Enhancing the Hybrid Microgrid Performance with Jellyfish Optimization for Efficient MPPT and THD Estimation by the Unscented Kalman Filter Article Swipe
Nivedita Singh
,
M. A. Ansari
,
Manoj Tripathy
,
Pratiksha Gupta
,
Ikbal Ali
,
Adel Rawea
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1155/2023/5661381
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1155/2023/5661381
Power management in advanced grid systems requires the seamless integration of diverse renewable energy sources. This study investigates the optimization of a grid-connected system comprising a photovoltaic (PV) solar panel, energy storage system, fuel cell (FC), and diesel generator (DG) using the bioinspired metaheuristic technique called jellyfish optimization (JF). The objective is to maximize power generation from the PV system under normal and partial shading conditions. The performance of JF is compared against particle swarm optimization (PSO) using various parameters. As India heavily relies on solar PV, the results highlight JF’s exceptional effectiveness in extracting maximum power during partial shading scenarios. Inspired by the active and passive motions of jellyfish in the ocean, the JF algorithm is utilized. To further optimize the power output, the system is integrated with an efficient battery management system, PEM fuel cell stacking, and diesel generators. The system’s performance is analyzed using fast Fourier transform (FFT) to evaluate harmonic distortions, which consistently meet the limits specified in IEEE STD 1547-2018. Furthermore, unscented Kalman filter-based analysis is employed to assess total harmonic distortion (THD) and power rating for the grid system across various renewable energy scenarios. The contribution of the jellyfish optimization (JF) algorithm lies in its ability to efficiently and effectively maximize power generation from the PV system, regardless of normal or partial shading conditions. JF, a bioinspired metaheuristic optimization technique, successfully emulates the collective behavior of jellyfish in the ocean to identify optimal solutions. In this study, JF outperforms particle swarm optimization (PSO) in terms of power generation under partial shading conditions. Notably, JF exhibits remarkable capability in exploring the search space and discovering the global optimum, even when the system operates under challenging conditions. Overall, this study demonstrates the tremendous potential of JF in maximizing power generation in grid-connected systems with renewable energy sources while also highlighting the benefits of integrating additional components to further enhance the system performance.
Related Topics
Concepts
Particle swarm optimization
Microgrid
Photovoltaic system
Total harmonic distortion
Computer science
Renewable energy
Maximum power point tracking
Control theory (sociology)
Ant colony optimization algorithms
Engineering
Algorithm
Electrical engineering
Inverter
Artificial intelligence
Control (management)
Voltage
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1155/2023/5661381
- https://downloads.hindawi.com/journals/itees/2023/5661381.pdf
- OA Status
- gold
- Cited By
- 2
- References
- 47
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4384661974
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4384661974Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1155/2023/5661381Digital Object Identifier
- Title
-
Enhancing the Hybrid Microgrid Performance with Jellyfish Optimization for Efficient MPPT and THD Estimation by the Unscented Kalman FilterWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-07-18Full publication date if available
- Authors
-
Nivedita Singh, M. A. Ansari, Manoj Tripathy, Pratiksha Gupta, Ikbal Ali, Adel RaweaList of authors in order
- Landing page
-
https://doi.org/10.1155/2023/5661381Publisher landing page
- PDF URL
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https://downloads.hindawi.com/journals/itees/2023/5661381.pdfDirect link to full text PDF
- 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://downloads.hindawi.com/journals/itees/2023/5661381.pdfDirect OA link when available
- Concepts
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Particle swarm optimization, Microgrid, Photovoltaic system, Total harmonic distortion, Computer science, Renewable energy, Maximum power point tracking, Control theory (sociology), Ant colony optimization algorithms, Engineering, Algorithm, Electrical engineering, Inverter, Artificial intelligence, Control (management), VoltageTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
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2023: 2Per-year citation counts (last 5 years)
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47Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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