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Optimisasi Multi-objektif pada Rekonfigurasi Jaringan Distribusi Tenaga Listrik dengan Integrasi Pembangkit Terdistribusi Menggunakan Metode Sistem Kekebalan Buatan
Author(s) -
Ramadoni Syahputra,
Indah Soesanti
Publication year - 2020
Publication title -
jurnal teknik elektro/jurnal teknik elektro
Language(s) - English
Resource type - Journals
eISSN - 2549-1571
pISSN - 1411-0059
DOI - 10.15294/jte.v12i2.26353
Subject(s) - distributed generation , engineering , renewable energy , reliability engineering , computer science , electrical engineering
This study proposes a multi-objective optimization for power distribution network reconfiguration by integrating distributed generators using an artificial immune system (AIS) method. The most effective and inexpensive technique in reducing power losses in distribution networks is optimizing the network reconfiguration. On the other hand, small to medium scale renewable energy power plant applications are growing rapidly. These power plants are operated on-grid to a distribution network, known as distributed generation (DG). The presence of DG in this distribution network poses new challenges in distribution network operations. In this study, the distribution network optimization was carried out using the AIS method. In optimization, the goal to be achieved is not only one objective but should be multiple objectives. Multi-objective optimization aims to reduce power losses, improve the voltage profile, and maintain a maintained network load balance. The AIS method has the advantage of fast convergence and avoids local minima. To test the superiority of the AIS method, the distribution network optimization with and without DG integration was carried out for the 33-bus and 71-bus models of the IEEE standard distribution networks. The results show that the AIS method can produce better system operating conditions than before the optimization. The parameters for the success of the optimization are minimal active power losses, suitable voltage profiles, and maintained load balance. This optimization has successfully increased the efficiency of the distribution network by an average of 0.61%.

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