---
_id: '32334'
abstract:
- lang: eng
text: 'The market for microinverters is growing, especially in Europe. Driven by
the strongly rising prices for electricity, many small photovoltaic energy systems
are being installed. Since monitoring for these plants is often quite costly,
their yields are often not logged. Since 2014, microinverters have been studied
at the University of Paderborn. The investigations are divided into indoor and
outdoor tests. In the indoor area conversion efficiencies as a function of load
have been measured with high accuracy and ranked according to Euro- and CEC weightings.
In the outdoor laboratory, the behavior in the real world is tested. Energy yields
have been measured outdoors via identical and calibrated crystalline silicon PV
modules. Here, the investigations were carried out with modules of the power of
215 Wp until the year 2020. Because of the increasing module power nowadays, modules
with an output of 360 Wp are now being used. To assess the influence of PV module
size, two extremes have been investigated: A rather small module with 215 Wp -
as it has been used 10 years ago, and a brand-new module (2021) offering 360 Wp.
Both types of modules contain 60 solar cells in series connection. Appling the
low-power modules, the challenge for the different micro-inverters has been during
weak-light conditions, using the high-power modules, some inverters temporarily
reach their power limits and yield is reduced. A method using a reference configuration
of inverter & module and a linear equation resulting in the actual yield, any
module & inverter configuration can be characterized by just the two coefficients.'
author:
- first_name: Stefan
full_name: Krauter, Stefan
id: '28836'
last_name: Krauter
orcid: 0000-0002-3594-260X
- first_name: Jörg
full_name: Bendfeld, Jörg
id: '16148'
last_name: Bendfeld
- first_name: Marius Claus
full_name: Möller, Marius Claus
id: '72391'
last_name: Möller
citation:
ama: 'Krauter S, Bendfeld J, Möller MC. Microinverter testing update using high
power modules: Efficiency, yield, and conformity to a new ”estimation formula”
for variation of PV panel size. In: Proceedings of the 49th IEEE Photovoltaic
Specialists Conference. ; 2022.'
apa: 'Krauter, S., Bendfeld, J., & Möller, M. C. (2022). Microinverter testing
update using high power modules: Efficiency, yield, and conformity to a new ”estimation
formula” for variation of PV panel size. Proceedings of the 49th IEEE Photovoltaic
Specialists Conference. 49th IEEE Photovoltaic Specialists Conference, Philadelphia,
PA, USA.'
bibtex: '@inproceedings{Krauter_Bendfeld_Möller_2022, title={Microinverter testing
update using high power modules: Efficiency, yield, and conformity to a new ”estimation
formula” for variation of PV panel size}, booktitle={Proceedings of the 49th IEEE
Photovoltaic Specialists Conference}, author={Krauter, Stefan and Bendfeld, Jörg
and Möller, Marius Claus}, year={2022} }'
chicago: 'Krauter, Stefan, Jörg Bendfeld, and Marius Claus Möller. “Microinverter
Testing Update Using High Power Modules: Efficiency, Yield, and Conformity to
a New ”estimation Formula” for Variation of PV Panel Size.” In Proceedings
of the 49th IEEE Photovoltaic Specialists Conference, 2022.'
ieee: 'S. Krauter, J. Bendfeld, and M. C. Möller, “Microinverter testing update
using high power modules: Efficiency, yield, and conformity to a new ”estimation
formula” for variation of PV panel size,” presented at the 49th IEEE Photovoltaic
Specialists Conference, Philadelphia, PA, USA, 2022.'
mla: 'Krauter, Stefan, et al. “Microinverter Testing Update Using High Power Modules:
Efficiency, Yield, and Conformity to a New ”estimation Formula” for Variation
of PV Panel Size.” Proceedings of the 49th IEEE Photovoltaic Specialists Conference,
2022.'
short: 'S. Krauter, J. Bendfeld, M.C. Möller, in: Proceedings of the 49th IEEE Photovoltaic
Specialists Conference, 2022.'
conference:
end_date: 2022-06-10
location: Philadelphia, PA, USA
name: 49th IEEE Photovoltaic Specialists Conference
start_date: 2022-06-05
date_created: 2022-07-08T07:52:03Z
date_updated: 2022-07-11T06:58:40Z
department:
- _id: '53'
language:
- iso: eng
publication: Proceedings of the 49th IEEE Photovoltaic Specialists Conference
status: public
title: 'Microinverter testing update using high power modules: Efficiency, yield,
and conformity to a new ”estimation formula” for variation of PV panel size'
type: conference
user_id: '16148'
year: '2022'
...
---
_id: '32333'
abstract:
- lang: eng
text: This paper provides a hybrid energy system model created in Matlab/Simulink
which is based on photovoltaics as its main energy source. The model includes
a hybrid energy storage which consists of a short-term lithium-ion battery and
hydrogen as long-term storage to ensure autonomy even during periods of low PV
production (e.g., in winter). The sectors heat and electricity are coupled by
using the waste-heat generated by production and reconversion of hydrogen through
an electrolyser respectively a fuel cell. A heat pump has been considered to cover
the residual heat demand (for well insulated homes). Within this paper a model
of the space heating system as well as the hot water heating system is presented.
The model is designed for the simulation and analysis of a whole year energy flow
by using a time series of loads, weather and heat profiles as input. Moreover,
results of the energy balance within the energy system by simulation of a complete
year by varying the orientation (elevation and azimuth) of the PV system and the
component sizing, such as the lithium-ion battery capacity, are presented. It
turned out that a high amount of heating energy can be saved by using the waste
heat generated by the electrolyser and the fuel cell. The model is well suited
for the analysis of the effects of different component dimensionings in a hydrogen-based
energy system via the overall energy balance within the residential sector.
author:
- first_name: Marius Claus
full_name: Möller, Marius Claus
id: '72391'
last_name: Möller
- first_name: Stefan
full_name: Krauter, Stefan
id: '28836'
last_name: Krauter
orcid: 0000-0002-3594-260X
citation:
ama: 'Möller MC, Krauter S. Model of a Self-Sufficient PV Home using a Hybrid Storage
System based on Li-Ion Batteries and Hydrogen Storage with Waste Heat Utilization
. In: IEEE, ed. Proceedings of the 49th IEEE Photovoltaic Specialists Conference.
; 2022.'
apa: Möller, M. C., & Krauter, S. (2022). Model of a Self-Sufficient PV Home
using a Hybrid Storage System based on Li-Ion Batteries and Hydrogen Storage with
Waste Heat Utilization . In IEEE (Ed.), Proceedings of the 49th IEEE Photovoltaic
Specialists Conference.
bibtex: '@inproceedings{Möller_Krauter_2022, title={Model of a Self-Sufficient PV
Home using a Hybrid Storage System based on Li-Ion Batteries and Hydrogen Storage
with Waste Heat Utilization }, booktitle={Proceedings of the 49th IEEE Photovoltaic
Specialists Conference}, author={Möller, Marius Claus and Krauter, Stefan}, editor={IEEE},
year={2022} }'
chicago: Möller, Marius Claus, and Stefan Krauter. “Model of a Self-Sufficient PV
Home Using a Hybrid Storage System Based on Li-Ion Batteries and Hydrogen Storage
with Waste Heat Utilization .” In Proceedings of the 49th IEEE Photovoltaic
Specialists Conference, edited by IEEE, 2022.
ieee: M. C. Möller and S. Krauter, “Model of a Self-Sufficient PV Home using a Hybrid
Storage System based on Li-Ion Batteries and Hydrogen Storage with Waste Heat
Utilization ,” in Proceedings of the 49th IEEE Photovoltaic Specialists Conference,
Philadelphia, PA, USA, 2022.
mla: Möller, Marius Claus, and Stefan Krauter. “Model of a Self-Sufficient PV Home
Using a Hybrid Storage System Based on Li-Ion Batteries and Hydrogen Storage with
Waste Heat Utilization .” Proceedings of the 49th IEEE Photovoltaic Specialists
Conference, edited by IEEE, 2022.
short: 'M.C. Möller, S. Krauter, in: IEEE (Ed.), Proceedings of the 49th IEEE Photovoltaic
Specialists Conference, 2022.'
conference:
end_date: 2022-06-10
location: Philadelphia, PA, USA
name: 49th IEEE Photovoltaic Specialists Conference
start_date: 2022-06-05
corporate_editor:
- IEEE
date_created: 2022-07-08T07:49:53Z
date_updated: 2022-07-11T06:59:25Z
department:
- _id: '53'
language:
- iso: eng
publication: Proceedings of the 49th IEEE Photovoltaic Specialists Conference
status: public
title: 'Model of a Self-Sufficient PV Home using a Hybrid Storage System based on
Li-Ion Batteries and Hydrogen Storage with Waste Heat Utilization '
type: conference
user_id: '16148'
year: '2022'
...
---
_id: '30262'
abstract:
- lang: eng
text: In this paper, a model of a hybrid, hydrogen-based energy system for a household
which includes the heating sector is presended. With such an energy system it's
possible to enable energy autarky over a whole year based on solar energy. The
scope of this study was to present a verified hybrid energy system model created
in Simulink which can be used to prospectively size future similar energy systems
where hydrogen in combination with a li-ion battery shall be used as energy storage
type.
author:
- first_name: Marius Claus
full_name: Möller, Marius Claus
id: '72391'
last_name: Möller
- first_name: Stefan
full_name: Krauter, Stefan
id: '28836'
last_name: Krauter
orcid: 0000-0002-3594-260X
citation:
ama: Möller MC, Krauter S. Hybrid Energy System Model in Matlab/Simulink based on
Solar Energy, Lithium-Ion Battery and Hydrogen. Energies / Special Issue “Sustainable
Energy Concepts for Energy Transition.” 2022;15 (6), 2201. doi:10.3390/en15062201
apa: Möller, M. C., & Krauter, S. (2022). Hybrid Energy System Model in Matlab/Simulink
based on Solar Energy, Lithium-Ion Battery and Hydrogen. Energies / Special
Issue “Sustainable Energy Concepts for Energy Transition,” 15 (6), 2201.
https://doi.org/10.3390/en15062201
bibtex: '@article{Möller_Krauter_2022, title={Hybrid Energy System Model in Matlab/Simulink
based on Solar Energy, Lithium-Ion Battery and Hydrogen}, volume={15 (6), 2201},
DOI={10.3390/en15062201}, journal={Energies
/ Special Issue “Sustainable Energy Concepts for Energy Transition”}, publisher={MDPI
/ Basel, Switzerland}, author={Möller, Marius Claus and Krauter, Stefan}, year={2022}
}'
chicago: Möller, Marius Claus, and Stefan Krauter. “Hybrid Energy System Model in
Matlab/Simulink Based on Solar Energy, Lithium-Ion Battery and Hydrogen.” Energies
/ Special Issue “Sustainable Energy Concepts for Energy Transition” 15 (6),
2201 (2022). https://doi.org/10.3390/en15062201.
ieee: 'M. C. Möller and S. Krauter, “Hybrid Energy System Model in Matlab/Simulink
based on Solar Energy, Lithium-Ion Battery and Hydrogen,” Energies / Special
Issue “Sustainable Energy Concepts for Energy Transition,” vol. 15 (6), 2201,
2022, doi: 10.3390/en15062201.'
mla: Möller, Marius Claus, and Stefan Krauter. “Hybrid Energy System Model in Matlab/Simulink
Based on Solar Energy, Lithium-Ion Battery and Hydrogen.” Energies / Special
Issue “Sustainable Energy Concepts for Energy Transition,” vol. 15 (6), 2201,
MDPI / Basel, Switzerland, 2022, doi:10.3390/en15062201.
short: M.C. Möller, S. Krauter, Energies / Special Issue “Sustainable Energy Concepts
for Energy Transition” 15 (6), 2201 (2022).
date_created: 2022-03-11T09:56:32Z
date_updated: 2022-07-11T07:03:34Z
department:
- _id: '53'
doi: 10.3390/en15062201
language:
- iso: eng
publication: Energies / Special Issue "Sustainable Energy Concepts for Energy Transition"
publication_identifier:
issn:
- 1996-1073
publication_status: published
publisher: MDPI / Basel, Switzerland
quality_controlled: '1'
status: public
title: Hybrid Energy System Model in Matlab/Simulink based on Solar Energy, Lithium-Ion
Battery and Hydrogen
type: journal_article
user_id: '16148'
volume: 15 (6), 2201
year: '2022'
...
---
_id: '34155'
author:
- first_name: Stefan
full_name: Krauter, Stefan
id: '28836'
last_name: Krauter
orcid: 0000-0002-3594-260X
- first_name: Jörg
full_name: Bendfeld, Jörg
id: '16148'
last_name: Bendfeld
citation:
ama: 'Krauter S, Bendfeld J. Microinverter PV Systems: New Efficiency Rankings and
Formula for Energy Yield Assessment for any PV Panel Size at different Microinverter
types. In: Proceedings of the 8th World Conference on Photovoltaik Energy Conversion.
; 2022.'
apa: 'Krauter, S., & Bendfeld, J. (2022). Microinverter PV Systems: New Efficiency
Rankings and Formula for Energy Yield Assessment for any PV Panel Size at different
Microinverter types. Proceedings of the 8th World Conference on Photovoltaik
Energy Conversion. 8th World Conference on Photovoltaik Energy Conversion,
Milano / Italy.'
bibtex: '@inproceedings{Krauter_Bendfeld_2022, title={Microinverter PV Systems:
New Efficiency Rankings and Formula for Energy Yield Assessment for any PV Panel
Size at different Microinverter types}, booktitle={Proceedings of the 8th World
Conference on Photovoltaik Energy Conversion}, author={Krauter, Stefan and Bendfeld,
Jörg}, year={2022} }'
chicago: 'Krauter, Stefan, and Jörg Bendfeld. “Microinverter PV Systems: New Efficiency
Rankings and Formula for Energy Yield Assessment for Any PV Panel Size at Different
Microinverter Types.” In Proceedings of the 8th World Conference on Photovoltaik
Energy Conversion, 2022.'
ieee: 'S. Krauter and J. Bendfeld, “Microinverter PV Systems: New Efficiency Rankings
and Formula for Energy Yield Assessment for any PV Panel Size at different Microinverter
types,” presented at the 8th World Conference on Photovoltaik Energy Conversion,
Milano / Italy, 2022.'
mla: 'Krauter, Stefan, and Jörg Bendfeld. “Microinverter PV Systems: New Efficiency
Rankings and Formula for Energy Yield Assessment for Any PV Panel Size at Different
Microinverter Types.” Proceedings of the 8th World Conference on Photovoltaik
Energy Conversion, 2022.'
short: 'S. Krauter, J. Bendfeld, in: Proceedings of the 8th World Conference on
Photovoltaik Energy Conversion, 2022.'
conference:
end_date: 2022-09-30
location: Milano / Italy
name: 8th World Conference on Photovoltaik Energy Conversion
start_date: 2022-09-26
date_created: 2022-11-29T09:55:14Z
date_updated: 2022-11-29T10:00:44Z
department:
- _id: '53'
language:
- iso: eng
publication: Proceedings of the 8th World Conference on Photovoltaik Energy Conversion
status: public
title: 'Microinverter PV Systems: New Efficiency Rankings and Formula for Energy Yield
Assessment for any PV Panel Size at different Microinverter types'
type: conference
user_id: '16148'
year: '2022'
...
---
_id: '34156'
author:
- first_name: Josephine Nakato
full_name: Kakande, Josephine Nakato
id: '88649'
last_name: Kakande
- first_name: Godiana Hagile
full_name: Philipo, Godiana Hagile
last_name: Philipo
- first_name: Stefan
full_name: Krauter, Stefan
id: '28836'
last_name: Krauter
orcid: 0000-0002-3594-260X
citation:
ama: 'Kakande JN, Philipo GH, Krauter S. Optimal Design of a Semi Grid-Connected
PV System for a Site in Lwak, Kenya Using HOMER. In: Proceedings of the 8th
World Conference on Photovoltaik Energy Conversion. ; 2022.'
apa: Kakande, J. N., Philipo, G. H., & Krauter, S. (2022). Optimal Design of
a Semi Grid-Connected PV System for a Site in Lwak, Kenya Using HOMER. Proceedings
of the 8th World Conference on Photovoltaik Energy Conversion. 8th World Conference
on Photovoltaik Energy Conversion, Milano / Italy.
bibtex: '@inproceedings{Kakande_Philipo_Krauter_2022, title={Optimal Design of a
Semi Grid-Connected PV System for a Site in Lwak, Kenya Using HOMER}, booktitle={Proceedings
of the 8th World Conference on Photovoltaik Energy Conversion}, author={Kakande,
Josephine Nakato and Philipo, Godiana Hagile and Krauter, Stefan}, year={2022}
}'
chicago: Kakande, Josephine Nakato, Godiana Hagile Philipo, and Stefan Krauter.
“Optimal Design of a Semi Grid-Connected PV System for a Site in Lwak, Kenya Using
HOMER.” In Proceedings of the 8th World Conference on Photovoltaik Energy Conversion,
2022.
ieee: J. N. Kakande, G. H. Philipo, and S. Krauter, “Optimal Design of a Semi Grid-Connected
PV System for a Site in Lwak, Kenya Using HOMER,” presented at the 8th World Conference
on Photovoltaik Energy Conversion, Milano / Italy, 2022.
mla: Kakande, Josephine Nakato, et al. “Optimal Design of a Semi Grid-Connected
PV System for a Site in Lwak, Kenya Using HOMER.” Proceedings of the 8th World
Conference on Photovoltaik Energy Conversion, 2022.
short: 'J.N. Kakande, G.H. Philipo, S. Krauter, in: Proceedings of the 8th World
Conference on Photovoltaik Energy Conversion, 2022.'
conference:
end_date: 2022-09-30
location: Milano / Italy
name: 8th World Conference on Photovoltaik Energy Conversion
start_date: 2022-09-26
date_created: 2022-11-29T10:03:24Z
date_updated: 2022-11-29T10:03:30Z
department:
- _id: '53'
language:
- iso: eng
publication: Proceedings of the 8th World Conference on Photovoltaik Energy Conversion
status: public
title: Optimal Design of a Semi Grid-Connected PV System for a Site in Lwak, Kenya
Using HOMER
type: conference
user_id: '16148'
year: '2022'
...
---
_id: '32403'
abstract:
- lang: eng
text: 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.
article_number: '5215'
author:
- first_name: Godiana Hagile
full_name: Philipo, Godiana Hagile
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.
Energies. 2022;15(14). doi:10.3390/en15145215
apa: Philipo, G. H., Kakande, J. N., & Krauter, S. (2022). Neural Network-Based
Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting
and Peak-Clipping. Energies, 15(14), Article 5215. https://doi.org/10.3390/en15145215
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={10.3390/en15145215},
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.” Energies 15, no. 14 (2022).
https://doi.org/10.3390/en15145215.
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,” Energies, vol. 15, no. 14, Art. no. 5215, 2022, doi: 10.3390/en15145215.'
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.”
Energies, vol. 15, no. 14, 5215, MDPI AG, 2022, doi:10.3390/en15145215.
short: G.H. Philipo, J.N. Kakande, S. Krauter, Energies 15 (2022).
date_created: 2022-07-20T11:46:09Z
date_updated: 2023-10-11T08:26:43Z
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'
...
---
_id: '47961'
abstract:
- lang: eng
text: 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.
article_number: '5215'
author:
- first_name: Godiana Hagile
full_name: Philipo, Godiana Hagile
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.
Energies. 2022;15(14). doi:10.3390/en15145215
apa: Philipo, G. H., Kakande, J. N., & Krauter, S. (2022). Neural Network-Based
Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting
and Peak-Clipping. Energies, 15(14), Article 5215. https://doi.org/10.3390/en15145215
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={10.3390/en15145215},
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.” Energies 15, no. 14 (2022).
https://doi.org/10.3390/en15145215.
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,” Energies, vol. 15, no. 14, Art. no. 5215, 2022, doi: 10.3390/en15145215.'
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.”
Energies, vol. 15, no. 14, 5215, MDPI AG, 2022, doi:10.3390/en15145215.
short: G.H. Philipo, J.N. Kakande, S. Krauter, Energies 15 (2022).
date_created: 2023-10-11T08:13:13Z
date_updated: 2023-10-11T08:14:06Z
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'
...