Repository logo
  • Log In
    New user? Click here to register.Have you forgotten your password?
University College Dublin
    Colleges & Schools
    Statistics
    All of DSpace
  • Log In
    New user? Click here to register.Have you forgotten your password?
  1. Home
  2. College of Engineering & Architecture
  3. School of Electrical and Electronic Engineering
  4. Electrical and Electronic Engineering Research Collection
  5. Scenario-Based Stochastic Framework for Optimal Planning of Distribution Systems Including Renewable-Based DG Units
 
  • Details
Options

Scenario-Based Stochastic Framework for Optimal Planning of Distribution Systems Including Renewable-Based DG Units

Author(s)
Ramadan, Ashraf  
Ebeed, Mohamed  
Kamel, Salah  
Abdelaziz, Almoataz Y.  
Alhelou, Hassan Haes  
Uri
http://hdl.handle.net/10197/25323
Date Issued
2021-03-23
Date Available
2024-01-26T17:18:15Z
Abstract
Renewable energy-based distributed generators are widely embedded into distribution systems for several economical, technical, and environmental tasks. The main concern related to the renewable-based distributed generators, especially photovoltaic and wind turbine generators, is the continuous variations in their output powers due to variations in solar irradiance and wind speed, which leads to uncertainties in the power system. Therefore, the uncertainties of these resources should be considered for feasible planning. The main innovation of this paper is that it proposes an efficient stochastic framework for the optimal planning of distribution systems with optimal inclusion of renewable-based distributed generators, considering the uncertainties of load demands and the output powers of the distributed generators. The proposed stochastic framework depends upon the scenario-based method for modeling the uncertainties in distribution systems. In this framework, a multi-objective function is considered for optimal planning, including minimization of the expected total power loss, the total system voltage deviation, the total cost, and the total emissions, in addition to enhancing the expected total voltage stability. A novel efficient technique known as the Equilibrium Optimizer (EO) is actualized to appoint the ratings and locations of renewable-based distributed generators. The effectiveness of the proposed strategy is applied on an IEEE 69-bus network and a 94-bus practical distribution system situated in Portugal. The simulations verify the feasibility of the framework for optimal power planning. Additionally, the results show that the optimal integration of the photovoltaic and wind turbine generators using the proposed method leads to a reduction in the expected power losses, voltage deviations, cost, and emission rate and enhances the voltage stability by 60.95%, 37.09%, 2.91%, 70.66%, and 48.73%, respectively, in the 69-bus system, while in the 94-bus system these values are enhanced to be 48.38%, 39.73%, 57.06%, 76.42%, and 11.99%, respectively.
Sponsorship
Science Foundation Ireland
Other Sponsorship
UCD Energy Institute
Type of Material
Journal Article
Publisher
MDPI
Journal
Sustainability
Volume
13
Issue
6
Copyright (Published Version)
2021 the Authors
Subjects

Renewable energy

Uncertainties

Distributed generator...

Wind turbine

Solar photovoltaic

Equilibrium optimizer...

Radial distribution s...

Scenario-based method...

DOI
10.3390/su13063566
Language
English
Status of Item
Peer reviewed
ISSN
2071-1050
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by/3.0/ie/
File(s)
Loading...
Thumbnail Image
Name

sustainability-13-03566.pdf

Size

862.54 KB

Format

Adobe PDF

Checksum (MD5)

f041af2b53d988f7c16548b41681f92d

Owning collection
Electrical and Electronic Engineering Research Collection
Mapped collections
Energy Institute Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

For all queries please contact research.repository@ucd.ie.

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Cookie settings
  • Privacy policy
  • End User Agreement