A hybrid multi-objective Evolutionary Programming-Firefly Algorithm for different type of Distributed Generation in distribution system

被引：0

作者：

Husni, Noor Najwa Husnaini Mohammad ^{[1
]}

Rahim, Siti Rafidah Abdul ^{[1
,2
]}

Adzman, Mohd Rafi ^{[1
]}

Hussain, Muhamad Hatta ^{[1
]}

Musirin, Ismail ^{[3
]}

Azmi, Syahrul Ashikin ^{[1
]}

机构：

[1] Univ Malaysia Perlis, Fac Elect Engn Technol, Arau 02600, Perlis, Malaysia

[2] Univ Malaysia Perlis, CERE, Arau 02600, Perlis, Malaysia

[3] Univ Teknol MARA UiTM, Coll Engn, Sch Elect Engn, Shah Alam 40450, Selangor, Malaysia

来源：

ENERGY REPORTS | 2022年 / 8卷

关键词：

Distributed Generation; Multi-objective optimization; Loss minimization; Evolutionary Programming; ALLOCATION; SIZE;

D O I：

10.1016/j.egyr.2022.10.192

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

With the rise in electricity demand, various additional sources of generation, known as Distributed Generation (DG), have been introduced to boost the performance of power systems. A hybrid multi-objective Evolutionary Programming-Firefly Algorithm (MOEPFA) technique is presented in this study for solving multi-objective power system problems which are minimizing total active and reactive power losses and improving voltage profile while considering the cost of energy losses. This MOEPFA is developed by embedding Firefly Algorithm (FA) features into the conventional EP method. The analysis in this study considered DG with 4 different scenarios. Scenario 1 is the base case or without DG, scenario 2 is for DG with injected active power, scenario 3 is for DG injected with reactive power only and scenario 4 is for DG injected with both active and reactive power. The IEEE 69-bus test system is applied to validate the suggested technique. (C) 2022 The Author(s). Published by Elsevier Ltd.

引用

页码：169 / 174

页数：6

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