Choiri, Miftah Ahmad (2019) Optimasi Respon Beban Berbasis Insentif untuk Beban Rumah Tangga Menggunakan Algoritma Symbiotic Organism Search. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Pada program Demand Response (DR) yang dilakukan pada penelitian tugas akhir ini bertujuan untuk mengendalikan pola konsumsi daya listrik pada sektor rumah tangga menggunakan algortima symbiotic organism search. Melalui program DR berbasis insentif ini pengguna rumah tangga dapat peralatan listrik dapat dikontrol sehingga beban puncak akan berkurang, stabilitas dan efisiensi jaringan akan meningkat. Peralatan elektronik kategori non esensial di alihkan pada jam-jam tidak sibuk agar didapatkan tagihan listrik yang lebih murah. Agar masyarakat bersedia peralatan rumah tangganya dikontrol secara terpusat, maka penyedia energi memberikan program insentif berupa pengurangan harga pada jam-jam beban rendah. Salah satu algoritma Symbiotic Organism Search (SOS) dapat digunakan sebagai metode optimasi program demand response sehingga didapatkan penjadwalan harga dan jadwalan program insentif yang optimal bagi pelanggan. Dalam tugas akhir ini, SOS akan dibandingkan dengan algoritma Genetic Algorithm (GA) untuk metode pembanding untuk mendapatkan hasil yang lebih optimal dalam melakukan penjadwalan beban rumah tangga. Sedangkan teknologi Home Energy Management System (HEMS) digunakan untuk memonitor dan mengontrol peralatan secara real time dan terpusat. Hasil simulasi menggunakan program GA dapat berkurang hingga 10.9%. Sedangkan hasil analisa menggunakan program SOS dapat berkurang hingga 17.5%. Hasil dari simulasi program DR akan diterapkan pada salah satu fitur aplikasi manajemen energi skala rumah tangga.
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Demand Response (DR) program carried out in this final project research aims to control the pattern of electric power consumption in the household sector using the symbiotic organism search algorithm. Through this incentive-based DR program household users can control electrical equipment so that peak loads will be reduced, network stability and efficiency will increase. Non-essential electronic equipment is diverted at busy hours to get cheaper electricity bills. In order for the community to be willing to control their household equipment centrally, the energy provider provides an incentive program in the form of price reductions at low load hours. One of the Symbiotic Organism Search (SOS) algorithms can be used as a method of optimizing the demand response program so that price scheduling and optimal incentive program scheduling are obtained for customers. In this final project, SOS will be compared with the Genetic Algorithm (GA) algorithm for comparison methods to get more optimal results in scheduling household expenses. While Home Energy Management System (HEMS) technology is used to monitor and control equipment in real time and centrally. The simulation results using the GA program can be reduced to 10.9%. While the results of the analysis using the SOS program can be reduced by up to 17.5%. The results of the DR program simulation will be applied to one of the features of a household scale energy management application.
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | RSE 621.319 Cho o-1 |
| Uncontrolled Keywords: | Demand Response, Optimasi, Symbiotic Organism Search, Penjadwalan Beban, Load Schedulling |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3030 Electric power distribution systems T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5103.8 Switching systems |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis |
| Depositing User: | Miftah Ahmad Choiri |
| Date Deposited: | 11 Jan 2023 07:33 |
| Last Modified: | 11 Jan 2023 07:33 |
| URI: | http://repository.its.ac.id/id/eprint/63508 |
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