Genetic single objective optimisation for sizing and allocation of renewable DG systems

被引：62

作者：

Hassan A.A. ^{[1
]}

Fahmy F.H. ^{[1
]}

Nafeh A.E.-S.A. ^{[1
]}

Abu-elmagd M.A. ^{[2
]}

机构：

[1] Electronics Research Institute, Giza

[2] Faculty of Engineering, Cairo University, Giza

来源：

International Journal of Sustainable Energy | 2017年 / 36卷 / 06期

关键词：

distributed generation; genetic algorithms; optimisation; renewable energy; single objective; sizing;

D O I：

10.1080/14786451.2015.1053393

中图分类号：

学科分类号：

摘要：

The optimal design of renewable-based distributed generations (DGs) is a challenging issue in order to maximise their benefits and to overcome power quality problems. Therefore, this paper proposes a methodology for optimal allocation and sizing of renewable DG units to minimise total power losses over radial distribution systems. The planning problem is formulated as a single objective nonlinear mixed integer-constrained optimisation problem and is solved by using the augmented Lagrangian genetic algorithm (ALGA) by combining the objective function and the nonlinear constraints. In that case, the ALGA solves a sequence of sub-problems where the objective function penalises the constraints violation in order to obtain the best solution. The proposed technique is applied to IEEE radial test systems including 33-bus, 69-bus and 119-bus and is implemented with different scenarios including all possible combinations and various types of renewable DG units to prove the effectiveness of the proposed methodology. © 2015 Taylor & Francis.

引用

页码：545 / 562

页数：17

共 18 条

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