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All Journal International Journal of Electrical and Computer Engineering Jurnal Teknik ITS Jurnal Sains dan Teknologi JUTI: Jurnal Ilmiah Teknologi Informasi Indonesian Journal of Electrical Engineering and Computer Science Sewagati Serambi Engineering
Rony Seto Wibowo
Institut Teknologi 10 Nopember Surabaya
Arts Humanities Computer Science & IT Dentistry Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Public Health Social Sciences Other

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Mixed-Integer Linear Programming for Optimal Operation of Integrated Electricity and Natural Gas System Considering Take or Pay Agreements Nooraini, Ervina; Prakasa, Mohamad Almas; Djalal, Muhammad Ruswandi; Wibowo, Rony Seto; Robandi, Imam
JUTI: Jurnal Ilmiah Teknologi Informasi Vol.23, No.2, July 2025
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v23i2.a1265

Abstract

This paper is proposed to demonstrate the implementation of Mixed-Integer Linear Programming (MILP) for solving the optimal operation of the Integrated Electricity and Natural Gas System (IENGS). The MILP is used to realize an economical and reliable power electricity system based on Dynamic Optimal Power and Gas Flow (DOPGF) considering Take or Pay (TOP) agreements for natural gas. This method is simulated on the integrated 6-bus electricity and 6-node natural gas systems. By using MILP, the best costs for optimal operation of IENGS are obtained in three scenarios. The superiority of the MILP is validated by suppressing the increasing best cost for optimal operation to be below 10%. In the first case, the best cost is $735,405.37 without the TOP agreement. In the second scenario, the best cost ranges from $748,399.30 to $760,320.57 with the TOP agreement implemented in one-by-one generators, which is 1.77% to 3.39% higher than the first scenario. In the third case, the best cost is $791,833.04 with the TOP agreement in all of the generators, which is 7.67% higher than the first scenario. In addition, the MILP can perform the DOPGF for IENGS without violating the problem constraints regarding the load demand fulfillment and power system limitations in both coal-fired and gas-fired generators.                                                        
Unit Commitment Scenarios for Distributed Energy Resources Using Binary Particle Swarm Optimization Aryani, Ni Ketut; Wibowo, Rony Seto; Rosida, Yasfi Nur; Santoso, Dimas Budi; Kurniawan, Muhammad
JST (Jurnal Sains dan Teknologi) Vol. 14 No. 1 (2025): April
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jstundiksha.v14i1.92194

Abstract

This study examines the integration of wind power plants and the application of Emergency Demand Response (EDRP) in the Unit Commitment (UC) problem in the electric power system, by utilizing the Binary Particle Swarm Optimization (BPSO) method. The UC problem focuses on optimal scheduling of generating units to meet load requirements with minimum operating costs. However, the intermittent characteristics of wind energy cause significant uncertainty in the scheduling process. Therefore, EDRP is applied as an adaptive strategy to change the load demand pattern dynamically, so as to improve system reliability and reduce dependence on conventional generators. This study aims to develop and implement an optimization method usingBinary Particle Swarm Optimization (BPSO) Algorithm in determining unit commitment scenarioin the electric power system involvingDistributed Energy Resources (DERs), in order to improve operational efficiency and reliability of the power system. This type of research issimulation-based experimental quantitative research.  Population: Electric power systems with DERs that have various load profiles and generating unit characteristics.Sample: A standard distribution system or test case system (e.g. IEEE 30-bus or hypothetical system) modified to include DERs such as PV (photovoltaic), microturbines, and energy storage (batteries). The data collection method is done by software simulation (e.g. MATLAB or Python) to generate load data, DER capacity, and system parameters.The Data Analysis Method Used isComputational Analysis. The simulation results show that the implementation of the fourth scenario results in lower generation costs and improves the operational efficiency of the system, indicating the potential for integrating demand strategies and renewable energy sources in modern power systems. The implications of this study can be used as a reference forshort term operational planning in spower system with high DER penetration.
Optimasi Dynamic Economic Dispatch pada Sistem Tenaga Hibrida Berbasis Photovoltaic Menggunakan Algoritma Turbulent Flow of Water-Based Optimization Moh. Erdianto Triputradi; Aryani , Ni Ketut; Wibowo, Rony Seto; Oktaviani , Berliandra; Najmy, Achsan
Jurnal Serambi Engineering Vol. 10 No. 3 (2025): Juli 2025
Publisher : Faculty of Engineering, Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The Increasing of living population, which impacts the increasing need for loads, is a challenge for plants in providing the need for electrical loads. The depletion of supplies and the high price of fossils constrain the cost of generating thermal plants. Therefore, a combination of alternative Photovoltaic (PV) energy power generation is needed to reduce the cost of generating thermal plants. Dynamic Economic Dispatch (DED) is one of the optimization techniques in power plants to determine the combination of output power in each generator in each period. This paper proposes an optimization technique to solve the DED problem in a hybrid PV base power system using Turbulent Flow Water-Based Optimization (TFWO) Method. This paper will compare the results and analysis of total generation costs before and after using PV plants. The total generation cost shows that the generation cost using PV can reduce the generation cost by $302,799.67.
Co-Authors Adi Soeprijanto Adyatmoko Wirananto Agil Dwijatmoko Rahmatullah Andi Fitriati Ardyan Bhakti Setyarso Ardyono Priyadi Arianto, Marcel Nicky Aryani , Ni Ketut Aryani, Ni Ketut Badru Tamam Arozaq Christina Tio Trisnasari Daniar Fahmi, Daniar Daya Juang Mahaputra Dedet Candra Riawan Dedet Chandra Riawan Dhimas Oktavian Andryana Dimas Fajar Uman Putra Fakhruddin Wirakusuma Feby Agung Pamuji Ferdinand Rico Firaldi Galih Budi Virgiansyah Giorgio Rendra Gumelar Gokma Eunike Napitu Hari Agus Sujono Heri Suryoatmojo Imam Robandi Januar Adi Perdana Kemas Robby Firmansyah Kresna Bayu Ar-razi Arifin Lutfi, Aulia Amjad Mikhael Vidi Santoso Mochamad Ashari Mochamad Luthfiyansah Moh Fasich Moh. Erdianto Triputradi Monica Amelia Oktaviani Muhammad Arindra Muhammad Kurniawan Muhammad Ruswandi Djalal Muhira Dzar Faraby Musthofa, Arif Najmy, Achsan Ni Ketut Aryani Nooraini, Ervina Nugroho Wicaksono Oktaviani , Berliandra Ontoseno Penangsang Pius Aditya Kurnia Ray Prakasa, Mohamad Almas Prasetiyono Hari Mukti Prasetyo, Mario Dwi Pujiantara, Margo Putra, Dimas Fajar Uman R Wahyudi Rachmad Nur Priyanto Rahmat Riyadi Ridho Syahrial Ibrahim Riny Sulistyowati Rizka Winda Novialifiah Rizky Ramadyan Widiarto Ronny Mardiyanto, Ronny Rosida, Yasfi Nur Saifi Sabiq Sampulur Kerta Sugih Harta Santoso, Dimas Budi Sjamsjul Anam Surya Mahendra Vicky Pria Permata Vita Lystianingrum Willy Prasetyadi Yauri Mahaputra Zico Musiano Sihombing