---
_id: '47961'
abstract:
- lang: eng
  text: <jats:p>Due to failures or even the absence of an electricity grid, microgrid
    systems are becoming popular solutions for electrifying African rural communities.
    However, they are heavily stressed and complex to control due to their intermittency
    and demand growth. Demand side management (DSM) serves as an option to increase
    the level of flexibility on the demand side by scheduling users’ consumption patterns
    profiles in response to supply. This paper proposes a demand-side management strategy
    based on load shifting and peak clipping. The proposed approach was modelled in
    a MATLAB/Simulink R2021a environment and was optimized using the artificial neural
    network (ANN) algorithm. Simulations were carried out to test the model’s efficacy
    in a stand-alone PV-battery microgrid in East Africa. The proposed algorithm reduces
    the peak demand, smoothing the load profile to the desired level, and improves
    the system’s peak to average ratio (PAR). The presence of deferrable loads has
    been considered to bring more flexible demand-side management. Results promise
    decreases in peak demand and peak to average ratio of about 31.2% and 7.5% through
    peak clipping. In addition, load shifting promises more flexibility to customers.</jats:p>
article_number: '5215'
author:
- first_name: Godiana Hagile
  full_name: Philipo, Godiana Hagile
  id: '88505'
  last_name: Philipo
- first_name: Josephine Nakato
  full_name: Kakande, Josephine Nakato
  id: '88649'
  last_name: Kakande
- first_name: Stefan
  full_name: Krauter, Stefan
  id: '28836'
  last_name: Krauter
  orcid: 0000-0002-3594-260X
citation:
  ama: Philipo GH, Kakande JN, Krauter S. Neural Network-Based Demand-Side Management
    in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping.
    <i>Energies</i>. 2022;15(14). doi:<a href="https://doi.org/10.3390/en15145215">10.3390/en15145215</a>
  apa: Philipo, G. H., Kakande, J. N., &#38; Krauter, S. (2022). Neural Network-Based
    Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting
    and Peak-Clipping. <i>Energies</i>, <i>15</i>(14), Article 5215. <a href="https://doi.org/10.3390/en15145215">https://doi.org/10.3390/en15145215</a>
  bibtex: '@article{Philipo_Kakande_Krauter_2022, title={Neural Network-Based Demand-Side
    Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and
    Peak-Clipping}, volume={15}, DOI={<a href="https://doi.org/10.3390/en15145215">10.3390/en15145215</a>},
    number={145215}, journal={Energies}, publisher={MDPI AG}, author={Philipo, Godiana
    Hagile and Kakande, Josephine Nakato and Krauter, Stefan}, year={2022} }'
  chicago: Philipo, Godiana Hagile, Josephine Nakato Kakande, and Stefan Krauter.
    “Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery
    Microgrid Using Load-Shifting and Peak-Clipping.” <i>Energies</i> 15, no. 14 (2022).
    <a href="https://doi.org/10.3390/en15145215">https://doi.org/10.3390/en15145215</a>.
  ieee: 'G. H. Philipo, J. N. Kakande, and S. Krauter, “Neural Network-Based Demand-Side
    Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and
    Peak-Clipping,” <i>Energies</i>, vol. 15, no. 14, Art. no. 5215, 2022, doi: <a
    href="https://doi.org/10.3390/en15145215">10.3390/en15145215</a>.'
  mla: Philipo, Godiana Hagile, et al. “Neural Network-Based Demand-Side Management
    in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping.”
    <i>Energies</i>, vol. 15, no. 14, 5215, MDPI AG, 2022, doi:<a href="https://doi.org/10.3390/en15145215">10.3390/en15145215</a>.
  short: G.H. Philipo, J.N. Kakande, S. Krauter, Energies 15 (2022).
date_created: 2023-10-11T08:13:13Z
date_updated: 2024-10-17T08:46:23Z
department:
- _id: '53'
doi: 10.3390/en15145215
intvolume: '        15'
issue: '14'
keyword:
- Energy (miscellaneous)
- Energy Engineering and Power Technology
- Renewable Energy
- Sustainability and the Environment
- Electrical and Electronic Engineering
- Control and Optimization
- Engineering (miscellaneous)
- Building and Construction
language:
- iso: eng
publication: Energies
publication_identifier:
  issn:
  - 1996-1073
publication_status: published
publisher: MDPI AG
status: public
title: Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery
  Microgrid Using Load-Shifting and Peak-Clipping
type: journal_article
user_id: '16148'
volume: 15
year: '2022'
...