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All Journal International Journal of Engineering Science and Technology Development (IJEST) Mechatronics, Electrical Power, and Vehicular Technology Jurnal Tapis : Jurnal Teropong Aspirasi Politik Islam International Conference on Engineering and Technology Development (ICETD) Jurnal Agroteknos Jurnal Intelektualita: Keislaman, Sosial, dan Sains E-Dimas: Jurnal Pengabdian kepada Masyarakat ARISTO Machine : Jurnal Teknik Mesin Al Mi’yar: Jurnal Ilmiah Pembelajaran Bahasa Arab dan Kebahasaaraban JURNAL KAJIAN TEKNIK MESIN Societas : Jurnal Ilmu Administrasi dan Sosial Teknobiz : Jurnal Ilmiah Program Studi Magister Teknik Mesin Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi International Journal of Robotics and Control Systems Jurnal Gagasan Hukum Jurnal Ilmiah Teknik (JUIT) International Journal Science and Technology (IJST) International Journal of Ethno-Sciences and Education Research Jurnal Teknik Mesin Sinergi Indonesian Journal of Physics (IJP) e-Jurnal Inovasi Pembelajaran Sekolah Dasar KOLONI Jurnal Pengabdian Masyarakat Bangsa AME (Aplikasi Mekanika dan Energi) : Jurnal Ilmiah Teknik Mesin Ihsanika : Jurnal Pendidikan Agama Islam JOSEE : Journal of College Student's Intellectual Journal of Applied Science and Advanced Engineering Almikanika e-Jurnal Inovasi Pembelajaran Sekolah Dasar
Rudi Irawan
Universitas Gunadarma
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Journal : International Journal of Robotics and Control Systems

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Utilize the Prediction Results from the Neural Network Gate Recurrent Unit (GRU) Model to Optimize Reactive Power Usage in High-Rise Buildings Rofii, Ahmad; Soerowirdjo, Busono; Irawan, Rudi; Caesarendra, Wahyu
International Journal of Robotics and Control Systems Vol 4, No 2 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i2.1351

Abstract

The growing urbanization and the construction sector, efficient use of electric energy becomes important, especially the use of reactive power. If excessive use causes decreased efficiency and increased operational costs. Decreased efficiency contributes to increasing exhaust gas volumes and greenhouse emissions. Efficient energy can achieved if planning and predictions are correct. This research applies the GRU neural network method with grid search initialization as a novelty predictive model for energy-use high-rise buildings in form fast training without multiple iterations because optimal hyperparameters are obtained. Experimental show the MAE and RMSE performance metrics of the GRU better than LSTM in predicting energy consumption data peak loads, off-peak loads and reactive power. The accuracy of GRU predictions can optimize the use of energy to contribute to saving the environment from exhaust emissions and the greenhouse effect in urban systems. Experimental results demonstrate the superiority of GRU over LSTM, proof of the much lower MAE and RMSE values. This metric shows the accuracy of GRU in generalizing data both during peak and off-peak hours, as well as in reactive power usage. By Utilizing GRU's capabilities, building management can manage reactive power usage effectively, allocate reactive power resources appropriately, and mitigate peak load times and the power factor within the threshold, thus avoiding additional costs and electrical system efficiency and contributing to reducing the carbon footprint and gas emissions greenhouse. Research on GRU is widely open in the high-rise building sector, including its integration with sensors to automatically control energy use.
Co-Authors -, Joko Abdul Rahman Afrizal Riyantono Afzeri Tamsir Afzeri Tamsir Afzeri Tamsir Afzeri Tamsir Afzeri Tamsir Afzeri Tamsir AGUNG PRATAMA, RIZKY Agus Pahrudin Ahmad Firdaus A. Zaidi Ahmad Firdaus A. Zaidi Ahmad Firdaus A. Zaidi Ahmad Rofii Ahmad Suhaedi Al - Farid, Ahlan Husaini Alfasha, Muhammad Zidan Alfitri Alfitri Alhuda, M Raffi Andries Lionardo, Andries Anggil Viyantini Kuswanto Anindya, R.A.Sekar Ciptaning Apriansa, Farul Ardiansyah, Irwan Ari Legowo Ari Legowo Ariandi, Rian Dwi Arief Goeritno Arwin Arwin Azama, Irham Muhammad Baharudin Budiman Busono Soerowirdjo Chayati, Nurul Cokorda Prapti Mahandari Dedy Haryanto Dena Hendriana Desilia Purnama Dewi Dian Wulandari Eko Hadi Purwanto Fadillah, Afan Firmansyah, Riyan Harjoyo Harjoyo Husni Thamrin Ida Ayu Putu Sri Widnyani Jeremi Badar, Johanes K, G.B Heru Kasutjianingati Kasutjianingati, Kasutjianingati Khairunnisa Khairunnisa Ksatrio Susanto Kuncoro, Heru Luluk Dianarini Mansurdin, Mansurdin Mohamad Yamin Muamar Al Qadri Muhamad Lutfi Mulya Juarsa Nor Hilmi Mohamad Nor Hilmi Mohamad Nur‘ainingsih, Dyah Oktaviandi, Ryan Putri Aulia Putri, Sherly Amanda Raden Mohamad Herdian Bhakti Rasyid Habibi, Said Ratika Dewi Ricky Therisno Ridwan Ridwan Ridwan Ridwan, Ridwan Ritzkal, Ritzkal Riza Muhida Roy Waluyo Rudianto, Haris Rulhendri Rulhendri Siti Zulaiha Subha, Habibah Aurora Suharto Suharto Sukatin, Sukatin Syaiful Syaiful Sya’bani, Rafi Fajar Syihabuddin Syihabuddin Tri Wijaya Putra, Doni Utami, Priska Restu Wahyu Caesarendra Wicaksono, Nugroho Adi Widyastuti Widyastuti Winda Astuti Winda Astuti Yayan M.A Nurbayan Zulfi Diane Zaini