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All Journal Jurnal Rekayasa Mesin INTEK: Jurnal Penelitian Jurnal Teknik Elektro dan Komputasi (ELKOM) IJITEE (International Journal of Information Technology and Electrical Engineering) Jurnal Rekayasa Elektro Sriwijaya International Journal of Research in Vocational Studies (IJRVOCAS) Ramatekno Journal of Electronics Technology Exploration (JOeTEx)
Ningtias, Dieta Wahyu Asry
Universitas Sains Dan Teknologi Komputer, Indonesia
Aerospace Engineering Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Techno-Economic Optimization of Rooftop Photovoltaic Systems Using Genetic Algorithm for Government Building Kemenko 3 in Nusantara Capital City Sapruddin, Ayu Fitriah; Muhammad Yusuf Yunus; Dieta Wahyu Asry Ningtias; Nurriza Kholifatulloh Hasanah; Diyono, Diyono
INTEK: Jurnal Penelitian Vol 13 No 1 (2026): April 2026
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/intek.v13i1.6351

Abstract

Rooftop photovoltaic (PV) systems installed on government buildings play an important role in supporting the energy transition and reducing carbon emissions, particularly in rapidly developing urban areas. However, conventional rooftop PV system designs are typically based on deterministic simulations that focus primarily on maximizing energy production, while technical and economic performance indicators are rarely optimized simultaneously. As a result, many installations may experience suboptimal system sizing, lower self-consumption, and higher energy costs. This study proposes a techno-economic optimization framework for an on-grid rooftop PV system installed at Government Building Kemenko 3 in the Nusantara Capital City (IKN), Indonesia. The proposed approach integrates PVsyst-based baseline simulation with a Genetic Algorithm (GA) implemented in Python to optimize key design variables, including module tilt angle, azimuth angle, and system capacity. The optimization simultaneously considers multiple performance indicators, namely annual energy production, self-consumption rate (SCR), self-sufficiency rate (SSR), and the Levelized Cost of Energy (LCOE). The optimization results indicate that the optimal configuration is achieved with a tilt angle of 1.09° and an azimuth angle of 8.58°, resulting in an installed capacity of 79.80 kW and an annual energy production of 164,114.63 kWh. The optimized system achieves an LCOE of 0.0590 USD/kWh, with an SCR of 72.76% and an SSR of 51.85%, demonstrating efficient utilization of locally generated solar energy. These results confirm that GA-based optimization can significantly improve both the technical performance and economic competitiveness of rooftop PV systems, providing a practical framework for optimizing PV deployment in government buildings in tropical regions.
Co-Authors Al Rasyid , Zya Jamaluddin Ali Nur Fathoni Asmoro, Purwandito Tulus Ayu Janitra, Atikah Bayu, Tatar Dani Usman Diyono, Diyono Ermanu Azizul Hakim Fransisco Danang Wijaya Hadisantoso, Feri Siswoyo Handayani, Sita Tri Haneef Nouval Alannibras Humaidi Hasanah, Nurriza Kholifatulloh Heri Yudiono Humaidi, Haneef Nouval Alannibras Lesnanto Multa Putranto Marliyati Muhammad Yusuf Yunus Ningrum, Siti Mardiyanti Nur Kasan, Nur Prasetya, Valendry Naufal Pratama, Aziz Yulianto Rizal Rahma Sandi Sapruddin, Ayu Fitriah Setiyawan, Trio Syafrudi Syafrudi Syukur Alfauzi, Abdul Timotius Anggit Kristiawan Tono Putri, Farika Widhaninggar, Diana Fika Widodo Yusuf Dewantoro Herlambang