chamber In Industrial Pulverized Coal Boiler Under Different Excess Air Coefficients By CFD Numerical Simulation","type":"article-journal","volume":"264"},"uris":["http://www.mendeley.com/documents/?uuid=8bb64e37-6578-4686-bd89-3ff2ad3e91da"]}],"mendeley":{"formattedCitation":"[16]","plainTextFormattedCitation":"[16]","previouslyFormattedCitation":"[16]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[16] yang menyatakan bahwa penggunaan mode operasi katup berurutan pada turbin uap menunjukkan efisiensi yang lebih tinggi dibandingkan dengan mode katup tunggal. Hal ini dapat disebabkan oleh pembukaan katup yang lebih besar dalam mode berurutan, yang mengurangi hambatan aliran uap dan meningkatkan efisiensi termal, terutama pada silinder bertekanan tinggi. Secara khusus, pada beban rendah sekitar 400 MW hingga 500 MW, silinder bertekanan tinggi menunjukkan efisiensi termal yang lebih baik dalam mode katup berurutan dibandingkan dengan mode katup tunggal. Namun, pada beban di atas 600 MW, perbedaan efisiensi antara kedua mode tersebut menjadi lebih kecil, meskipun mode berurutan tetap menunjukkan keunggulan dalam efisiensi silinder bertekanan tinggi. Hal ini membuktikan bahwa mode sliding pressure mampu mengoptimalkan efisiensi boiler dan NPHR, sehingga menghasilkan kinerja unit pada titik optimumnya.298894514732000-63514732000Gambar SEQ Gambar \* ARABIC 5. Perbandingan Simulasi Mode Operasi Sliding Pressure dan Hasil Kurva DesainPada Gambar grafik 8. dipaparkan hubungan antara mode sliding pressure menggunakan simulasi gate cycle dengan grafik desain hybrida sliding saat beban rendah beracuan (Manual Book Boiler PLTU). Pada perbandingan tersebut didapatkan hasil pada beban 50% untuk tekanan uap kerja yang direkomendasikan pada simulasi sebesar 138,06 bar. Sedangkan, pada desain buku ditunjukkan hasil sebesar 107 bar. Pada beban 75% tekanan uap kerja yang direkomendasikan sebesar 153,96 bar dan pada desain buku sebesar 160 bar serta untuk beban 75% dan 100%, tekanan uap kerja yang direkomendasikan pada simulasi 156,95 bar dan pada desain sebesar 169 bar. Adapun perbedaan antara simulasi dan desain pada buku panduan dapat terjadi karena parameter yang lain seperti nilai kalor, jumlah aliran uap yang masuk, dan rekomendasi terkait menjaga kehandalan pipa boiler. Hasil ini sejalan dengan penelitian Milovanovic et al (2018) ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemData":{"DOI":"https://doi.org/10.2298/TSCI18S5371M","author":[{"dropping-particle":"","family":"Milovanovic","given":"Zdravko N.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Dumonjic-Milovanovic","given":"Svetlana R.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Milasinovic","given":"Aleksandar N.","non-dropping-particle":"","parse-names":false,"suffix":""},{"dropping-particle":"","family":"Knezevic","given":"Darko M.","non-dropping-particle":"","parse-names":false,"suffix":""}],"container-title":"Thermal Science","id":"ITEM-1","issue":"5","issued":{"date-parts":[["2018"]]},"page":"1371-1382","title":"Efficiency Of Operation Of 300 MW Condensing Thermal Power Blocks With Supercritical Steam Parameters In Sliding Pressure Mode","type":"article-journal","volume":"22"},"uris":["http://www.mendeley.com/documents/?uuid=a82a5089-5c1a-424b-8780-14a72cba27c4"]}],"mendeley":{"formattedCitation":"[17]","plainTextFormattedCitation":"[17]","previouslyFormattedCitation":"[17]"},"properties":{"noteIndex":0},"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"}[17] menyatakan bahwa perpindahan blok 300 MW dari menggunakan tekanan konstan menjadi tekanan geser pada rentang 30-60% masing-masing dapat meningkatkan efisiensi blok sebesar 6,70-1,05%.KesimpulanMode sliding pressure (tekanan geser) direkomendasikan untuk menunjang pengoperasian unit PLTU. Dengan optimalisasi menggunakan mode sliding pressure pada beban rendah dapat meningkatkan kinerja PLTU tersebut. Hal ini membuktikan bahwa mode sliding pressure pada beban 450 MW dengan rekomendasi pressure sebesar 154 bar dapat menghasilkan efisiensi boiler sebesar 80,34% dengan perbaikan NPHR sebesar 2479,577 kCal/kWh. Adapun untuk mode sliding pressure pada beban 510 MW dan 600 MW dengan pressure sebesar 157 bar menghasilkan efisiensi boiler sebesar 80,98% dengan perbaikan NPHR sebesar 2170,608 kCal/kWh dan 1845,017.Selain itu, berdasarkan hasil penelitian dapat disimpulkan bahwa terdapat perbedaan antara grafik mode sliding pressure desain dengan simulasi menggunakan Software Gate Cycle. Hal ini dapat dipengaruhi oleh beberapa parameter seperti, aliran steam yang masuk pada turbin dan karakteristik batu bara. Untuk mendapatkan hasil yang optimal dapat menggunakan grafik dari desain buku manual pengoperasian PLTU PT X di Banten. Namun, pertimbangan keandalan pada pipa boiler dan kondisi karakteristik bahan bakar yang telah berubah, mode pengoperasian menggunakan acuan simulasi gate cycle lebih relevan digunakan saat ini. Selain itu, terdapat gap antara mode simulasi dengan rekomendasi buku manual. Akan tetapi, gap tersebut masih mampu mengoptimalkan efisiensi boiler dan NPHR pada PLTU X di Banten.ReferensiADDIN Mendeley Bibliography CSL_BIBLIOGRAPHY [1]A. Deon, E. Mursanti, and F. Tumiwa, “Implikasi Paris Agreement terhadap Masa Depan Pembangkit Listrik Tenaga Uap (PLTU) Batubara di Indonesia,” 2019.[2]Y. Tu, W. Yang, K. B. Siah, and S. Prabakaran, “Effect of Different Operating Conditions on the Performance of a 32 MW Woodchip-Fired Grate Boiler,” Energy Procedia, vol. 158, pp. 898–903, 2019, doi: 10.1016/j.egypro.2019.01.228.[3]M. Yang, Y.-L. Zhou, D. Wang, J. Han, and Y. Yan, “Thermodynamic Cycle Analysis And Optimization To Improve Efficiency In A 700 °C Ultra-Supercritical Double Reheat System,” J. Therm. Anal. Calorim., vol. 141, no. 1, pp. 83–94, 2020, doi: https://doi.org/10.1007/s10973-019-08871-9.[4]B. Petroolum, BP Energy Outlook 2024 Edition. 2024.[5]W. Zheng et al., “Experimental Study on Low-load Sliding Pressure Operation of Supercritical Unit,” IOP Conf. Ser. Mater. Sci. Eng., vol. 677, p. 052019, 2019, doi: 10.1088/1757-899X/677/5/052019.[6]Z. Wang, M. Liu, and J. Yan, “Flexibility And Efficiency Co-Enhancement Of Thermal Power Plant By Control Strategy Improvement Considering Time Varying And Detailed Boiler Heat Storage Characteristics,” Energy, vol. 232, p. 121048, 2021, doi: https://doi.org/10.1016/j.energy.2021.121048.[7]B. Santoso and B. A. Dwiyantoro, “Numerical Study of Heat Transfer Characteristics in High Pressure Steam Turbine during Stop Unit Process with Sliding Pressure,” JMES Int. J. Mech. Eng. Sci., vol. 6, no. 2, pp. 91–99, 2022.[8]M. Qasem, O. Mohamed, and W. A. Elhaija, “Parameter Identification and Sliding Pressure Control of a Supercritical Power Plant Using Whale Optimizer,” Sustainability, vol. 14, p. 8039, 2022, doi: https://doi.org/10.3390/su14138039.[9]D. Kong et al., “Research on Optimization of Sliding Pressure Curve of 300MW Unit Based on Data Mining,” in 2022 4th International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI), 2022, pp. 84–88. doi: https://doi.org/10.1109/MLBDBI58171.2022.00022.[10]M. Biencinto, M. J. Montes, L. Valenzuela, and L. González, “Simulation And Comparison Between Fixed And Sliding-Pressure Strategies In Parabolic-Trough Solar Power Plants With Direct Steam Generation,” Appl. Therm. Eng., vol. 125, pp. 735–745, 2017, doi: https://doi.org/10.1016/j.applthermaleng.2017.07.059.[11]H. Suhaily, B. F. T. Kiono, and S. W. A. Suedy, “Analysis of the Impact of Sliding Pressure Operation on the Efficiency of a 610 MW Subcritical Steam Power Plant Boiler,” IRJIET (International Res. J. Innov. Eng. Technol., vol. 08, no. 11, pp. 211–218, 2024, doi: 10.47001/irjiet/2024.811026.[12]P. Chong, J. Li, X. Zhu, D. Jing, and L. Deng, “Numerical Study on Combustion Characteristics of a 600 MW Boiler Under Low-Load Conditions,” Processes, vol. 12, p. 2496, 2024, doi: 10.3390/pr12112496.[13]H. Tang et al., “Study on Low-Load Combustion Characteristics of a 600 MW Power Plant Boiler with Self-Sustaining Internal Combustion Burners,” Appl. Therm. Eng., vol. 267, p. 125859, 2025, doi: 10.1016/j.applthermaleng.2025.125859.[14]H. Djabal, R. Djafar, Y. Djamalu, and B. Liputo, “SIMULASI SISTEM PLTU ANGGREK 2 X 25 MW MENGGUNAKAN SOFTWARE CYCLE TEMPO DENGAN VARIASI BEBAN TURBIN 25%, 50%, 75% DAN 100%,” J. Renew. Energy Eng., vol. 1, no. 1, pp. 20–23, 2023, doi: https://doi.org/10.56190/jree.v1i1.8.[15]Mahmuddin, H. Apriadi, and S. Habiba, “Studi Termodinamika Pengaruh Hidden Capacity pada Pembangkit Listrik Tenaga Uap dengan Permodelan GateCyle,” Innov. J. Soc. Sci. Res., vol. 4, no. 2, pp. 4907–4918, 2024.[16]Z. Yuan et al., “Study On The Slagging Trends Of The Pre-Combustion Chamber In Industrial Pulverized Coal Boiler Under Different Excess Air Coefficients By CFD Numerical Simulation,” Energy, vol. 264, p. 126184, 2023, doi: https://doi.org/10.1016/j.energy.2022.126184.[17]Z. N. Milovanovic, S. R. Dumonjic-Milovanovic, A. N. Milasinovic, and D. M. Knezevic, “Efficiency Of Operation Of 300 MW Condensing Thermal Power Blocks With Supercritical Steam Parameters In Sliding Pressure Mode,” Therm. Sci., vol. 22, no. 5, pp. 1371–1382, 2018, doi: https://doi.org/10.2298/TSCI18S5371M.Halaman ini sengaja dikosongkan(This page is intentionally left blank)Purnama, N. C., Silviana & Suedy, W. A., Optimalisasi Mode Sliding Pressure Beban Rendah Terhadap Kinerja Boiler pada Unit 600 MW PLTU X di Banten, R.E.M. (Rekayasa Energi Manufaktur) Jurnal, vol. 11, no. 1, pp. 149-156, 2026. PAGE \* MERGEFORMAT 2R.E.M. (Rekayasa Energi Manufaktur) Jurnal | Vol.11 No.1/2026ISSN online (2528-3723)http://doi.org/10.21070/rem.v11i1.1838Copyright © 2026 Author [s]. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. 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