Advances in Modeling and Optimization of Intelligent Power Systems Integrating Renewable Energy in the Industrial Sector: A Multi-Perspective Review
With the increasing liberalization of energy markets, the penetration of renewable clean energy sources, such as photovoltaics and wind power, has gradually increased, providing more sustainable energy solutions for energy-intensive industrial sectors or parks, such as iron and steel production. How...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/10/2465 |
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| author | Lei Zhang Yuxing Yuan Su Yan Hang Cao Tao Du |
| author_facet | Lei Zhang Yuxing Yuan Su Yan Hang Cao Tao Du |
| author_sort | Lei Zhang |
| collection | DOAJ |
| description | With the increasing liberalization of energy markets, the penetration of renewable clean energy sources, such as photovoltaics and wind power, has gradually increased, providing more sustainable energy solutions for energy-intensive industrial sectors or parks, such as iron and steel production. However, the issues of the intermittency and volatility of renewable energy have become increasingly evident in practical applications, and the economic performance and operational efficiency of localized microgrid systems also demand thorough consideration, posing significant challenges to the decision and management of power system operation. A smart microgrid can effectively enhance the flexibility, reliability, and resilience of the grid, through the frequent interaction of generation–grid–load. Therefore, this paper will provide a comprehensive summary of existing knowledge and a review of the research progress on the methodologies and strategies of modeling technologies for intelligent power systems integrating renewable energy in industrial production. |
| format | Article |
| id | doaj-art-93e6699e910044aea58d5dbf2d691d41 |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-93e6699e910044aea58d5dbf2d691d412025-08-20T03:47:54ZengMDPI AGEnergies1996-10732025-05-011810246510.3390/en18102465Advances in Modeling and Optimization of Intelligent Power Systems Integrating Renewable Energy in the Industrial Sector: A Multi-Perspective ReviewLei Zhang0Yuxing Yuan1Su Yan2Hang Cao3Tao Du4Key Laboratory of Eco-Industry, Ministry of Ecology and Environment, Northeastern University, Shenyang 110819, ChinaKey Laboratory of Eco-Industry, Ministry of Ecology and Environment, Northeastern University, Shenyang 110819, ChinaKey Laboratory of Eco-Industry, Ministry of Ecology and Environment, Northeastern University, Shenyang 110819, ChinaKey Laboratory of Eco-Industry, Ministry of Ecology and Environment, Northeastern University, Shenyang 110819, ChinaKey Laboratory of Eco-Industry, Ministry of Ecology and Environment, Northeastern University, Shenyang 110819, ChinaWith the increasing liberalization of energy markets, the penetration of renewable clean energy sources, such as photovoltaics and wind power, has gradually increased, providing more sustainable energy solutions for energy-intensive industrial sectors or parks, such as iron and steel production. However, the issues of the intermittency and volatility of renewable energy have become increasingly evident in practical applications, and the economic performance and operational efficiency of localized microgrid systems also demand thorough consideration, posing significant challenges to the decision and management of power system operation. A smart microgrid can effectively enhance the flexibility, reliability, and resilience of the grid, through the frequent interaction of generation–grid–load. Therefore, this paper will provide a comprehensive summary of existing knowledge and a review of the research progress on the methodologies and strategies of modeling technologies for intelligent power systems integrating renewable energy in industrial production.https://www.mdpi.com/1996-1073/18/10/2465smart microgridrenewable energymodeling techniques of predictionmodeling techniques for microgrid scheduling |
| spellingShingle | Lei Zhang Yuxing Yuan Su Yan Hang Cao Tao Du Advances in Modeling and Optimization of Intelligent Power Systems Integrating Renewable Energy in the Industrial Sector: A Multi-Perspective Review Energies smart microgrid renewable energy modeling techniques of prediction modeling techniques for microgrid scheduling |
| title | Advances in Modeling and Optimization of Intelligent Power Systems Integrating Renewable Energy in the Industrial Sector: A Multi-Perspective Review |
| title_full | Advances in Modeling and Optimization of Intelligent Power Systems Integrating Renewable Energy in the Industrial Sector: A Multi-Perspective Review |
| title_fullStr | Advances in Modeling and Optimization of Intelligent Power Systems Integrating Renewable Energy in the Industrial Sector: A Multi-Perspective Review |
| title_full_unstemmed | Advances in Modeling and Optimization of Intelligent Power Systems Integrating Renewable Energy in the Industrial Sector: A Multi-Perspective Review |
| title_short | Advances in Modeling and Optimization of Intelligent Power Systems Integrating Renewable Energy in the Industrial Sector: A Multi-Perspective Review |
| title_sort | advances in modeling and optimization of intelligent power systems integrating renewable energy in the industrial sector a multi perspective review |
| topic | smart microgrid renewable energy modeling techniques of prediction modeling techniques for microgrid scheduling |
| url | https://www.mdpi.com/1996-1073/18/10/2465 |
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