Integration of Renewable Energy with Thermal-Based Power Systems: A Review of Grid Reliability, Optimization, and Storage

Stephen Adole Benson; Emmanuel Majiyebo Eronu

doi:doi:10.11648/j.epes.20251402.12

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| Peer-Reviewed

Integration of Renewable Energy with Thermal-Based Power Systems: A Review of Grid Reliability, Optimization, and Storage

Stephen Adole Benson^*

, Emmanuel Majiyebo Eronu

Published in American Journal of Electrical Power and Energy Systems (Volume 14, Issue 2)

Received: 8 April 2025 Accepted: 27 April 2025 Published: 29 May 2025

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Abstract

Thermal power system are major contributors to power generation and are mostly powered by natural gas, coal, and diesel, all of which are derivatives of petroleum. Aside from their inability to meet energy demands, they have led to growing environmental and economic challenges. Dependence on thermal based power system has further necessitated a transition to sustainable energy systems. This article presents a literature review and statistical analysis based on data obtained from 78 articles published between 2017 and 2025 addressing renewable energy, hybrid power systems, energy storage, optimization strategies, and grid stability. Analysis shows that 50% of the reviewed studies were published in 2024, reflecting a rising research interest. Lithium-ion batteries dominate energy storage (65%), followed by solid-state batteries (10%) and hydrogen fuel cells (6%). Optimization methods are increasingly being adopted, with artificial intelligence-based approaches accounting for 40% and metaheuristic algorithms such as genetic algorithms and particle swarm optimization comprising 30%. However, grid stability continues to be a central challenge as highlighted in 55% of the studies reviewed. Therefore, future work should focus on advanced optimization models to enhance system efficiency and stability. Promising approaches could include techniques that integrate voltage sensitivity analysis with artificial intelligence driven optimization models to improve grid resilience and enable real-time energy management. Furthermore, artificial intelligence driven predictive control, block-chain based energy trading, and IoT enabled smart grids are expected to advance energy networks. By leveraging these innovations, renewable energy sources and thermal power systems can be seamlessly integrated, ensuring a more resilient and sustainable energy future.

Published in	American Journal of Electrical Power and Energy Systems (Volume 14, Issue 2)
DOI	10.11648/j.epes.20251402.12
Page(s)	28-44
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2025. Published by Science Publishing Group

Keywords

Renewable Energy Integration, Hybrid Power Systems, Energy Storage, Optimization, Grid Stability, AI-driven Optimization, Voltage Sensitivity Analysis, Smart Grids

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APA Style

Benson, S. A., Eronu, E. M. (2025). Integration of Renewable Energy with Thermal-Based Power Systems: A Review of Grid Reliability, Optimization, and Storage. American Journal of Electrical Power and Energy Systems, 14(2), 28-44. https://doi.org/10.11648/j.epes.20251402.12

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ACS Style

Benson, S. A.; Eronu, E. M. Integration of Renewable Energy with Thermal-Based Power Systems: A Review of Grid Reliability, Optimization, and Storage. Am. J. Electr. Power Energy Syst. 2025, 14(2), 28-44. doi: 10.11648/j.epes.20251402.12

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AMA Style

Benson SA, Eronu EM. Integration of Renewable Energy with Thermal-Based Power Systems: A Review of Grid Reliability, Optimization, and Storage. Am J Electr Power Energy Syst. 2025;14(2):28-44. doi: 10.11648/j.epes.20251402.12

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@article{10.11648/j.epes.20251402.12,
  author = {Stephen Adole Benson and Emmanuel Majiyebo Eronu},
  title = {Integration of Renewable Energy with Thermal-Based Power Systems: A Review of Grid Reliability, Optimization, and Storage
},
  journal = {American Journal of Electrical Power and Energy Systems},
  volume = {14},
  number = {2},
  pages = {28-44},
  doi = {10.11648/j.epes.20251402.12},
  url = {https://doi.org/10.11648/j.epes.20251402.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20251402.12},
  abstract = {Thermal power system are major contributors to power generation and are mostly powered by natural gas, coal, and diesel, all of which are derivatives of petroleum. Aside from their inability to meet energy demands, they have led to growing environmental and economic challenges. Dependence on thermal based power system has further necessitated a transition to sustainable energy systems. This article presents a literature review and statistical analysis based on data obtained from 78 articles published between 2017 and 2025 addressing renewable energy, hybrid power systems, energy storage, optimization strategies, and grid stability. Analysis shows that 50% of the reviewed studies were published in 2024, reflecting a rising research interest. Lithium-ion batteries dominate energy storage (65%), followed by solid-state batteries (10%) and hydrogen fuel cells (6%). Optimization methods are increasingly being adopted, with artificial intelligence-based approaches accounting for 40% and metaheuristic algorithms such as genetic algorithms and particle swarm optimization comprising 30%. However, grid stability continues to be a central challenge as highlighted in 55% of the studies reviewed. Therefore, future work should focus on advanced optimization models to enhance system efficiency and stability. Promising approaches could include techniques that integrate voltage sensitivity analysis with artificial intelligence driven optimization models to improve grid resilience and enable real-time energy management. Furthermore, artificial intelligence driven predictive control, block-chain based energy trading, and IoT enabled smart grids are expected to advance energy networks. By leveraging these innovations, renewable energy sources and thermal power systems can be seamlessly integrated, ensuring a more resilient and sustainable energy future.
},
 year = {2025}
}

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TY  - JOUR
T1  - Integration of Renewable Energy with Thermal-Based Power Systems: A Review of Grid Reliability, Optimization, and Storage

AU  - Stephen Adole Benson
AU  - Emmanuel Majiyebo Eronu
Y1  - 2025/05/29
PY  - 2025
N1  - https://doi.org/10.11648/j.epes.20251402.12
DO  - 10.11648/j.epes.20251402.12
T2  - American Journal of Electrical Power and Energy Systems
JF  - American Journal of Electrical Power and Energy Systems
JO  - American Journal of Electrical Power and Energy Systems
SP  - 28
EP  - 44
PB  - Science Publishing Group
SN  - 2326-9200
UR  - https://doi.org/10.11648/j.epes.20251402.12
AB  - Thermal power system are major contributors to power generation and are mostly powered by natural gas, coal, and diesel, all of which are derivatives of petroleum. Aside from their inability to meet energy demands, they have led to growing environmental and economic challenges. Dependence on thermal based power system has further necessitated a transition to sustainable energy systems. This article presents a literature review and statistical analysis based on data obtained from 78 articles published between 2017 and 2025 addressing renewable energy, hybrid power systems, energy storage, optimization strategies, and grid stability. Analysis shows that 50% of the reviewed studies were published in 2024, reflecting a rising research interest. Lithium-ion batteries dominate energy storage (65%), followed by solid-state batteries (10%) and hydrogen fuel cells (6%). Optimization methods are increasingly being adopted, with artificial intelligence-based approaches accounting for 40% and metaheuristic algorithms such as genetic algorithms and particle swarm optimization comprising 30%. However, grid stability continues to be a central challenge as highlighted in 55% of the studies reviewed. Therefore, future work should focus on advanced optimization models to enhance system efficiency and stability. Promising approaches could include techniques that integrate voltage sensitivity analysis with artificial intelligence driven optimization models to improve grid resilience and enable real-time energy management. Furthermore, artificial intelligence driven predictive control, block-chain based energy trading, and IoT enabled smart grids are expected to advance energy networks. By leveraging these innovations, renewable energy sources and thermal power systems can be seamlessly integrated, ensuring a more resilient and sustainable energy future.

VL  - 14
IS  - 2
ER  -

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Author Information

Stephen Adole Benson

Kaduna State Teachers Service Board, Kaduna, Nigeria

Contact Email

http://orcid.org/0000-0002-3053-6872
Emmanuel Majiyebo Eronu

Department of Electrical Electronic, University of Abuja, FCT Abuja, Nigeria

Contact Email

http://orcid.org/0000-0002-7614-9675

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APA Style

Benson, S. A., Eronu, E. M. (2025). Integration of Renewable Energy with Thermal-Based Power Systems: A Review of Grid Reliability, Optimization, and Storage. American Journal of Electrical Power and Energy Systems, 14(2), 28-44. https://doi.org/10.11648/j.epes.20251402.12

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ACS Style

Benson, S. A.; Eronu, E. M. Integration of Renewable Energy with Thermal-Based Power Systems: A Review of Grid Reliability, Optimization, and Storage. Am. J. Electr. Power Energy Syst. 2025, 14(2), 28-44. doi: 10.11648/j.epes.20251402.12

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AMA Style

Benson SA, Eronu EM. Integration of Renewable Energy with Thermal-Based Power Systems: A Review of Grid Reliability, Optimization, and Storage. Am J Electr Power Energy Syst. 2025;14(2):28-44. doi: 10.11648/j.epes.20251402.12

Copy | Download

@article{10.11648/j.epes.20251402.12,
  author = {Stephen Adole Benson and Emmanuel Majiyebo Eronu},
  title = {Integration of Renewable Energy with Thermal-Based Power Systems: A Review of Grid Reliability, Optimization, and Storage
},
  journal = {American Journal of Electrical Power and Energy Systems},
  volume = {14},
  number = {2},
  pages = {28-44},
  doi = {10.11648/j.epes.20251402.12},
  url = {https://doi.org/10.11648/j.epes.20251402.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20251402.12},
  abstract = {Thermal power system are major contributors to power generation and are mostly powered by natural gas, coal, and diesel, all of which are derivatives of petroleum. Aside from their inability to meet energy demands, they have led to growing environmental and economic challenges. Dependence on thermal based power system has further necessitated a transition to sustainable energy systems. This article presents a literature review and statistical analysis based on data obtained from 78 articles published between 2017 and 2025 addressing renewable energy, hybrid power systems, energy storage, optimization strategies, and grid stability. Analysis shows that 50% of the reviewed studies were published in 2024, reflecting a rising research interest. Lithium-ion batteries dominate energy storage (65%), followed by solid-state batteries (10%) and hydrogen fuel cells (6%). Optimization methods are increasingly being adopted, with artificial intelligence-based approaches accounting for 40% and metaheuristic algorithms such as genetic algorithms and particle swarm optimization comprising 30%. However, grid stability continues to be a central challenge as highlighted in 55% of the studies reviewed. Therefore, future work should focus on advanced optimization models to enhance system efficiency and stability. Promising approaches could include techniques that integrate voltage sensitivity analysis with artificial intelligence driven optimization models to improve grid resilience and enable real-time energy management. Furthermore, artificial intelligence driven predictive control, block-chain based energy trading, and IoT enabled smart grids are expected to advance energy networks. By leveraging these innovations, renewable energy sources and thermal power systems can be seamlessly integrated, ensuring a more resilient and sustainable energy future.
},
 year = {2025}
}

Copy | Download

TY  - JOUR
T1  - Integration of Renewable Energy with Thermal-Based Power Systems: A Review of Grid Reliability, Optimization, and Storage

AU  - Stephen Adole Benson
AU  - Emmanuel Majiyebo Eronu
Y1  - 2025/05/29
PY  - 2025
N1  - https://doi.org/10.11648/j.epes.20251402.12
DO  - 10.11648/j.epes.20251402.12
T2  - American Journal of Electrical Power and Energy Systems
JF  - American Journal of Electrical Power and Energy Systems
JO  - American Journal of Electrical Power and Energy Systems
SP  - 28
EP  - 44
PB  - Science Publishing Group
SN  - 2326-9200
UR  - https://doi.org/10.11648/j.epes.20251402.12
AB  - Thermal power system are major contributors to power generation and are mostly powered by natural gas, coal, and diesel, all of which are derivatives of petroleum. Aside from their inability to meet energy demands, they have led to growing environmental and economic challenges. Dependence on thermal based power system has further necessitated a transition to sustainable energy systems. This article presents a literature review and statistical analysis based on data obtained from 78 articles published between 2017 and 2025 addressing renewable energy, hybrid power systems, energy storage, optimization strategies, and grid stability. Analysis shows that 50% of the reviewed studies were published in 2024, reflecting a rising research interest. Lithium-ion batteries dominate energy storage (65%), followed by solid-state batteries (10%) and hydrogen fuel cells (6%). Optimization methods are increasingly being adopted, with artificial intelligence-based approaches accounting for 40% and metaheuristic algorithms such as genetic algorithms and particle swarm optimization comprising 30%. However, grid stability continues to be a central challenge as highlighted in 55% of the studies reviewed. Therefore, future work should focus on advanced optimization models to enhance system efficiency and stability. Promising approaches could include techniques that integrate voltage sensitivity analysis with artificial intelligence driven optimization models to improve grid resilience and enable real-time energy management. Furthermore, artificial intelligence driven predictive control, block-chain based energy trading, and IoT enabled smart grids are expected to advance energy networks. By leveraging these innovations, renewable energy sources and thermal power systems can be seamlessly integrated, ensuring a more resilient and sustainable energy future.

VL  - 14
IS  - 2
ER  -

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