LAPSE:2023.6752
Published Article

LAPSE:2023.6752
Allocation of Renewable Energy Resources in Distribution Systems While considering the Uncertainty of Wind and Solar Resources via the Multi-Objective Salp Swarm Algorithm
February 24, 2023
Abstract
Given the importance of renewable energy sources in distribution systems, this article addresses the problem of locating and determining the capacity of these sources, namely, wind turbines and solar panels. To solve this optimization problem, a new algorithm based on the behavior of salp is used. The objective functions include reducing losses, improving voltage profiles, and reducing the costs of renewable energy sources. In this method, the allocation of renewable resources is considered for different load models in distribution systems and different load levels using smart meters. Due to the fact that these objective functions are multi-objective, the fuzzy decision-making method is used to select the optimal solution from the set of Pareto solutions. The considered objective functions lead to loss reduction, voltage profile improvement, and RES cost reduction (A allocating RES resources optimally without resource limitations; B: allocating RES resources optimally with resource limitations). In addition, daily wind, solar radiation, and temperature data are taken into account. The proposed method is applied to the IEEE standard 33-bus system. The simulation results show the better performance of the multi-objective salp swarm algorithm (MSSA) at improving voltage profiles and reducing losses in distribution systems. Lastly, the optimal results of the MSSA algorithm are compared with the PSO and GA algorithms.
Given the importance of renewable energy sources in distribution systems, this article addresses the problem of locating and determining the capacity of these sources, namely, wind turbines and solar panels. To solve this optimization problem, a new algorithm based on the behavior of salp is used. The objective functions include reducing losses, improving voltage profiles, and reducing the costs of renewable energy sources. In this method, the allocation of renewable resources is considered for different load models in distribution systems and different load levels using smart meters. Due to the fact that these objective functions are multi-objective, the fuzzy decision-making method is used to select the optimal solution from the set of Pareto solutions. The considered objective functions lead to loss reduction, voltage profile improvement, and RES cost reduction (A allocating RES resources optimally without resource limitations; B: allocating RES resources optimally with resource limitations). In addition, daily wind, solar radiation, and temperature data are taken into account. The proposed method is applied to the IEEE standard 33-bus system. The simulation results show the better performance of the multi-objective salp swarm algorithm (MSSA) at improving voltage profiles and reducing losses in distribution systems. Lastly, the optimal results of the MSSA algorithm are compared with the PSO and GA algorithms.
Record ID
Keywords
energy distribution systems, Optimization, renewable energy sources, salp swarm algorithm, uncertainty
Subject
Suggested Citation
Zishan F, Mansouri S, Abdollahpour F, Grisales-Noreña LF, Montoya OD. Allocation of Renewable Energy Resources in Distribution Systems While considering the Uncertainty of Wind and Solar Resources via the Multi-Objective Salp Swarm Algorithm. (2023). LAPSE:2023.6752
Author Affiliations
Zishan F: Department of Electrical Engineering, Sahand University of Technology, Tabriz 5513351996, Iran [ORCID]
Mansouri S: Faculty of Electrical and Computer engineering, Babol Noushirvaniy University of Technology, Babol 4714873113, Iran
Abdollahpour F: Department of Electrical Engineering, University of Kurdistan, Sanandaj 6617715175, Iran
Grisales-Noreña LF: Department of Electrical Engineering, Faculty of Engineering, Universidad de Talca, Curicó 3340000, Chile [ORCID]
Montoya OD: Grupo de Compatibilidad e Interferencia Electromágnetica (GCEM), Facultad de Ingeniería, Universidad Distrital Francisco José de Caldas, Bogotá 110231, Colombia; Laboratorio Inteligente de Energía, Facultad de Ingeniería, Universidad Tecnológica de [ORCID]
Mansouri S: Faculty of Electrical and Computer engineering, Babol Noushirvaniy University of Technology, Babol 4714873113, Iran
Abdollahpour F: Department of Electrical Engineering, University of Kurdistan, Sanandaj 6617715175, Iran
Grisales-Noreña LF: Department of Electrical Engineering, Faculty of Engineering, Universidad de Talca, Curicó 3340000, Chile [ORCID]
Montoya OD: Grupo de Compatibilidad e Interferencia Electromágnetica (GCEM), Facultad de Ingeniería, Universidad Distrital Francisco José de Caldas, Bogotá 110231, Colombia; Laboratorio Inteligente de Energía, Facultad de Ingeniería, Universidad Tecnológica de [ORCID]
Journal Name
Energies
Volume
16
Issue
1
First Page
474
Year
2023
Publication Date
2023-01-01
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en16010474, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2023.6752
This Record
External Link

https://doi.org/10.3390/en16010474
Publisher Version
Download
Meta
Record Statistics
Record Views
499
Version History
[v1] (Original Submission)
Feb 24, 2023
Verified by curator on
Feb 24, 2023
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2023.6752
Record Owner
Auto Uploader for LAPSE
Links to Related Works
(0.08 seconds)
[0.08 s]
