A novel artificial intelligence based multistage controller for load frequency control in power systems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F24%3A10256141" target="_blank" >RIV/61989100:27240/24:10256141 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27730/24:10256141
Result on the web
<a href="https://www.nature.com/articles/s41598-024-81382-2" target="_blank" >https://www.nature.com/articles/s41598-024-81382-2</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/s41598-024-81382-2" target="_blank" >10.1038/s41598-024-81382-2</a>
Alternative languages
Result language
angličtina
Original language name
A novel artificial intelligence based multistage controller for load frequency control in power systems
Original language description
The imbalance between generated power and load demand often causes unwanted fluctuations in the frequency and tie-line power changes within a power system. To address this issue, a control process known as load frequency control (LFC) is essential. This study aims to optimize the parameters of the LFC controller for a two-area power system that includes a reheat thermal generator and a photovoltaic (PV) power plant. An innovative multi-stage TDn(1 + PI) controller is introduced to reduce the oscillations in frequency and tie-line power changes. This controller combines a tilt-derivative with an N filter (TDn) with a proportional-integral (PI) controller, which improves the system's response by correcting both steady-state errors and the rate of change. This design enhances the stability and speed of dynamic control systems. A new meta-heuristic optimization technique called bio-dynamic grasshopper optimization algorithm (BDGOA) is used for the first time to fine-tune the parameters of the proposed controller and improve its performance. The effectiveness of the controller is evaluated under various load demands, parameter variations, and nonlinearities. Comparisons with other controllers and optimization algorithms show that the BDGOA-TDn(1 + PI) controller significantly reduces overshoot in system frequency and tie-line power changes and achieves faster settling times for these oscillations. Simulation results demonstrate that the BDGOA-TDn(1 + PI) controller significantly outperforms conventional controllers, achieving a reduction in overshoot by 75%, faster settling times by 60%, and a lower integral of time-weighted absolute error by 50% under diverse operating conditions, including parameter variations and nonlinearities such as time delays and governor deadband effects.
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
Scientific Reports
ISSN
2045-2322
e-ISSN
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Volume of the periodical
14
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
32
Pages from-to
1-32
UT code for WoS article
001367267900007
EID of the result in the Scopus database
2-s2.0-85210553882