dc.contributor.author |
Premadasa, PND |
|
dc.contributor.author |
Silva, CMMRS |
|
dc.contributor.author |
Chandima, DP |
|
dc.contributor.author |
Karunadasa, JP |
|
dc.contributor.editor |
Abeysooriya, R |
|
dc.contributor.editor |
Adikariwattage, V |
|
dc.contributor.editor |
Hemachandra, K |
|
dc.date.accessioned |
2024-03-21T08:13:00Z |
|
dc.date.available |
2024-03-21T08:13:00Z |
|
dc.date.issued |
2023-12-09 |
|
dc.identifier.citation |
P. N. D. Premadasa, C. M. M. R. S. Silva, D. P. Chandima and J. P. Karunadasa, "Optimal Sizing of Solar Photovoltaics and Battery Storage for Domestic Prosumers Using Genetic Algorithm," 2023 Moratuwa Engineering Research Conference (MERCon), Moratuwa, Sri Lanka, 2023, pp. 131-136, doi: 10.1109/MERCon60487.2023.10355510. |
en_US |
dc.identifier.uri |
http://dl.lib.uom.lk/handle/123/22362 |
|
dc.description.abstract |
Recently, the number of prosumers is increasing
significantly in the electrical system. Most prosumers use solar
photovoltaics to generate electricity; some even use batteries to
store excess energy. However, integrating solar photovoltaics with
batteries increases the system costs. Therefore, optimal sizing
of these storage systems and renewable generation is a critical
requirement of the prosumers to reduce investment costs and
increase system efficiency. Also, having the correct renewable
generation and storage capacity sizes is crucial to profit from the
system. This study presents an optimal sizing algorithm to size the
solar photovoltaic system and battery storage system for domestic
prosumers, giving the minimum cost using genetic algorithm. In
the context of Sri Lanka, grid availability also uses as an input
parameter to optimize the system capacities since the country
had planned power outages continuously throughout a year. By
contrast, the optimization results found that 14 solar panels with
8kWh battery capacity are sufficient for a load profile that has a
peak demand of 4.5kW with a grid availability of 88.9%. Also,
the optimized system has a 14-year payback period and a 6.8%
of loss of load probability. With the proposed integrated system,
power availability has been increased by 4.8%. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
IEEE |
en_US |
dc.relation.uri |
https://ieeexplore.ieee.org/document/10355510/ |
en_US |
dc.subject |
Solar photovoltaics |
en_US |
dc.subject |
Battery storage |
en_US |
dc.subject |
Prosumers |
en_US |
dc.subject |
Optimal sizing |
en_US |
dc.subject |
Genetic algorithm |
en_US |
dc.title |
Optimal sizing of solar photovoltaics and battery storage for domestic prosumers using genetic algorithm |
en_US |
dc.type |
Conference-Full-text |
en_US |
dc.identifier.faculty |
Engineering |
en_US |
dc.identifier.department |
Engineering Research Unit, University of Moratuwa |
en_US |
dc.identifier.year |
2023 |
en_US |
dc.identifier.conference |
Moratuwa Engineering Research Conference 2023 |
en_US |
dc.identifier.place |
Katubedda |
en_US |
dc.identifier.pgnos |
pp. 131-136 |
en_US |
dc.identifier.proceeding |
Proceedings of Moratuwa Engineering Research Conference 2023 |
en_US |
dc.identifier.email |
dishanin@uom.lk |
en_US |
dc.identifier.email |
silvacmmrs.20@uom.lk |
en_US |
dc.identifier.email |
chandimadp@uom.lk |
en_US |
dc.identifier.email |
karunadasaj@uom.lk |
en_US |