Multi-Objective Optimal DG Placement Approach Using Analytical Hierarchy Process

Distributed generation (DG) has been increasingly integrated into distribution systems in the last decade. The selection of the optimal location and capacity of these DGs is an important issue. This selection is based on minimizing losses, reducing emissions, reducing voltage deviation, and much mor...

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Vydáno v:Electric power components and systems Ročník 51; číslo 15; s. 1648 - 1663
Hlavní autoři: Mewafy, Abdelrahman A., Kaddah, Sahar S., Eladawy, Mohamed
Médium: Journal Article
Jazyk:angličtina
Vydáno: Philadelphia Taylor & Francis 14.09.2023
Taylor & Francis Ltd
Témata:
Algorithms
Analytic hierarchy process
capacity factor
Deviation
Distributed generation
Electric potential
Hierarchies
Linear programming
Mathematical analysis
Multiple objective analysis
Optimization
power factor
tap changer
Voltage
ISSN:1532-5008, 1532-5016
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Shrnutí:Distributed generation (DG) has been increasingly integrated into distribution systems in the last decade. The selection of the optimal location and capacity of these DGs is an important issue. This selection is based on minimizing losses, reducing emissions, reducing voltage deviation, and much more. This paper proposes a new optimization approach with a multi-objective function for maximizing DG capacities and minimizing both system losses and voltage deviation, which are subject to system constraints. The weight of each attribute of the multi-objective function is estimated using the analytical hierarchical process (AHP). The optimal DG size is calculated for all possible buses, and hence, the optimal bus can be located. Moreover, an algorithm is introduced to decrease the number of iterations when integrating more than one DG. The proposed method is an iterative linear programming method based on the familiar Newton-Raphson sensitivity matrix. The proposed approach has been tested on 69 and IEEE 33 bus systems. The simulation results are compared with previous literature results.
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ISSN:1532-5008
1532-5016
DOI:10.1080/15325008.2023.2202651