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<![CDATA[MODIFIED IMPROVED PARTICLE SWARM OPTIMIZATION (MIPSO) SEBAGAI SOLUSI ECONOMIC DISPATCH PADA SISTEM KELISTRIKAN 500 kV JAWA-BALI ]]>
<![CDATA[Kanata, Sabhan]]>;
<![CDATA[Sarjiya, Sarjiya]]>;
<![CDATA[Hadi, Sasongko Pramono]]>
<![CDATA[ Transmisi Vol 15, No 2 (2013): TRANSMISI ]]>
Publisher : <![CDATA[Departemen Teknik Elektro, Universitas Diponegoro ]]>
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DOI: 10.12777/transmisi.15.2.66-72
<![CDATA[Abstrak  Komponen biaya paling besar pada operasi pembangkitan thermal adalah biaya bahan bakar. Permasalahan bagaimana meminimalkan biaya bahan bakar dengan menentukan kombinasi daya output dari masing-masing unit pembangkit dengan kekangan terpenuhinya beban sistem dan batas kemampuan masing-masing unit pembangkit dikenal dengan istilah economic dispatch (ED). Dalam penelitian ini, diusulkan metode Modified Improved Particle Swarm Optimization (MIPSO) dengan pendekatan Contriction Factor Based Particle Swarm Optimization (CFBPSO) Kemudian metode pendekatan ini diterapkan dalam 2 kasus sistem tenaga yaitu pada kasus IEEE 30 bus pada pembebanan 800 MW dan sistem interkoneksi 500 kV Jawa-Bali dengan pembebanan puncak 12058 MW. Dari hasil simulasi IEEE 30 bus, metode MIPSO dengan pendekatan CFBPSO mampu menghasilkan solusi paling optimal ekonomi dibanding metode pendekatan MPSO dan Quadratic Programing. Untuk kasus sistem interkoneksi 500 kV Jawa-Bali, metode MIPSO dengan pendekatan ini juga mampu memberikan solusi paling optimal dibanding dengan sistem real PT. PLN (Persero).  Kata kunci:  economic dispatch (ED), modified improved particle swarm optimization (MIPSO), sistem interkoneksi 500 kV Jawa-Bali.   Abstract The most substantial component of the operating cost of thermal generation is fuel costs. The problem of how to minimize the cost of fuel to determine the combination of the output power of each generating unit with the fulfillment of load constraint systems and limit the ability of each generating unit known as economic dispatch (ED). In this study, the proposed method Modified Improved Particle Swarm Optimization (MIPSO) approach Contriction Factor Based Particle Swarm Optimization (CFBPSO) then this approach is applied in 2 cases the power system in the case of IEEE 30 bus at loading 800 MW and 500 kV power system Java-Bali with 12058 MW peak load.  The IEEE 30 bus simulation results, the method MIPSO with CFBPSO approach is able to produce the most optimal economic solution than MPSO approach and Quadratic Programming. For the case of 500 kV power system is Java-Bali, MIPSO method with this approach is also able to provide the most optimal solution compared with the real system PT. PLN (Persero).  Keywords: economic dispatch (ED), modified improved particle swarm optimization (MIPSO), 500 kV power system in Java-Bali.]]>
<![CDATA[KOMBINASI INERTIA WEIGHT DAN CONSTRICTION FACTOR PADA PARTICLE SWARM OPTIMIZATION SEBAGAI SOLUSI PEMBANGKITAN EKONOMIS PADA SISTEM TENAGA IEEE 26 BUS ]]>
<![CDATA[Sabhan Kanata]]>
<![CDATA[ ELECTRANS Vol 12, No 2 (2013): Volume 12, Nomor 2, Tahun 2013 ]]>
Publisher : <![CDATA[Universitas Pendidikan Indonesia ]]>
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<![CDATA[Komponen biaya paling besar pada operasi pembangkitan thermal adalah biaya bahan bakar.Untuk membuat biaya komsumsi bahan bakar generator atau biaya operasi dari keseluruhan sistem seminimal mungkin dengan menentukan kombinasi daya output dari masing-masing unit pembangkit di bawah kekangan dari tuntutan beban sistem dan batas kemampuan pembangkitan masing-masing unit pembangkit dikenal dengan istilah economic dispatch. Dalam penelitian ini, dilakukan 2 pendekatan yaitu Constriction Factor based Particle Swarm Optimization (CFBPSO) dan kombinasi inertia weight dengan contriction factor(IWCFPSO). Pendekatan ini diterapkan dalam kasus sistem tenaga yaitu pada kasus IEEE 26 bus dengan pembebanan 1.263 MW dimana pendekatan CFBPSO danIWCFPSO menunjukkan hasil yang lebih optimal dibanding metode Improved Particle Swarm Optimization (IPSO), Newton Raphson(NR), dan Genetic Algorithm (GA) namun metode IWCFPSO mampu memberikan solusi lebih cepat dibandingkan dengan metode CFBPSO.]]>
<![CDATA[CFBPSO sebagai Solusi Economic Dispatch pada Sistem Kelistrikan 500 kV Jawa-Bali ]]>
<![CDATA[Sabhan Kanata]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 2 No 4: November 2013 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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<![CDATA[The most substantial component of the operating cost of thermal generation is fuel costs. The problem of how to minimize the cost of fuel to determine the combination of the output power of each generating unit with the fulfillment of load constraint systems and limit the ability of each generating unit known as economic dispatch (ED). In this study, the proposed method Modified Improved Particle Swarm Optimization (MIPSO) approach Contriction Factor Based Particle Swarm Optimization (CFBPSO) then this approach is applied in 2 cases the power system in the case of IEEE 30 bus at loading 800 MW and 500 kV power system Jawa-Bali with 12058 MW peak load. The IEEE 30 bus simulation results, the method MIPSO with CFBPSO approach is able to produce the most optimal economic solution than IPSO approach and Quadratic Programming. For the case of 500 kV power system is Jawa-Bali, MIPSO method with this approach is also able to provide the most optimal solution compared with the real system PT. PLN (Persero).]]>
<![CDATA[Variety of Characteristic Magnetic Material on Permanent Magnet Synchronous Generator (PMSG) ]]>
<![CDATA[Syamsyarief Baqaruzi]]>;
<![CDATA[Amrina Mustaqim]]>;
<![CDATA[Putty Yunesti]]>;
<![CDATA[Gde KM Atmajaya]]>;
<![CDATA[Ali Muhtar]]>;
<![CDATA[Sabhan Kanata]]>
<![CDATA[ IPTEK The Journal for Technology and Science Vol 33, No 2 (2022) ]]>
Publisher : <![CDATA[IPTEK, LPPM, Institut Teknologi Sepuluh Nopember ]]>
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DOI: 10.12962/j20882033.v33i2.13532
<![CDATA[Wind energy conversion system, one of the main components is a Permanent Magnet Synchronous Generator (PMSG). During the past two decades, many types of per- manent magnet generators for wind power applications have been the research topic. This study focuses primarily on designing a PMSG to create, simulate, and analyze an internal permanent magnet topology with twelve plots and eight poles. We limit with the simulation was carried out at a rotational speed of 1000rpm, and a type of permanent magnet material, Ceramic 11, SmCo 26/26, and NdFeB 48/11. The result of the analysis is that permanent magnets applied in the design of a generator impact its output power and efficiency. At 15 Ω and 60 Ω loads, SmCo 26/26 and NdFeB 48/11 are the only ones that fulfill the specified requirements in this investigation. The permanent magnet type with the most optimal characteristics is Neodymium Iron Boron 48/11 because it has a high flux density, thus causing the electrical energy generated to be greater than other types of permanent magnets. The 48/11 NdFeB permanent magnet generates the most output power, 2110.86 W when loaded with 15 Ω. The best efficiency of 89.38 percent for the PMSG 12 slot eight poles occurs when the load is 15 on the 48/11 NdFeB permanent magnet.]]>
<![CDATA[Pembangkitan Ekonomis pada Unit Pembangkit Listrik Tenaga Diesel Telaga Gorontalo Menggunakan Algoritma Genetika ]]>
<![CDATA[Sabhan Kanata]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 13, No 3 (2017) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v13i3.5451
<![CDATA[The increasing daily need towards electrical energy demands for generation companies to conduct operational cost-saving strategy including the generation fuel. One of the strategies that can be done is through economical generation optimization. The genetics algorithm of the heuristics method is known for its ability to overcome the problems characterized as non-linear, non convex, integer/ discrete, not continuous, and a system with a lot of variables. The evaluation technique employing the evolution theory has been applied to the case of IEEE 26 buses power system and diesel power generation in a unit in Telaga, Gorontalo. The result shows that the proposed method is believed to be able to minimize the generation cost better than the previous method. The method is tested by applying for its real system in Telaga, Gorontalo and it is found that the total cost at Rp 20.201.000,00 per hour with total load at 5.000 kW.]]>
<![CDATA[Kajian Ekonomis Pembangkit Hybrid Renewable Energi Menuju Desa Mandiri Energi di Kabupaten Bone-Bolango ]]>
<![CDATA[Sabhan Kanata]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 11, No 3 (2015) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v11i2.2288
<![CDATA[Energy crisis due to extensive uses of fossil fuel and environmental issues caused by unsustainable uses of energy driving the world and Indonesian government to accelerate the usage of renewable energy such as hydro, wind and solar. One of the government approaches is to implement a program called Independent Energy Village (IEV). Hybrid Optimization Model for Electric Renewables (HOMER) serves to design a micropower systems and to facilitate the comparison between some of power generation technologies. Researcher models the power system based on the physical behavior and overall cost, which are the total cost of installation and operation of the system during operation of the system. HOMER allows researcher to compare various forms of system designs technically and economically. This research was conducted in the village of Lombongo, District Suwawa, in Bone-Bolango Gorontalo. Some of the modeling results showed that the combination of micro-hydro and solar power have the most favorable economic value if operated over 25 years with a Net Present Cost (NPC) is US$ -369,087.00 and a Level Cost of Energy (LCOE) of -0.106 US$/kWh below the level energy costs of PLN at 0.116 US$/kWh in whch made this hybrid plant is very competitive. The hybrid plant has micro-hydro generating capacity of 58,9 kW with annual production of 657,384 kW, while solar power plant with a production capacity of 15,7 kW per year 20.091 kW.]]>
<![CDATA[Pembangkitan Ekonomis pada Unit Pembangkit Listrik Tenaga Diesel Telaga Gorontalo Menggunakan Algoritma Genetika ]]>
<![CDATA[Sabhan Kanata]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 13, No 3 (2017) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v13i3.5451
<![CDATA[The increasing daily need towards electrical energy demands for generation companies to conduct operational cost-saving strategy including the generation fuel. One of the strategies that can be done is through economical generation optimization. The genetics algorithm of the heuristics method is known for its ability to overcome the problems characterized as non-linear, non convex, integer/ discrete, not continuous, and a system with a lot of variables. The evaluation technique employing the evolution theory has been applied to the case of IEEE 26 buses power system and diesel power generation in a unit in Telaga, Gorontalo. The result shows that the proposed method is believed to be able to minimize the generation cost better than the previous method. The method is tested by applying for its real system in Telaga, Gorontalo and it is found that the total cost at Rp 20.201.000,00 per hour with total load at 5.000 kW.]]>
<![CDATA[Kajian Ekonomis Pembangkit Hybrid Renewable Energi Menuju Desa Mandiri Energi di Kabupaten Bone-Bolango ]]>
<![CDATA[Sabhan Kanata]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 11, No 3 (2015) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v11i2.2288
<![CDATA[Energy crisis due to extensive uses of fossil fuel and environmental issues caused by unsustainable uses of energy driving the world and Indonesian government to accelerate the usage of renewable energy such as hydro, wind and solar. One of the government approaches is to implement a program called Independent Energy Village (IEV). Hybrid Optimization Model for Electric Renewables (HOMER) serves to design a micropower systems and to facilitate the comparison between some of power generation technologies. Researcher models the power system based on the physical behavior and overall cost, which are the total cost of installation and operation of the system during operation of the system. HOMER allows researcher to compare various forms of system designs technically and economically. This research was conducted in the village of Lombongo, District Suwawa, in Bone-Bolango Gorontalo. Some of the modeling results showed that the combination of micro-hydro and solar power have the most favorable economic value if operated over 25 years with a Net Present Cost (NPC) is US$ -369,087.00 and a Level Cost of Energy (LCOE) of -0.106 US$/kWh below the level energy costs of PLN at 0.116 US$/kWh in whch made this hybrid plant is very competitive. The hybrid plant has micro-hydro generating capacity of 58,9 kW with annual production of 657,384 kW, while solar power plant with a production capacity of 15,7 kW per year 20.091 kW.]]>
<![CDATA[Smart Room Design as a Concrete Step Towards a Sustainable Smart Campus at the Institut Teknologi Sumatra ]]>
<![CDATA[Sabhan Kanata]]>;
<![CDATA[Sabar Sabar]]>;
<![CDATA[Amrina Mustaqim]]>;
<![CDATA[Gde Komang Atmajaya]]>;
<![CDATA[Muhammad Rizky Hikmatullah]]>;
<![CDATA[Muhammad Asrofi]]>;
<![CDATA[Asmar Asmar]]>
<![CDATA[ Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) Vol 10 No 1 (2023): Jurnal Ecotipe, April 2023 ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro, Universitas Bangka Belitung ]]>
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DOI: 10.33019/jurnalecotipe.v10i1.3807
<![CDATA[Institut Teknologi Sumatera (ITERA) is one of the new PTN campuses in Indonesia. As a campus that carries the smart-campus motto, ITERA will continue to create smart services, including saving electrical energy. One of the programs to support a sustainable campus is innovation in electrical energy management so that electrical energy efficiency can be maximized. The ITERA smart-room product called SMARTERA is one of the campus's tangible manifestations to control electrical equipment using Internet-based intelligent control of Things (IoT). The initial stage in this research is automatic control of the two most widely used electrical equipment in the campus environment, namely lights and air conditioning (AC)]]>
<![CDATA[Analisis dan Perbaikan Sistem Pencahayaan Buatan pada Rumah Sakit Tipe C di Kota Semarang dengan Menggunakan Simulasi Software Dialux Evo 11.1 ]]>
<![CDATA[Rachmawan, Rizky Firdaus]]>;
<![CDATA[Kanata, Sabhan]]>;
<![CDATA[Sumarno, Radiktyo Nindyo]]>
<![CDATA[ JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Vol 9, No 3 (2024): September 2024 ]]>
Publisher : <![CDATA[Universitas Al Azhar Indonesia ]]>
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DOI: 10.36722/sst.v9i3.3069
<![CDATA[The need for electrical energy is increasing due to population growth and the use of electrical equipment, including lighting systems or lamps. Lighting systems or lamps are important factors in creating a comfortable, safe and efficient atmosphere in the work environment, especially hospitals. Various methods have been used so that the lighting system or lamps can be optimized, for example by analyzing through Dialux Evo simulation. This study analyzes and improves the lighting system in a Type C hospital in Semarang using the Dialux Evo 11.1 simulation. The focus is on the nutrition or surgical polyclinic room and the operating room. The research method involves a comparison between the results of lighting strength measurements and simulations with the SNI 6197: 2011 standard. The measurement results show that the polyclinic room has an average lighting of 91.61 lux, while the simulation reaches 127 lux. For the operating room, the measurement produces 81.52 lux and the simulation 274 lux. Both of these rooms do not meet the minimum standards: 250 lux for the polyclinic room and 300 lux for the operating room. For the recommended improvements in the polyclinic room is the addition of 4 Philips LED-Tube 765 T8 AP C G light points or 5 Philips Downlight DN020B G3 D150 light points. While for the operating room, it is recommended to replace 14 points with Philips LED-Tube UO 16W865 T8 lights.Keywords - Lighting System, Strong Lighting, Dialux Evo 11.1, SNI 6197:2011]]>
