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All Journal Journal of Engineering and Technological Sciences Jurnal Nasional Teknik Elektro dan Teknologi Informasi
FX Nugroho Soelami
Institut Teknologi Bandung
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Data Driven Building Electricity Consumption Model Using Support Vector Regression FX Nugroho Soelami; Putu Handre Kertha Utama; Irsyad Nashirul Haq; Justin Pradipta; Edi Leksono; Meditya Wasesa
Journal of Engineering and Technological Sciences Vol. 53 No. 3 (2021)
Publisher : Institute for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.eng.technol.sci.2021.53.3.13

Abstract

Every building has certain electricity consumption patterns that depend on its usage. Building electricity budget planning requires a consumption forecast to determine the baseline electricity load and to support energy management decisions. In this study, an algorithm to model building electricity consumption was developed. The algorithm is based on the support vector regression (SVR) method. Data of electricity consumption from the past five years from a selected building object in ITB campus were used. The dataset unexpectedly exhibited a large number of anomalous points. Therefore, a tolerance limit of hourly average energy consumption was defined to obtain good quality training data. Various tolerance limits were investigated, that is 15% (Type 1), 30% (Type 2), and 0% (Type 0). The optimal model was selected based on the criteria of mean absolute percentage error (MAPE) < 20% and root mean square error (RMSE) < 10 kWh. Type 1 data was selected based on its performance compared to the other two. In a real implementation, the model yielded a MAPE value of 14.79% and an RMSE value of 7.48 kWh when predicting weekly electricity consumption. Therefore, the Type 1 data-based model could satisfactorily forecast building electricity consumption.
Pemodelan Manajemen Energi Microgrid pada Sistem Bangunan Cerdas FX Nugroho Soelami; Edi Leksono; Irsyad Nashirul Haq; Justin Pradipta; Putu Handre Kertha Utama; Aretha Fieradiella Pahrevi; Faizatuzzahrah Rahmaniah; Meditya Wasesa
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 4: November 2020
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1528.314 KB) | DOI: 10.22146/jnteti.v9i4.488

Abstract

From the electricity system point of view, smart buildings can be seen as an integration of a microgrid electricity network that connects solar PV, storage system, and building load distribution. The operation condition of the microgrid needs to be evaluated and optimized to obtain efficient and reliable performance. This contribution presents an energy management modeling for the microgrid optimization process in a smart building system. The energy sources connected to the microgrid are solar PV, battery storage system, and the PLN (utility) grid. Combinations of load scenarios are evaluated, which consists of building a lighting system, water pump, dan HVAC system. The optimization goal is to find the optimal estimation of Self Consumption (SC) and Self Sufficiency (SS) values. A simulation result before the optimization shows that the system is operating with SC of 63.2% and SS of 96.32%. After the optimization, the values become SC = 84.68% and SS = 83.27%. Therefore, the amount of energy sourced from the Solar PV system is increased and the microgrid is working more optimally.
Co-Authors Aretha Fieradiella Pahrevi Edi Leksono Faizatuzzahrah Rahmaniah Irsyad Nashirul Haq Justin Pradipta Meditya Wasesa Putu Handre Kertha Utama