Priority-based scheduling in residential energy management systems integrated with renewable sources using adaptive Salp swarm algorithm
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F24%3A10255403" target="_blank" >RIV/61989100:27240/24:10255403 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27730/24:10255403
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S2590123024008983" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2590123024008983</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.rineng.2024.102643" target="_blank" >10.1016/j.rineng.2024.102643</a>
Alternative languages
Result language
angličtina
Original language name
Priority-based scheduling in residential energy management systems integrated with renewable sources using adaptive Salp swarm algorithm
Original language description
With the remarkable growth and implementation of communication technology, sensors, and measurement equipment in the Smart Grid (SG) environment, demand side management (DSM) and demand response (DRs) can be easily implementable in residential energy systems integrated with renewable energy sources (RES). Looking at this perspective, this paper suggests an intelligent and dynamic load-priority-based scheduling optimal smart residential energy management system (REMS). The objectives to achieve through priority-based scheduling in the case of a residential energy management system are multi-focussed in terms of peak load reduction, consumer choice of consumption according to priority basis, and cost-effectiveness towards electricity price savings. The issues related to uncertainties with RES due to environmental dependency must be incorporated into the DSM. A single objective discrete formulation based on the Adaptive Salp Swarm Algorithm (ASSA) has been done on modelling and optimizing the crucial system parameters for scheduling, ideally the operation of residential appliances, along with the sources and prioritized-based loads available. System constraints, consumer priorities, energy source availability, uncertainties, and objectives are considered in the formulation to justify the approach that is feasible in real-time conditions. To enhance the search capabilities of SSA, the control parameters vary optimally in both the exploration and exploitation stages of searching. Comparative results with genetic algorithms (GA), particle swarm optimization (PSO), and conventional SSA are presented in different cases, such as (1) traditional homes without REMS, (ii) smart homes with REMS (iii) smart homes using REMS with RES. (C) 2024 The Author(s)
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
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Results in Engineering
ISSN
2590-1230
e-ISSN
2590-1230
Volume of the periodical
23
Issue of the periodical within the volume
September 2024
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
16
Pages from-to
nestránkováno
UT code for WoS article
001287742400001
EID of the result in the Scopus database
2-s2.0-85200128019