Tjahjono, Anang (2017) Self Adaptable Coordination Overcurrent Digital Protection Relay For Power Distribution Network. Doctoral thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Dengan terintegrasinya berbagai jenis sumber energi listrik dengan menggunakan
distributed generation (DG) dalam satu sistem jaringan distribusi akan
menimbulkan perubahan seting pada tiap perangkat rele, dimana mengikuti
perubahan status dari DG yang mempunyai sifat intermitten. Pada penelitian ini
telah dilakukan terobosan inovasi baru berupa pengembangan rele digital yang
mempunyai fitur user-defined characteristic curve dengan cara memodelkan kurva
karakteristik dengan menerapkan ujicoba algoritma polynomial Lagrange hingga
algoritma artificial intelligence. Keberhasilan dalam memodelkan kurva
karakteristik rele digital membawa dampak yang sangat luas, antara lain
kemampuan perencanaan kurva non-standar, multi curve dalam satu rele serta
kemampuan pemilihan kurva yang bersifat adaptif mengikuti kondisi atau status
dari DG yang terdapat dalam jaringan distribusi. Inovasi terobosan baru selain
pemodelan kurva adalah optimisasi parameter dari kurva karakteristik rele yakni
plug seting (PS) dan time multiplier seting (TMS), dua parameter penting tersebut
harus dicari nilai optimumnya agar dihasilkan koordinasi antar rele dalam satu
jaringan distribusi yang maksimal dimana perangkat sumber energi listrik dan
beban terlindungi dengan baik dengan bantuan algoritma optimisasi firefly yang
dikembangkan, yakni modified firefly algorithm (MFA) serta adaptive modified
firefly algorithm (AMFA). Ketercapaian pemodelan kurva karakteristik userdefined dengan menggunakan artificial neural network (ANN) mencapai nilai
MSE=0,00010, sedang nilai optimisasi yang tertinggi mencapai 42,22% dengan
menggunakan AMFA. Dengan keberhasilan ini maka kebutuhan akan adaptive
digital overcurrent relay yang mampu beroperasi pada active distribution network
telah terjawab dan siap untuk dikembangkan pada tataran implementasi.
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With the integration of various types of electrical energy sources by using distributed generation (DG) in a distribution network system will cause changes in settings in each relay device, which follows the change in status of DG that has intermittent properties. In this research, innovation of digital relay has been developed with user-defined curve capability by modeling characteristic curves using Lagrange polynomial interpolation algorithm and artificial intelligence algorithm. Success in modeling digital relay characteristic curves has a wide impact, such as the ability of non-standard curve planning, multi curve in one relay and adaptive curve selection capability following the condition or status of DG in the distribution network. New breakthrough innovations besides curve modeling are parameter optimization of relay characteristic curves ie plug setting (PS) and time multiplier setting (TMS), two important parameters must be obtained optimum value to generate coordination between relays in a distribution network as much as possible, where the device The source of electrical energy and load is well protected, with the help of modification firefly optimization algorithm, called modified firefly algorithm (MFA) and adaptive modified firefly algorithm (AMFA). The user-defined curve modeling results using artificial neural network (ANN) get MSE 0.00010, while the highest optimization value reached 42.22% using AMFA. With the success of this research, the need for adaptive digital overcurrent relay capable of operating on active distribution network has been answered and ready to be developed at the implementation level.
Item Type: | Thesis (Doctoral) |
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Uncontrolled Keywords: | distributed generation, intermitten, digital relay, user-defined characteristic curve, artificial intelligence algorithm, LaGrange interpolation, ANN, ANFIS, MFA, AMFA, adaptive digital protection relay, active distribution network. |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK201 Electric Power Transmission |
Divisions: | Faculty of Industrial Technology > Electrical Engineering > 20001-(S3) PhD Thesis |
Depositing User: | Anang Tjahjono |
Date Deposited: | 07 Nov 2017 02:59 |
Last Modified: | 05 Mar 2019 03:32 |
URI: | http://repository.its.ac.id/id/eprint/48567 |
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