PDF 2021 IEEE Conference on Energy Conversion (CENCON)

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2021 IEEE Conference on Energy Conversion (CENCON)

IEEE Catalog Number: CFP21CEO-ART ISBN: 978-1-6654-0129-6

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Message from General Chairs

On behalf of the CENCON 2021 organizing committee, we welcome you to the 5th IEEE Conference on Energy Conversion (CENCON 2021). This conference is organized and sponsored by the IEEE Power Electronics (PELS) Malaysia Chapter, co-organized by Power Electronics and Drives Research Group (PEDG), Universiti Teknologi Malaysia (UTM), and technical co-sponsor by The Korean Institute of Power Electronics (KIPE).

Every one of us has been affected by the Covid-19 pandemic since it started a couple of years ago.

We must not let the pandemic weaken us; in fact, we must move forward and do our best to control the spread of the virus. Because of this, we have decided to hold CENCON 2021 virtually. To ensure the best experience for the participants, the conference is conducted on a user-friendly platform that offers almost the same features as a physical conference. Our virtual conference this year will have 3 parallel sessions held in one day. Registered participants can join and move between any session they wish by joining any virtual breakout rooms. They can choose to watch the recorded presentation of the technical papers and keynote speeches at their convenient time. The contents will be available to the participants up to 2 weeks after the conference ends.

CENCON 2021 is our 5th conference, which is held bi-annually. The last CENCON was held physically in Jog Jakarta, Indonesia, in 2019. CENCON provides an excellent opportunity for researchers and academicians to discuss and present their findings. This year we are lucky to have two distinguished professors deliver the keynote speeches. They are Prof. Dr. Zainal Salam from UTM and Prof. Taufik from Calpoly, USA. CENCON 2021 has received 79 paper submissions. And out of this, 39 have been accepted for presentations. Papers accepted and presented at the conference will be submitted to the IEEE and included in the IEEE Xplore digital library. We notice that the number of submissions is relatively lower than the past CENCON; however, the submissions came from all over the world, including India, the USA, South Korea, Taiwan, Germany, South Africa and a few more.

We hope that you will enjoy this virtual conference from the comfort of your home, and hopefully, we will see you again in 2023 for our next CENCON. Thank you.

Nik Rumzi Nik Idris Rahimi Baharom

CENCON 2021 General Chairs

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Message from General Chairs i

Table of Contents ii

Copyright Page vii

Author Index viii

Author Papers

Session 1A: Photovoltaic System

Session chairs: Tan Chee Wei & Razman Ayop

1A1 A Single-Phase Multilevel Inverter With Reduced Switch Count for Solar PV Application

1

Ali Bughneda (Universiti Sains Malaysia, Malaysia); Mohamed Salem (Universiti Sains Malaysia (USM), Malaysia); Dahaman Ishak (Universiti Sains Malaysia, Malaysia);

Salah Alatai (Universiti Sains Malaysia, Malaysia & Bani Waleed University, Libya);

Mohamad Kamarol Mohd Jamil (Universiti Sains Malaysia, Malaysia); Khlid Ben Hamad (Cape Peninsula University of Technology, South Africa)

1A2 Increasing the Efficiency of Photovoltaic Generation Using Parabolic Reflector 7 Udaya Santha Rahubadde (Kotelawala Defence Univerisity, Sri Lanka); Akmeemanage

Don Dinul Manjitha (General Sir John Kotelawala Defence University, Sri Lanka)

1A3 Performance of the Hybrid Photovoltaic-Thermoelectric Generator (PV-TEG) System Under Malaysian Weather Conditions

11

Umar Abubakar Saleh (University Tun Hussein Onn Malaysia & Centre for Atmospheric Research, NARSDA, Prince Audu Abubakar University Anyigba, Kogi, Malaysia); Siti Amely Jumaat (Universiti Tun Hussein Onn Malaysia, Malaysia);

Muhammad Akmal Johar (Universiti Tun Hussein Onn Malaysia & Smart Structure and System Research Group, Malaysia); Wan Akasha Wan Jamaluddin (University Tun Hussein Onn Malaysia, Malaysia)

1A4 Photovoltaic Emulator Using Particle Swarm Optimization 17 Razman Ayop, Chee Wei Tan, Mohd Zaki Daud, Shahrin Md. Ayob, Awang Jusoh and

Mohd Rodhi Sahid (Universiti Teknologi Malaysia, Malaysia)

1A5 Sizing of Photovoltaic Wind Battery System Integrated With Vehicle-To-Grid Using Cuckoo Search Algorithm

22

Abdulgader H Alsharif, Chee Wei Tan, Razman Ayop and Kwan Yiew Lau (School of Electrical Engineering Universiti Teknologi Malaysia, UTM Johor Bahru, Malaysia);

Chuen Ling Toh (Department of Electrical and Electronic Engineering Universiti Tenaga National Kajang, Malaysia)

1A6 Design and Integration of Valves Controller for Drone Monitored Solar Irrigation System

28

Firas Basim Ismail Alnaimi, Muhammad Luqman Syakir Rosli, Mohamed Najah Mahdi (Universiti Tenaga Nasional, Malaysia), Ranjani Vasu (GSPARX Tenaga Nasional Berhad)

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Session 1B: Power Converters

Session chairs: Naziha Ahmad Azli & Mohd Zaki Daud

1B1 Comparison of Efficiency of Double Conversion UPS With LC, LCL and LCL With Damping Resistor Filters

34

Robinson Kong and Mohd Zaki Daud (Universiti Teknologi Malaysia, Malaysia); Lee Kar Kuan (Universiti Teknlogi Malaysia, Malaysia)

1B2 Design of a Half-Bridge Converter for Self-Adapting Capacitive Wireless Power Transfer

40 Norbert Seliger (Technische Hochschule Rosenheim, Germany)

1B3 Multiple Input Single Output Converter With Uneven Load Sharing Control for Improved Efficiency

46

Kristen Chan, Taufik (Cal Poly State University, USA), Rini Nur Hasanah (Universitas Brawijaya Malang, Indonesia), Suprapto, Mentari Putri Jati, Aris Nasuha (Universitas Negeri Yogyakarta Yogyakarta, Indonesia)

1B4 Lithium-Ion Cell Balancing Using Auxiliary Battery and DC/DC Unidirectional Converter

52

Mohd Junaidi Abd Aziz (Universiti Teknologi Malaysia, Malaysia), Muhammad Hazwan Hashim, Mohd Saiful Jamaluddin, Mohd Hafidzuddin Sam Hun (Kolej Kemahiran Tinggi Mara Pasir Mas Kelantan, Malaysia)

1B5 Model Predictive Control for DC-DC Boost Converters 58 Ashish Choubey (PDPM, IIITDM, India); Sachin Kumar Jain (PDPM IIITDM Jabalpur, India); Prabin Padhy (PDPM, IIITDM Jabalpur (M. P.) India, India)

1B6 Phase-Shifted LLC Resonant DC-DC Converter for Battery Charging Application 64 Salah Alatai (Universiti Sains Malaysia, Malaysia & Bani Waleed University, Libya);

Mohamed Salem (Universiti Sains Malaysia (USM), Malaysia); Dahaman Ishak, Ali Bughneda and Mohamad Kamarol Mohd Jamil (Universiti Sains Malaysia, Malaysia);

Doudou N. Luta (University of Technology Cape Town, South Africa)

1B7 IMC-PID Control for Bidirectional Three Phase Active Front End Rectifier for Reference Tracking and Disturbance Rejection Capabilities

69

Azizah Abdul Razak, Norjulia Mohamad Nordin and Naziha Ahmad Azli (Universiti Teknologi Malaysia, Malaysia)

Session 1C: Inverters

Session chairs: Shahrin Md Ayob & Nik Din Mohamed

1C1 Open Circuit Fault Diagnosis for Multi-Level Inverters Using an Improved Current Distortion Method

75

Laith M. Halabi (Ajou University); Ibrahim M Alsofyani and Kyo-Beum Lee (Ajou University, Korea (South))

1C2 Open Fault Tolerant Method Using DPWM for Reducing Switching Loss in Three- Level Hybrid ANPC Inverter

80 Ha-Rang Jo (Ajou University, Korea (South)); Youngjong Ko (Pukyong National University, Korea (South)); Kyo-Beum Lee (Ajou University, Korea (South))

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1C3 Performance Analysis of FCS-MPC Using the Generalized Formulation and Euler Method on Switched-Battery Boost Multilevel Inverter

85

Ahmad Takiyuddin Abdullah (Universiti Teknologi Malaysia & Universiti Kuala Lumpur Malaysia France Institute, Malaysia); Sevia Mahdaliza Idrus (Faculty Of Electrical Engineering & Universiti Teknologi Malaysia, Malaysia); Shahrin Md. Ayob (Universiti Teknologi Malaysia, Malaysia)

1C4 Quasi-Z-Source Four-Switch Three-Phase Inverter With Split Capacitor DC-Link Voltage Input

91

Izni Mustafar (Universiti Teknologi Malaysia, Malaysia & Universiti Sains Islam Malaysia, Malaysia); Naziha Ahmad Azli and Norjulia Mohamad Nordin (Universiti Teknologi Malaysia, Malaysia)

1C5 Single Phase Nine-Level Symmetrical Inverter Topology With Reduced Switch Count and Total Standing Voltage

97

Farogh Alam (Aligarh Muslim University, India); M Saad Bin Arif, Shahrin Md. Ayob and Razman Ayop (Universiti Teknologi Malaysia, Malaysia)

1C6 Zero-Sequence Circulating Current Suppression in Multi-Paralleled Three-Level NPC Inverters Under Unbalanced Operating Conditions

103 Kyo-Beum Lee and Jun-Hyeok Park (Ajou University, Korea (South))

Session 2A: Energy Conversion 1

Session Chairs: Toh Chuen Ling & NorJulia Mohamad Nordin

2A1 Characterization and Optimization of Lattice-Matched InGaAs TPV Cell for Waste Heat Harvesting

108

Mansur Gamel (Universiti Tenaga Nasional & Institute of Electrical Engineering, Malaysia); Pin Jern Ker (University Tenaga Nasional, Malaysia); Hui Jing Lee and M A Hannan (Universiti Tenaga Nasional, Malaysia)

2A2 Evaluation of Triboelectric Energy Generators Based on Military Textiles 114 Joseph Olanrewaju Adegite, Aaron McCutcheon, Nancy Nguyen, Eric Scholz, Rebecca

Serven, Spencer Tess, Gregory Noetscher and Pratap Rao (Worcester Polytechnic Institute, USA)

2A3 Experimental Investigations of FOV for Conventional and Hybrid Cylindrical Spacers in Compressed N2: SF6 Gas Mixture Under AC Voltages

120 Aman Ulla (Visvesvaraya Technological University, India)

2A4 Novel Method for Estimating State of Health for Lead-Acid Batteries 125 Ali Asger Khattab (IIT Bombay, India)

2A5 Optimization of InGaAsSb Thermophotovoltaic Cell for Waste Heat Harvesting Application

130

Rafiqi Rosli, Hui Jing Lee and Md Zaini Jamaludin (Universiti Tenaga Nasional, Malaysia); Mansur Gamel (Universiti Tenaga Nasional & Institute of Electrical Engineering, Malaysia); Pin Jern Ker (University Tenaga Nasional, Malaysia)

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2A6 Simulation and Visualization of Occupancy-Based Energy Consumption in Campus Building Using SCADA Software

136

Aryuanto Soetedjo and Sotyohadi Sotyohadi (National Institute of Technology (ITN) Malang, Indonesia)

Session 2B: Energy Conversion 2

Session chairs: Mohd Junaidi Abd Aziz & Awang Jusoh

2B1 A Refined Predictive Torque Control for Two-Level Voltage Source Inverter of Induction Motor

142

Rozana Alik, Norjulia Mohamad Nordin and Nik Rumzi Nik Idris (Universiti Teknologi Malaysia, Malaysia)

2B2 Coal Fuel Efficiency With Mixed Palm Shell Biomass for Steam Power Plant 148 Hamzah Eteruddin, Muhammad Ridwan, Monice Monice and Zulfahri Zulfahri

(Universitas Lancang Kuning, Indonesia); Yanuar Arief (UNIMAS, Malaysia);

Fathimah Hasanti (Universiti Teknologi Malaysia, Malaysia)

2B3 Continuous-Time Sigma-Delta Modulator With Oscillator for Phase Locked Loop Wireless Controlled Power Applications

154 Wen Cheng Lai (National Taiwan University of Science and Technology, Taiwan)

2B4 Fuzzy Gain Scheduling for Cascaded PI-Control for DC Motor 158 Deany Putri Aulia, Alfiyah Yustin and Amien Hilman (Pertamina University, Indonesia); Aulia Annisa and Wahyu Kunto Wibowo (Universitas Pertamina, Indonesia)

2B5 Point Absorber With Direct-Drive Power Take-Off System for Low Wave Application

163

Jariyati Burhanudin and Asnor Mazuan Ishak (Universiti Pertahanan Nasional Malaysia, Malaysia); Taib Ibrahim (Universiti Teknologi Petronas, Malaysia); Ahmad Shukri Abu Hasim, Syed Mohd Fairuz Syed Mohd Dardin and Jariyani Burhanudin (Universiti Pertahanan Nasional Malaysia, Malaysia)

2B6 Reducing Power Loss Considering Massive Charging Station Using Metaheuristic Technique

169

Syed Norazizul Syed Nasir (Universiti Teknologi Malaysia, Malaysia); Wan Yusrizal Wan Yusoff (Tenaga Nasional Berhad, Malaysia); Jasrul Jamani Jamian and Razman Ayop (Universiti Teknologi Malaysia, Malaysia)

2B7 Modelling and Analysis of 18-Pulse Rectification System for DC Traction Power Substation

174 Chuen Ling Toh and Azrul Ikhwan Muhamad Shukran (Universiti Tenaga Nasional,

Malaysia); Chee Wei Tan (Universiti Teknologi Malaysia, Malaysia)

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Session 2C: Power Quality and Power System Session chairs: Lau Kwan Liew & Mohd Rodhi Sahid

2C1 Active Power Filtering Solution for Improving Power Quality in Cold Ironed Electric Ships

180

Rahman Syed and Roberto Cervantes (Texas A&M University, USA); Irfan A Khan (Texas A&M University USA, USA); Atif Iqbal (Qatar University, Qatar); Shahrin Md.

Ayob (Universiti Teknologi Malaysia, Malaysia)

2C2 Analysis of Droop Control for Emulating Grid Synchronization Mechanism 185 Ronald Jackson and Shamsul Zulkifli (Universiti Tun Hussein Onn Malaysia, Malaysia); Mohamed Benbouzid (University of Brest, France); Suriana Salimin, Mubashir Khan and Garba Elhassan (Universiti Tun Hussein Onn Malaysia, Malaysia)

2C3 Energy Management Strategy and Capacity Planning of an Autonomous Microgrid: A Comparative Study of Metaheuristic Optimization Searching Techniques

190

Abba Lawan Bukar, Chee Wei Tan and Kwan Yiew Lau (Universiti Teknologi Malaysia, Malaysia); Chuen Ling Toh (Universiti Tenaga Nasional, Malaysia); Razman Ayop (Universiti Teknologi Malaysia, Malaysia); Ahmed Tijjani Dahiru (School of Electrical Engineering, Universiti Teknologi Malaysia, Malaysia)

2C4 Investigation of Single-Band and Multi-Band Power System Stabilizers Towards Transient Stability Improvement in Electrical Networks

196

Ahmad Adel Alsakati and Chockalingam Aravind Vaithilingam (Taylor's University, Malaysia); Jamal Alnasseir (Damascus University, Syria); Arthanari Jagadeeshwaran (Sona College of Technology, India)

2C5 Review of Market Clearing Method for Blockchain-Based P2P Energy Trading for Microgrid System

202

Nor Ashbahani Mohamad Kajaan, (Universiti Malaysia Perlis, Malaysia), Zainal Salam, Raja Zahilah Raja Mohd Radzi (Universiti Teknologi Malaysia, Malaysia)

2C6 Blockchain Applications and Challenges in Smart Grid 208 Ibrahim Alhamrouni (British Malaysian Institute, Universiti Kuala Lumpur); Younes

Zahraoui (British Malaysian Institute, Universiti Kuala Lumpur, Malaysia)

2C7 Stability Analysis in a Grid-Interactive Residential Nanogrid Using Markov Chains

214

Ahmed Tijjani Dahiru (School of Electrical Engineering, Universiti Teknologi Malaysia, Malaysia); Chee Wei Tan and Kwan Yiew Lau (Universiti Teknologi Malaysia, Malaysia); Chuen Ling Toh (Universiti Tenaga Nasional, Malaysia); Abba Lawan Bukar and Sani Salisu (Universiti Teknologi Malaysia, Malaysia)

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IEEE Copyright

2021 IEEE Conference on Energy Conversion (CENCON)

Copyright and Reprint Permission: Abstracting is permitted with credit to the source. Libraries are permitted to photocopy beyond the limit of U.S. copyright law for private use of patrons those articles in this volume that carry a code at the bottom of the first page, provided the per- copy fee indicated in the code is paid through Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923.

For reprint or republication permission, email to IEEE Copyrights Manager at pubs- [email protected].

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Copyright ©2021 by IEEE.

IEEE CATALOG NUMBER: CFP21CEO-ART

ISBN : 978-1-6654-0129-6

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Author Index

Aaron McCutcheon (Worcester Polytechnic Institute, USA) 2A2

Abba Lawan Bukar (Universiti Teknologi Malaysia, Malaysia) 2C3, 2C7 Abdulgader H Alsharif (Universiti Teknologi Malaysia, Malaysia) 1A5

Ahmad Adel Alsakati (Taylor's University, Malaysia) 2C4

Ahmad Shukri Abu Hasim (Universiti Pertahanan Nasional Malaysia, Malaysia) 2B5 Ahmad Takiyuddin Abdullah (Universiti Teknologi Malaysia Malaysia) 1C3 Ahmed Tijjani Dahiru (Universiti Teknologi Malaysia, Malaysia) 2C3, 2C7 Akmeemanage Don Dinul Manjitha (General Sir John Kotelawala Defence University, Sri Lanka) 1A2

Alfiyah Yustin (Universitas Pertamina, Indonesia) 2B4

Ali Asger Khattab (IIT Bombay, India) 2A4

Ali Bughneda (Universiti Sains Malaysia, Malaysia) 1A1, 1B6

Ali Bughneda (Universiti Sains Malaysia, Malaysia)

Aman Ulla (Visvesvaraya Technological University, India) 2A3

Amien Hilman (Universitas Pertamina, Indonesia) 2B4

Aris Nasuha (Universitas Negeri Yogyakarta Yogyakarta, Indonesia) 1B3 Arthanari Jagadeeshwaran (Sona College of Technology, India) 2C4 Aryuanto Soetedjo (National Institute of Technology (ITN) Malang, Indonesia) 2A6

Ashish Choubey (PDPM, IIITDM, India) 1B5

Asnor Mazuan Ishak (Universiti Pertahanan Nasional Malaysia, Malaysia) 2B5

Atif Iqbal (Qatar University, Qatar) 2C1

Aulia Annisa (Universitas Pertamina, Indonesia) 2B4

Awang Jusoh (Universiti Teknologi Malaysia, Malaysia) 1A4

Azizah Abdul Razak (Universiti Teknologi Malaysia, Malaysia) 1B7 Azrul Ikhwan Muhamad Shukran (Universiti Tenaga Nasional, Malaysia) 2B7

Chee Wei Tan (Universiti Teknologi Malaysia, Malaysia) 1A4, 1A5, 2B7,

2C3, 2C7 Chockalingam Aravind Vaithilingam (Taylor's University, Malaysia) 2C4

Chuen Ling Toh (Universiti Tenaga Nasional, Malaysia) 1A5, 2B7, 2C3

2C7

Dahaman Ishak (Universiti Sains Malaysia, Malaysia) 1A1, 1B6

Deany Putri Aulia (Universitas Pertamina, Indonesia) 2B4

Doudou N. Luta (University of Technology Cape Town, South Africa) 1B6

Eric Scholz (Worcester Polytechnic Institute, USA) 2A2

Farogh Alam (Aligarh Muslim University, India) 1C5

Fathimah Hasanti (Universiti Teknologi Malaysia, Malaysia) 2B2

Firas Basim Ismail Alnaimi (Universiti Tenaga Nasional, Malaysia) 1A6 Garba Elhassan (Universiti Tun Hussein Onn Malaysia, Malaysia) 2C2

Gregory Noetscher (Worcester Polytechnic Institute, USA) 2A2

Hamzah Eteruddin (Universitas Lancang Kuning, Indonesia) 2B2

Ha-Rang Jo (Ajou University, South Korea) 1C2

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Hui Jing Lee (Universiti Tenaga Nasional, Malaysia) 2A1, 2A5

Ibrahim Alhamrouni (Universiti Kuala Lumpur, Malaysia) 2C6

Ibrahim M Alsofyani (Ajou University, South Korea) 1C1

Irfan A Khan (Texas A&M University USA, USA) 2C1

Izni Mustafar (Universiti Sains Islam Malaysia, Malaysia) 1C4

Jamal Alnasseir (Damascus University, Syria) 2C4

Jariyani Burhanudin (Universiti Pertahanan Nasional Malaysia, Malaysia) 2B5 Jariyati Burhanudin (Universiti Pertahanan Nasional Malaysia, Malaysia) 2B5 Jasrul Jamani Jamian (Universiti Teknologi Malaysia, Malaysia) 2B6 Joseph Olanrewaju Adegite (Worcester Polytechnic Institute, USA) 2A2

Jun-Hyeok Park (Ajou University, South Korea) 1C6

Khlid Ben Hamad (Cape Peninsula University of Technology, South Africa) 1A1

Kristen Chan (Cal Poly State University, USA) 1B3

Kwan Yiew Lau (Universiti Teknologi Malaysia, Malaysia) 1A5, 2C3, 2C7

Kyo-Beum Lee (Ajou University, South Korea) 1C1, 1C2, 1C6

Laith M. Halabi (Ajou University, South Korea) 1C1

Lee Kar Kuan (Universiti Teknlogi Malaysia, Malaysia) 1B1

M A Hannan (Universiti Tenaga Nasional, Malaysia) 2A1

M Saad Bin Arif (Universiti Teknologi Malaysia, Malaysia) 1C5

Mansur Gamel (Universiti Tenaga Nasional, Malaysia) 2A1, 2A5

Md Zaini Jamaludin (Universiti Tenaga Nasional, Malaysia) 2A5

Mohamad Kamarol Mohd Jamil (Universiti Sains Malaysia, Malaysia) 1A1, 1B6

Mohamed Benbouzid (University of Brest, France) 2C2

Mohamed Najah Mahdi (Universiti Tenaga Nasional, Malaysia) 1A6

Mohamed Salem (Universiti Sains Malaysia, Malaysia) 1A1, 1B6

Mohd Hafidzuddin Sam Hun (Kolej Kemahiran Tinggi Mara Pasir Mas Kelantan, Malaysia) 1B4 Mohd Junaidi Abd Aziz (Universiti Teknologi Malaysia, Malaysia) 1B4

Mohd Rodhi Sahid (Universiti Teknologi Malaysia, Malaysia) 1A4

Mohd Saiful Jamaluddin (Kolej Kemahiran Tinggi Mara Pasir Mas Kelantan, Malaysia) 1B4

Mohd Zaki Daud (Universiti Teknologi Malaysia, Malaysia) 1A4, 1B1

Monice Monice (Universitas Lancang Kuning, Indonesia) 2B2

Mubashir Khan (Universiti Tun Hussein Onn Malaysia, Malaysia) 2C2 Muhammad Akmal Johar (Universiti Tun Hussein Onn Malaysia, Malaysia) 1A3 Muhammad Hazwan Hashim (Kolej Kemahiran Tinggi Mara Pasir Mas Kelantan, Malaysia) 1B4 Muhammad Luqman Syakir Rosli (Universiti Tenaga Nasional, Malaysia) 1A6

Muhammad Ridwan (Universitas Lancang Kuning, Indonesia) 2B2

Nancy Nguyen (Worcester Polytechnic Institute, USA) 2A2

Naziha Ahmad Azli (Universiti Teknologi Malaysia, Malaysia) 1B7, 1C4 Nik Rumzi Nik Idris (Universiti Teknologi Malaysia, Malaysia) 2B1 Nor Ashbahani Mohamad Kajaan (Universiti Malaysia Perlis, Malaysia) 2C5

Norbert Seliger (Technische Hochschule Rosenheim, Germany) 1B2

Norjulia Mohamad Nordin (Universiti Teknologi Malaysia, Malaysia) 1B7, 1C4, 2B1

Pin Jern Ker (University Tenaga Nasional, Malaysia) 2A1, 2A5

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Prabin Padhy (PDPM, IIITDM Jabalpur (M. P.) India, India) 1B5

Pratap Rao (Worcester Polytechnic Institute, USA) 2A2

Rafiqi Rosli (University Tenaga Nasional, Malaysia) 2A5

Rahman Syed (Texas A&M University, USA) 2C1

Raja Zahilah Raja Mohd Radzi (Universiti Teknologi Malaysia, Malaysia) 2C5

Ranjani Vasu (GSPARX Tenaga Nasional Berhad, Malaysia) 1A6

Razman Ayop (Universiti Teknologi Malaysia, Malaysia) 1A4, 1A5, 1C5,

2B6, 2C3

Rebecca Serven (Worcester Polytechnic Institute, USA) 2A2

Rini Nur Hasanah (Universitas Brawijaya Malang, Indonesia) 1B3

Roberto Cervantes (Texas A&M University, USA) 2C1

Robinson Kong (Universiti Teknologi Malaysia, Malaysia) 1B1

Ronald Jackson (Universiti Tun Hussein Onn Malaysia, Malaysia) 2C2

Rozana Alik (Universiti Teknologi Malaysia, Malaysia) 2B1

Sachin Kumar Jain (PDPM IIITDM Jabalpur, India) 1B5

Salah Alatai (Bani Waleed University, Libya) 1A1, 1B6

Sani Salisu (Universiti Teknologi Malaysia, Malaysia) 2C7

Sevia Mahdaliza Idrus (Universiti Teknologi Malaysia, Malaysia) 1C3

Shahrin Md. Ayob (Universiti Teknologi Malaysia, Malaysia) 1A4, 1C3, 1C5, 2C1

Shamsul Zulkifli (Universiti Tun Hussein Onn Malaysia, Malaysia) 2C2 Siti Amely Jumaat (Universiti Tun Hussein Onn Malaysia, Malaysia) 1A3 Sotyohadi Sotyohadi (National Institute of Technology (ITN) Malang, Indonesia) 2A6

Spencer Tess (Worcester Polytechnic Institute, USA) 2A2

Suprapto, Mentari Putri Jati (Universitas Negeri Yogyakarta Yogyakarta, Indonesia) 1B3 Suriana Salimin (Universiti Tun Hussein Onn Malaysia, Malaysia) 2C2 Syed Mohd Fairuz Syed Mohd Dardin (Universiti Pertahanan Nasional Malaysia, Malaysia) 2B5 Syed Norazizul Syed Nasir (Universiti Teknologi Malaysia, Malaysia) 2B6

Taib Ibrahim (Universiti Teknologi Petronas, Malaysia) 2B5

Taufik (Cal Poly State University, USA) 1B3

Udaya Santha Rahubadde (Kotelawala Defence Univerisity, Sri Lanka) 1A2 Umar Abubakar Saleh (Prince Audu Abubakar University Anyigba, Kogi, ) 1A3

Wahyu Kunto Wibowo (Universitas Pertamina, Indonesia) 2B4

Wan Akasha Wan Jamaluddin (University Tun Hussein Onn Malaysia, Malaysia) 1A3

Wan Yusrizal Wan Yusoff (Tenaga Nasional Berhad, Malaysia) 2B6

Wen Cheng Lai (National Taiwan University of Science and Technology, Taiwan) 2B3

Yanuar Arief (UNIMAS, Malaysia) 2B2

Younes Zahraoui (Universiti Kuala Lumpur, Malaysia) 2C6

Youngjong Ko (Pukyong National University, South Korea) 1C2

Zainal Salam (Universiti Teknologi Malaysia, Malaysia) 2C5

Zulfahri Zulfahri (Universitas Lancang Kuning, Indonesia) 2B2

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Biomass for Steam Power Plant

Hamzah Eteruddin Dept. of Electrical Engineering,

Faculty of Engineering Universitas Lancang Kuning

(UNILAK),

Jl. Yos Sudarso, km 8 Rumbai, 28265 Rumbai, Riau, Indonesia

[email protected] Zulfahri

Dept. of Electrical Engineering, Faculty of Engineering Universitas Lancang Kuning

(UNILAK),

[email protected]

Muhammad Ridwan Dept. of Electrical Engineering,

Faculty of Engineering Universitas Lancang Kuning

(UNILAK),

[email protected] Yanuar Z. Arief

Dept. of Electrical and Electronic Eng., Faculty of Engineering Universiti Malaysia Sarawak

(UNIMAS)

Kota Samarahan, Sarawak, Malaysia [email protected]

Monice

Dept. of Electrical Engineering, Faculty of Engineering Universitas Lancang Kuning

(UNILAK),

[email protected] Fathimah Hasanti Dept. of Computer Network &

Security, Faculty of Engineering Universiti Teknologi Malaysia (UTM)

Skudai, Johor Bahru, Malaysia [email protected]

Abstract—The accumulation of coal-based fuels is depleting and to obtain coal fuel requires a great amount of money, as a corollary, measures must be taken to reduce the usage of this fuel. PT. Pembangkit Jawa Bali (PJB) is currently investigating the co-firing technique by using oil palm shell biomass waste as a combination coal fuel with a proportion of 95% coal and 5%

palm shell, the efficiency results will be compared to 100% of coal fuel. In this research, the Mathcad program and the Professional Simulator 8 were employed, the specific fuel consumption (SFC) technique is used to determine the efficiency of production expenses, as well as the direct and indirect methods to calculate the boiler efficiency. The results reveal that 4.09 IDR/kWh reduction in primary energy expenses could be achieved (0.65%). Co-firing fuel will undoubtedly have a significant impact on the boiler's performance, therefore when using 100% of coal as a fuel, the boiler efficiency value is 63.38%

(Direct Method), while using the Indirect Method will produce up to 82.24%, respectively. However, when using co-firing fuel with 95% of coal and 5% of palm shell (Direct Method), the boiler efficiency value is 63.92%, and 83.71% when using the Indirect Method.

Keywords— Co-firing method, production cost efficiency, palm shell, biomass, boiler efficiency, direct method, indirect method

I. INTRODUCTION

Electric power generation, both new renewable energy and fossil energy generation, has been widely investigated [1]–[6].

A boiler in a Steam Power Plant (SPP) is a facility that transforms liquid water to steam. Boilers use Circulating Fluidized Bed Combustion (CFBC) as one of its technologies [7–10]. The system has several advantages of working principles such as a compact boiler design, fuel flexibility, high combustion efficiency and low emission of harmful pollutants such as Sulfur Oxide (SOx) and Nitrogen Oxide (NOx) [7]. Coal is the primary fuel, however biomass such as palm shells, sawdust, or other agricultural waste can also be used in boilers only if it mixed. [11–13].

The SPP Tenayan power station in Riau province, Indonesia has a capacity of 2×110 MW and it is one of the PLN power plants run by PT. PJB that utilizes low calories or Low Rank Coal (LRC) with a heating value of 3,800 – 4,700

kCal/kWh as a fuel [14], [15]. LRC has a high sulfur concentration, which is bad for equipment, particularly the tube Boiler. SPP Tenayan uses a Circulating Fluidized Bed (CFB) boiler, which has a wide range of fuel options, high combustion efficiency, effective sulfur absorption, low NOx emissions, and a lower furnace cross section. [16], [17].

Riau Province is home to a palm oil plant with a capacity of 12,170 tons per hour [18]. The potential for Palm Kernel Shell (PKS) or biomass waste is very substantial in terms of shifting away from reliance on fossil fuels and toward green power plants. Increasing the Medium-Rank Coal (MRC) ratio, contributed to higher furnace bed and intake cyclone temperatures [15], [19]. Meanwhile, the implementation of CFB at the SPP Tenayan supports co-firing experiments using palm shell biomass. This study discusses the comparison of the fuel efficiency of pure coal and coal with a mixture of PKS biomass in Boiler Unit 2 at PT. PJB Tenayan Raya using specific fuel consumption technique (SFC).

II. METHOD

The Specific Fuel Consumption (SFC) can be used to determine an-engine's economic value [20], [21]. SPLN No.

80 (1989) says, this parameter can be used to compute the amount of fuel required to create a specified amount of power in a given time interval. The following are some of the formulas that are used to calculate the particular fuel consumption [22]:

a) Specific Fuel Consumption Brutto (SFCB)

6 3

3.6 10 10 g/kWh (h LHV)

f eff

SFC m P

= × = (1)

Where mf is the fuel consumption in kg/s, Peff is power (brake) effective machine, the efficiency (η) of the engine, and LHV which is the lower calorific value fuel in kWh/kg, SFC gross = Qf/(kWh(gross)).

b) Specific Fuel Consumption Netto (SFCN) SFC netto = Qf/(kWh(netto))

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rate:

a). Heat Rate brutto (HRB) = (Mf ×LHV)/(kWhB) b). Heat Rate netto (HRN) = (Mf ×LHV)/(kWhB-kWhPS) Where:

Qf : Quantity of coal used (kg)

LHV : Lower calorific value of the utilized fuel (kCal/kg) HHV : Higher calorific value of the utilized fuel (kCal/kg) kWhB : Number of kWh generated by generator (kWh) kWhps : Number of kWh required for personal use (kWh) Mf : Fuel weight during test (kg)

Heat Rate Brutto (HRB) is the amount of fuel heat computed to produce each gross kWh based on the calorific value (LHV). The following is the formula for estimating the cost of producing energy per kWh. Electricity production cost is SFCnett (kg/kWh) x Coal price (IDR/kg).

Boiler Efficiency

The percentage of fuel heat energy (heat input) that is effectively used in the steam produced is referred to as a boiler's thermal efficiency. Alternatively, boiler efficiency is referred to as the work performance or level of boiler performance determined from the comparison of the energy transmitted to the working fluid or absorbed by the working fluid in the boiler with the heat energy input of the fuel.

According to the USA Standard ASME PTC 4-1 Power Test Code for Steam Generating Units, there are two methods for evaluating boiler efficiency are Direct Method, where energy is transferred to the working fluid (water and steam) rather than the heat energy of the fuel boilers, and the Indirect Method, where efficiency is the difference between the percentage of heat entering and the percentage of loss that occurs [23].

A. Direct Method

An engine's efficiency is a measurement of its performance. The value of the level of boiler performance capability resulting from a comparison of energy output (output) and energy input (input) is defined as the efficiency of the boiler engine. The direct / input – output technology is mainly referred as because the efficiency value is calculated by dividing the output or output (steam) with the heat input or input (fuel). As a result, the boiler efficiency (ƞBoiler) equation is (heat output)/(heat input)×100%, or as follows [24], [25]:

ƞBoiler = 𝑄𝑄 (ℎ𝑔𝑔−ℎ𝑓𝑓)

𝑞𝑞 ×𝐺𝐺𝐺𝐺𝐺𝐺 × 100%

Where:

Q = Total steam yield (kg/hour).

q = Total fuel consumption (kg/hour).

hg = Saturated steam enthalpy (kkal/kg).

hf = Feed water enthalpy (kkal/kg).

GCV = Fuel gross heat value (kkal/kg).

B. Indirect Method

The indirect method utilizes the difference between the input energy and the losses. This technique is often referred to as the heat loss technique. A coal-fired boiler and a fuel analysis provide the necessary information for the indirect technique. There are several things in the Coal fired boiler data, such as: the amount of fuel that enters every hour, the

the steam output, the temperature of the feed water, the content of CO2 and CO levels, the temperature of the exhaust gases, the ambient temperature, the humidity of the ambient air, the surface temperature of the boiler, wind speed around the boiler, the total surface area of the boiler, the GCV value of bottom ash and fly ash. The fuel analysis data includes information on coal's ash content, carbon, hydrogen, nitrogen, oxygen, sulfur, and HHV values. The boiler has eight heat losses, as shown in the calculation below, according to the ASME PTC 4-1 standard.

a). Estimate the total heat loss (%).

Heat loss due to dry flue gas (L1) L1 = (m×cp×(Tf-Ta))/GCV ×100 Where:

m = Mass of dry exhaust gas (kg/fuel)

Cp = Specific heat of dry exhaust gas (kCal/kg) GCV= Calorific coal value (kCal/kg)

Tf = Exhaust gas temperature (°C) Ta = Temperature ambient (°C) b). Heat loss due to H2 in fuel (L2)

L2 = (9×H2×(584×Cp(Tp-Cp)))/GCV 100 Where:

H2 = The number of hydrogen atoms in the fuel (kg/kg fuel)

Cp = Specific heat of superheated steam (kCal/kg) 584 = The latent heat associated with the partial pressure

of water vapor (kCal/kg) GCV= Calorific coal value (kCal/kg) Tf = Exhaust gas temperature (°C) Ta = Temperature ambient (°C) c). Heat loss due to moisture in fuel (L3)

L3 = (M×(584×CP(Tf-Ta)))/GCV 100 Where:

M = Moisture in fuel (kg/kg fuel)

Cp = Specific heat of superheated steam (kCal/kg 0C) 584 = The latent heat associated with the partial pressure

of water vapor (kCal/kg) GCV= Calorific coal value (kCal/kg) Tf = Exhaust gas temperature (°C) Ta = Temperature ambient (°C) d). Heat loss due to moisture in air (L4)

L4 = (AAS×humidity factor×Cp(Tf-Ta))/GCV 100 Where:

AAS = Actual mass of air (kg/kg fuel) Humidity factor = 0,023

Cp = Specific heat of superheated steam (kCal/kg) GCV = Calorific coal value (kCal/kg)

Tf = Exhaust gas temperature (°C) Ta = Temperature ambient (°C)

e). Heat loss due to incomplete combustion (L5) L5 =(%CO×C×5744)/((%CO+%CO2)×GCV)×100

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CO = Volume of CO in exhaust gas (%) CO2 = Actual volume of CO2 in exhaust gas (%) C = Carbon content (kg/kg fuel)

GCV = Calorific coal value (kCal/kg) f). Heat loss due to radiation and convection (L6)

4 4

6 0.548 1.25

1

1 9

.957 ( )

55.5 9

5 5

6.85 68

.55 .

L Ts 5Ta Ts a

Vm

 T

  

    + −

 

= × −  ×

 

× ×

 

+ Where:

Vm = Wind velocity (m/s) Ts = Surface temperature (K) Ta = Temperature ambient (K) g). Heat loss due unburnt in fly ash (L7)

(Total Ash Collected/kg of Fuel Burn) GCV of Fly 0 l

Ash 10 7 t

of Fue

L GVC

×

 

= ×

 

h). Heat loss due unburnt in bottom ash (L8) GCV of Fly Ash 100

8

of Fuel Total botom colected fuel

L GVC

 × 

= ×

 

Boiler efficiency is obtained by subtracting 100 with all losses

η𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏 = 100 – (𝐿𝐿1 + 𝐿𝐿2 + 𝐿𝐿3 + 𝐿𝐿4 + 𝐿𝐿5 + 𝐿𝐿6 + 𝐿𝐿7 + 𝐿𝐿8)

III. RESULT AND DISCUSSION

The SFC comparison was calculated at a load of 89 MW Gross in two fuel trials, namely circumstances utilizing 100%

coal and co-firing conditions using 5% Palm Shells, as shown in Table 1.

TABLE I. SFCCALCULATIONS FOR OPERATING CONDITIONS

Parameter Co-Firing Test

0 % PKS 5 % PKS

Gross Load Setting, MW 89.00 89.00

Gross Electrical Energy, kWh 350,276 346,680 Net Electrical Energy, kWh 306,081 302,749 2A CF Fuel Consumption, kg 50,219 54,594 2B CF Fuel Consumption, kg 100,000 102,000 2C CF Fuel Consumption, kg 103,000 92,000 2D CF Fuel Consumption, kg 52,000 48,000 Total Fuel Consumption, kg 305,219 296,594 Specific Fuel Consumption, kg/kWh 0.871 0.856

Table 1 shows the results of SFC calculations for operating conditions involving 100% coal and 5% palm shell co-firing.

Figure 1 shows a comparison of Specific Fuel Consumption (SFC) for 100% coal and co-firing 95% coal 5

% palm shells.

Fig. 1. Comparisson graph of SFC values of 100% Coal and 5% Palm Oil.

Specific fuel consumption Rp. 0.871 kg/kWh with 100%

coal and Rp. 0.856 kg/kWh for (95% BB + 5%PKS).

a) Production cost of 100% coal:

Production price

= Coal Price× SFC 100% BB

= 720 IDR/kg × 0.871 kg/kWh

= 627.38 IDR/kWh

Production cost of co-firing 5%:

Production price

= Cost (5% PKS+95%BB)×SFC co-firing 5%

= {(0.05 × Rp. 900 + 0.95 × Rp.720)}×0.855/kWh

= Rp. 623.29 /kWh

As a result, when 5% palm shells are co-fired with 100%

coal, the difference in production costs is:

= 627.38 IDR/kWh – 623.29 IDR/kWh

= 4.09 IDR/ kWh

The following calculations are performed to obtain the percentage of production cost efficiency:

= (4.09 IDR/kWh)/(627.38 IDR/kWh) × 100 %

= 0.00651 × 100 % = 0.65%

Based on the aforementioned calculations, the efficiency value of the production cost comparison between 100% coal fuel and co-firing fuel, 95% coal and 5% palm shell, is 4.09 IDR/kWh or 0.65% more efficient co-firing fuel than pure coal fuel.

Boiler Efficiency Comparison

As demonstrated in Table 2, the co-firing fuel 95% coal 5% PKS has a higher boiler efficiency estimate than 100%

coal.

TABLE II. BOILER EFFICIENCY COMPARISON

Fuel Boiler Efficiency Application Results (%) 100 %

Coal

Direct Method MathCad 63.38

Simulator Profesional 8 63.38

Indirect Method MathCad 81.60

Simulator Profesional 8 80.29 95% Coal

&

5% PKS

Direct Method MathCad 63.92

Simulator Profesional 8 63.92

Indirect Method MathCad 83.14

Simulator Profesional 8 83.71 87,10%

85,60%

0%

20%

40%

60%

80%

100%

95% Coal 5% PKS 100% Coal

Efficiency (%)

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The results of the boiler efficiency comparison can be seen in the graph shown in figure 2 below.

Fig. 2. Boiler Efficiency Comparison

According to the results of the boiler efficiency calculations shown in the previous graph, co-firing fuel can increase boiler efficiency by 0.12% using the Direct Method with Mathcad calculations and simulations, while using the Indirect Method calculation can increase boiler efficiency by 1.54% using (Mathcad) and 3.42% using (Simulation).

Palm Shell Demand Co-firing

To enhance the percentage of palm shell biomass in the co- firing test, the required fuel requirements must be predicted, as well as the fuel required to increase the percentage of the co-firing test, as indicated in Table 3.

TABLE III. PREDICTION OF CO-FIRING FUEL DEMAND

Co-firing 24 Hours 30 Days

5 % PKS 95 % Coal 3,648 Tons 109,440 Tons 5 % PKS 192 Tons 5,760 Tons 10 % PKS 90 % Coal 3,456 Tons 103,680 Tons 10 % PKS 384 Tons 11,520 Tons 15 % PKS 85 % Coal 3,264 Tons 97,920 Tons 15 % PKS 576 Tons 17,280 Tons

Based on the results of the survey on palm shell production in Table 3 and the availability of palm shells at PT. ATM and PT. EPE, the percentage of palm shells co-firing experiments should be increased to 10% - 15%. Both companies are still able to help with the current percentage of palm shells available. However, in the long run, the demand for palm shells supplies will grow year after year, so collaboration with other companies that can give palm shells supplies is encouraged to cover the expenses.

Operation Data Parameters During Co-Firing Test Observations were made on several elements that need to be monitored during the co-firing test, which were sourced from the co-firing test report data at PT. PJB SPP Tenayan Raya, to find out the comparison findings achieved in the 100% coal test results and the co-firing test results. When working with 95% coal and 5% palm shells, several factors must be taken into consideration [14].

a) Load – FEGT Temperature

Table 4 shows the results of observing Co-firing operation data on the Furnace Exit Gas Temperature parameter.

Time Load (MW) FEGT (°C)

0% PKS 5% PKS 0% PKS 5% PKS

11:00 88.499 87.455 868.905 843.014

11:30 89.722 86.622 873.548 845.159

12:00 89.145 87.691 859.611 849.094

12:30 87.854 88.045 853.266 852.434

13:00 88.795 87.736 858.735 852.955

13:30 88.559 87.455 860.146 853.092

14:00 88.395 88.499 855.442 855.356

14:30 89.322 88.549 863.058 853.586

15:00 88.982 88.549 860.911 855.898

Fig. 3. Comparison Graph of Furnace Exit Gas Temperature 0% Palm Shell and 5% Palm Shell

When testing co-firing 5% of palm shells with a similar load (89 MW), it is shown that the FEGT value with 5% of palm shells is lower than when using 100% BB. This is due to the fact that PKS has a lower density than coal and a higher Volatile Matter (VM), making PKS more combustible in the bed furnace region while decreasing FEGT values are still safe for operation.

b) Load – Bed Temperature

Table 5 shows the findings of the Bed Temperature parameter observation of the Co-firing operation data.

TABLE V. OBSERVATION OF LOAD OPERATION DATA –BED

TEMPERATURE

Time Load (MW) Bed Temp (°C)

0% PKS 5% PKS 0% PKS 5% PKS

11:00 88.499 87.455 816.305 812.766

11:30 89.722 86.622 818.200 809.775

12:00 89.145 87.691 818.212 812.322

12:30 87.854 88.045 814.707 816.051

13:00 88.795 87.736 817.871 813.810

13:30 88.559 87.455 819.510 811.872

14:00 88.395 88.499 817.331 819.654

14:30 89.322 88.549 821.272 819.340

15:00 88.982 88.549 820.038 821.837

63,8

81,6

63,92

83,14 63,8

80,29

63,92

83,71

0 20 40 60 80 100

100% Coal Direct

method 100% Coal

Indirect Method 95% Coal 5% PKS

Direct Method 95% Coal 5% PKS Indirect Method

Efficiency (%)

Mathcad Simulator

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Fig. 4. Comparison Graph of Bed Temperature 0% Palm Shell and 5%

Palm Shell

Co-firing 5% palm shells with a similar load (89MW) was put to the test. Due to lower density and greater VM than coal, the bed temperature trend tends to increase (up to a maximum of 3 ^oC) when employing 5% PKS, causing combustion to occur in the lower furnace. Meanwhile, the 5% PKS test trend of increasing bed temperature is still safe to operate.

c) Load – Coal Flow

Table 6 shows the findings of observations of Co-firing operation data on Coal Flow characteristics.

TABLE VI. OBSERVATION OF OPERATION DATA LOAD –COAL FLOW

Time Load (MW) Total coal flow (t/h)

0% PKS 5% PKS 0% PKS 5% PKS

11:00 88.499 87.455 76.134 74.139

11:30 89.722 86.622 77.155 74.225

12:00 89.145 87.691 76.478 75.282

12:30 87.854 88.045 76.476 75.923

13:00 88.795 87.736 77.420 74.296

13:30 88.559 87.455 76.012 73.993

14:00 88.395 88.499 78.038 73.890

14:30 89.322 88.549 77.102 75.262

15:00 88.982 88.549 78.790 73.889

Fig. 5. Comparison Graph of Coal Flow 0% Palm Shell and 5% Palm Shell

When testing co-firing 5% palm shells with a similar load (89MW), it shows that: Coal biomass flow is somewhat lower than when using 100% BB, which is related to PKS having a higher calorific value than the coal used in SPP Tenayan. This

cleaner (export standards).

d) Air Chamber Pressure

Table 7 summarizes the output of analyzing the Load – Air Chamber Pressure parameters after watching the Co-firing operation data.

TABLE VII. LOAD –AIR CHAMBER PRESSURE

Time Load (MW) Air Chamber Preasure (Kpa)

0% PKS 5% PKS 0% PKS 5% PKS

11:00 88.499 87.455 12.605 12.569

11:30 89.722 86.622 12.641 12.491

12:00 89.145 87.691 12.674 12.554

12:30 87.854 88.045 12.658 12.426

13:00 88.795 87.736 12.449 12.488

13:30 88.559 87.455 12.531 12.491

14:00 88.395 88.499 12.550 12.606

14:30 89.322 88.549 12.606 12.591

15:00 88.982 88.549 12.414 12.526

Fig. 6. Comparison Graph of Air Chamber Pressure 0% Oil Palm Shells and 5% Palm Shells

When testing co-firing 5% Palm shells with a similar load (89MW), it can be shown that: Air chamber pressure is relatively constant (stable) when examining 5% PKS compared to full coal data, indicating that there is no nozzle obstruction or agglomeration.

e) Load – Sealpot Temperature

Table 8 shows the results of observing the Co-firing operation data on the Load – Sealpot temperature parameters.

TABLE VIII. SEALPOT TEMPERATURE

Time Load (MW) Sealpot Temperature (°C)

0% PKS 5% PKS 0% PKS 5% PKS

11:00 88.499 87.455 932.789 924.835

11:30 89.722 86.622 938.529 921.069

12:00 89.145 87.691 932.593 923.015

12:30 87.854 88.045 928.585 928.503

13:00 88.795 87.736 931.166 927.022

13:30 88.559 87.455 931.476 924.523

14:00 88.395 88.499 931.011 928.580

14:30 89.322 88.549 935.952 928.745

15:00 88.982 88.549 935.738 929.592

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Fig. 7. Comparison Graph of Sealpot Temperature 0% Palm Shell and 5%

Palm Shell

When testing co-firing 5% Palm Shells with a similar load (89 MW), it was discovered that: a). The sealpot temperature was decreased when testing 5% Palm Shells compared to pure coal data, indicating that there is no combustion delay. b).

Before it reaches the sealpot, coal biomass is already burned in the furnace.

IV. CONCLUSION

With SFC difference of 0.016 kg/kWh, a coal price of 720 IDR/kg, and a palm shell price of 900 IDR/kg, the operation at the SPP Tenayan utilizing the co-firing method of 5% palm shells at a load of 89 MW gross can minimize primary energy costs by 4.09 IDR/kWh (0.65%). From Fig. 2 for boiler efficiency, it can be seen that co-firing fuel can boost boiler efficiency by 0.12% (Direct Method), while using the Indirect Method by 1.54% (Mathcad), and 3.42% using Simulator Professional 8, respectively.

Observation of operating conditions on boiler unit 2 of SPP Tenayan with a similar load of 89 MW reveals changes in numerous parameters when the ratio is between 100% coal and 5% co-firing. For instance, FEGT drops by 10 °C, Bed Temperature drops by 4 °C, and coal flow drops by 5 °C, respectively. As a result, the value of SFC decreased to 0,016 kg/kWh.

It can be observed from the calculation results that using 5% of co-firing fuel can reduce production costs as well as enhancing biogas production, thus palm shell percentage must be added to reach a higher efficiency value. In context of Table 3 on palm shell availability for long-term use, it is required to assess the availability of oil palm shells in the Riau area in order to fulfill the long-term fuel demands.

ACKNOWLEDGMENT

We would like to thank to PT. Pembangkit Jawa Bali (PJB) and Universitas Lancang Kuning for providing us the financial and technical support to conduct this study.

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