LAPSE:2023.1417
Published Article

LAPSE:2023.1417
Optimal DGs Siting and Sizing Considering Hybrid Static and Dynamic Loads, and Overloading Conditions
February 21, 2023
Abstract
There is no doubt that Distributed Generation (DG) has proved to be an effective solution for satisfying the growing demand within a fleeting period and improving system performance, voltage profile, and power quality, especially on the end user’s side. Thus, in modern distribution systems, DG is preferable to be installed in the vicinity of the end user to enhance the system performance, reduce power losses, and improve grid voltage. In this paper, hybrid static and dynamic load types (100% static, 50% static and 50% dynamic, and 100% dynamic loads) at different overloading conditions, for the standard IEEE 33-bus system, are considered, and power system performance is recorded. Moreover, to improve the power system performance, Distributed Generations (DGs) are optimally sized and allocated in the IEEE 33-bus system using the Harmony Search Algorithm (HSA), and two analytical approaches, respectively, and compared to other reported optimization methods. The results show that, at 100% loading, the minimum bus voltage for the proposed method reached 0.97 pu, compared to 0.94 pu for the Particle Swarm Optimization (PSO) algorithm and 0.9574 pu for the Improved Analytical (IA) method. From the results obtained in this paper, it can be concluded that the proposed technique improved the performance of the studied power system, compared to other reported techniques, by enhancing the voltage profile and minimizing the power losses.
There is no doubt that Distributed Generation (DG) has proved to be an effective solution for satisfying the growing demand within a fleeting period and improving system performance, voltage profile, and power quality, especially on the end user’s side. Thus, in modern distribution systems, DG is preferable to be installed in the vicinity of the end user to enhance the system performance, reduce power losses, and improve grid voltage. In this paper, hybrid static and dynamic load types (100% static, 50% static and 50% dynamic, and 100% dynamic loads) at different overloading conditions, for the standard IEEE 33-bus system, are considered, and power system performance is recorded. Moreover, to improve the power system performance, Distributed Generations (DGs) are optimally sized and allocated in the IEEE 33-bus system using the Harmony Search Algorithm (HSA), and two analytical approaches, respectively, and compared to other reported optimization methods. The results show that, at 100% loading, the minimum bus voltage for the proposed method reached 0.97 pu, compared to 0.94 pu for the Particle Swarm Optimization (PSO) algorithm and 0.9574 pu for the Improved Analytical (IA) method. From the results obtained in this paper, it can be concluded that the proposed technique improved the performance of the studied power system, compared to other reported techniques, by enhancing the voltage profile and minimizing the power losses.
Record ID
Keywords
DGs, dynamic loads, HSA optimization, hybrid loads, static loads
Subject
Suggested Citation
Sameh MA, Aloukili AA, El-Sharkawy MA, Attia MA, Badr AO. Optimal DGs Siting and Sizing Considering Hybrid Static and Dynamic Loads, and Overloading Conditions. (2023). LAPSE:2023.1417
Author Affiliations
Sameh MA: Electrical Engineering Department, Faculty of Engineering, Future University in Egypt, Cairo 11835, Egypt [ORCID]
Aloukili AA: Department of Electrical Power and Machines, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt
El-Sharkawy MA: Department of Electrical Power and Machines, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt
Attia MA: Department of Electrical Power and Machines, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt [ORCID]
Badr AO: Department of Electrical Power and Machines, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt [ORCID]
Aloukili AA: Department of Electrical Power and Machines, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt
El-Sharkawy MA: Department of Electrical Power and Machines, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt
Attia MA: Department of Electrical Power and Machines, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt [ORCID]
Badr AO: Department of Electrical Power and Machines, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt [ORCID]
Journal Name
Processes
Volume
10
Issue
12
First Page
2713
Year
2022
Publication Date
2022-12-15
ISSN
2227-9717
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Original Submission
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PII: pr10122713, Publication Type: Journal Article
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LAPSE:2023.1417
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https://doi.org/10.3390/pr10122713
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Feb 21, 2023
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