Fractional Order PID Controller Based‐Neural Network Algorithm for LFC in Multi‐Area Power Systems
Article Swipe
Ali M. El‐Rifaie
,
Slim Abid
,
Ahmed R. Ginidi
,
Abdullah M. Shaheen
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1002/eng2.70028
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1002/eng2.70028
Modern power systems are increasingly challenged by frequency stability issues due to dynamic load variations and the growing complexity of interconnected networks. Traditional PID controllers, while widely utilized, struggle to address the rapid fluctuations and uncertainties inherent in contemporary multi‐area interconnected power systems (MAIPS). This paper introduces an innovative approach to Load Frequency Control (LFC) using a Fractional‐Order PID (FOPID) controller, optimized by a Neural Network Algorithm (NNA). The proposed NNA‐FOPID framework leverages the biological principles of neural networks to dynamically tune controller parameters, significantly enhancing system performance. The solution is tested under various scenarios involving step load changes across multi‐area systems. The proposed method demonstrates marked improvements over traditional PID controllers and advanced optimization techniques such as Differential Evolution (DE) and Artificial Rabbits Algorithm (ARA). The comparisons show that the FOPID controller's NNA‐based design effectively and successfully handles LFC in MAIPSs for ITAE minimizations, and statistical evaluation supports its superiority.
Related Topics
Concepts
PID controller
Computer science
Artificial neural network
Control theory (sociology)
Order (exchange)
Power (physics)
Algorithm
Controller (irrigation)
Engineering
Control engineering
Artificial intelligence
Control (management)
Physics
Temperature control
Biology
Economics
Finance
Quantum mechanics
Agronomy
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/eng2.70028
- OA Status
- gold
- Cited By
- 10
- References
- 55
- Related Works
- 10
- OpenAlex ID
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https://openalex.org/W4407865049Canonical identifier for this work in OpenAlex
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https://doi.org/10.1002/eng2.70028Digital Object Identifier
- Title
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Fractional Order
PID Controller Based‐Neural Network Algorithm forLFC in Multi‐Area Power SystemsWork title - Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-02-01Full publication date if available
- Authors
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Ali M. El‐Rifaie, Slim Abid, Ahmed R. Ginidi, Abdullah M. ShaheenList of authors in order
- Landing page
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https://doi.org/10.1002/eng2.70028Publisher landing page
- Open access
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1002/eng2.70028Direct OA link when available
- Concepts
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PID controller, Computer science, Artificial neural network, Control theory (sociology), Order (exchange), Power (physics), Algorithm, Controller (irrigation), Engineering, Control engineering, Artificial intelligence, Control (management), Physics, Temperature control, Biology, Economics, Finance, Quantum mechanics, AgronomyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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10Total citation count in OpenAlex
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2025: 10Per-year citation counts (last 5 years)
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55Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| primary_location.license | cc-by |
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| primary_location.raw_source_name | Engineering Reports |
| primary_location.landing_page_url | https://doi.org/10.1002/eng2.70028 |
| publication_date | 2025-02-01 |
| publication_year | 2025 |
| referenced_works | https://openalex.org/W3089547809, https://openalex.org/W4399907260, https://openalex.org/W3048548789, https://openalex.org/W3196071416, https://openalex.org/W4220886639, https://openalex.org/W4200430158, https://openalex.org/W4223903927, https://openalex.org/W4400645614, https://openalex.org/W4400495880, https://openalex.org/W4379143889, https://openalex.org/W3088333447, https://openalex.org/W3000288585, https://openalex.org/W4229038883, https://openalex.org/W2921412552, https://openalex.org/W4402679769, https://openalex.org/W2063409030, https://openalex.org/W4367321410, https://openalex.org/W2005244017, https://openalex.org/W2062168005, https://openalex.org/W4363674208, https://openalex.org/W4399178638, https://openalex.org/W1985947223, https://openalex.org/W626048361, https://openalex.org/W2582924769, https://openalex.org/W4307445468, https://openalex.org/W4376865924, https://openalex.org/W4285606765, https://openalex.org/W4402635401, https://openalex.org/W4303700371, https://openalex.org/W4318475932, https://openalex.org/W2883800310, https://openalex.org/W4281756947, https://openalex.org/W3200740744, https://openalex.org/W4306977094, https://openalex.org/W4206182734, https://openalex.org/W2797105518, https://openalex.org/W4297538811, https://openalex.org/W4399802093, https://openalex.org/W4296307159, https://openalex.org/W4293777110, https://openalex.org/W4316469841, https://openalex.org/W2001762124, https://openalex.org/W2099090487, https://openalex.org/W2064146073, https://openalex.org/W4385344091, https://openalex.org/W4387886022, https://openalex.org/W4385307715, https://openalex.org/W3025917812, https://openalex.org/W4289225081, https://openalex.org/W2970296296, https://openalex.org/W4296250115, https://openalex.org/W3120614823, https://openalex.org/W4392109536, https://openalex.org/W3001149645, https://openalex.org/W2904868678 |
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