Cheetah optimization-based smart energy management for appliance scheduling and DER integration in residential and commercial-industrial grids
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10258560" target="_blank" >RIV/61989100:27240/25:10258560 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27730/25:10258560
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S2590174525003241" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2590174525003241</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ecmx.2025.101192" target="_blank" >10.1016/j.ecmx.2025.101192</a>
Alternative languages
Result language
angličtina
Original language name
Cheetah optimization-based smart energy management for appliance scheduling and DER integration in residential and commercial-industrial grids
Original language description
This study proposes a smart energy management strategy for the IEEE 15-bus radial distribution system (RDS) to minimize electricity costs, power losses, and grid dependency, while maximizing renewable energy usage and system stability. The system includes solar (PV) and wind (WT) generation, modeled using Monte Carlo (MC) simulations, along with electric vehicles (EVs) operating in vehicle-to-grid (V2G) mode and battery energy storage systems (BESS), addressing both residential and commercial-industrial loads. These normalized power outputs serve as inputs to a multi-objective optimization framework that balances technical (power loss, voltage stability, fault detection), economic (total electricity cost), and operational criteria. The cheetah optimization algorithm (COA), implemented in MATLAB, handles this complex optimization task. COA offers an adaptive exploration-exploitation balance through dynamic coefficients and stochastic movements, delivering better solution diversity and faster convergence than traditional algorithms such as GA, PSO, and WOA. Simulation results verify COA's superior performance. In the residential sector, COA achieves the lowest multi-objective function value (0.7064), with a 73.37 % increase in renewable energy usage and a 64.49 % drop in grid dependency. Similar improvements appear in commercial-industrial scenarios. These outcomes demonstrate COA's effectiveness in solving smart energy management challenges and establish the proposed framework as a scalable solution for modern smart grids.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20200 - Electrical engineering, Electronic engineering, Information engineering
Result continuities
Project
<a href="/en/project/TN02000025" target="_blank" >TN02000025: National Centre for Energy II</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Energy Conversion and Management-X
ISSN
2590-1745
e-ISSN
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Volume of the periodical
27
Issue of the periodical within the volume
August 2025
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
23
Pages from-to
1-23
UT code for WoS article
001582822800001
EID of the result in the Scopus database
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