Open AccessLoadability Investigation of Power System Network Integrated Distributed Generation Including Multi-Sector Consumers
Author(s) -
. Yusran,
Yuli Asmi Rahman,
Prisma Megantoro
Publication year - 2020
Publication title -
xi'nan jiaotong daxue xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.308
H-Index - 21
ISSN - 0258-2724
DOI - 10.35741/issn.0258-2724.55.4.18
Subject(s) - firefly algorithm , electric power system , voltage , limit (mathematics) , distributed generation , power (physics) , stability (learning theory) , electricity generation , computer science , automotive engineering , mathematical optimization , control theory (sociology) , reliability engineering , engineering , mathematics , electrical engineering , renewable energy , mathematical analysis , physics , quantum mechanics , particle swarm optimization , machine learning , control (management) , artificial intelligence
This article describes the hybrid approach of the Firefly Algorithm and power-voltage curve method in optimal placement of Distributed Generation while considering the actual load model. The actual load model is represented by six models. The six load models are a composite of industrial, residential, and commercial loads with dissimilar percentages. The Institute of Electrical and Electronics Engineers 30 Bus is selected as the testing object for the proposed method. The optimal Distributed Generation placement process was performed using the Firefly Algorithm, while evaluation of optimal Distributed Generation on the loading and stability index is continued using the power-voltage curve method. The results show that commercial loads contribute to high power loss values. The optimal Distributed Generation integration results in an increase the stability index from 53.83% at initial conditions to 90.84% at maximum load level when increasing the maximum loading limit to 95%.