A hybrid renewable energy system for Hassi Messaoud region of Algeria: Modeling and optimal sizing
The growing global energy demand and the need to mitigate greenhouse gas emissions have driven the exploration of sustainable and efficient energy solutions. In Algeria, where the energy sector relies heavily on fossil fuels, integrating renewable energy systems is essential for enhancing energy sec...
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KeAi Communications Co., Ltd.
2025-03-01
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| author | Yacine Bourek El Mouatez Billah Messini Chouaib Ammari Mohamed Guenoune Boulerbah Chabira Bipul Krishna Saha |
| author_facet | Yacine Bourek El Mouatez Billah Messini Chouaib Ammari Mohamed Guenoune Boulerbah Chabira Bipul Krishna Saha |
| author_sort | Yacine Bourek |
| collection | DOAJ |
| description | The growing global energy demand and the need to mitigate greenhouse gas emissions have driven the exploration of sustainable and efficient energy solutions. In Algeria, where the energy sector relies heavily on fossil fuels, integrating renewable energy systems is essential for enhancing energy security and reducing environmental impacts. This study focuses on optimizing a hybrid renewable energy system (HRES) for off-grid applications in the Hassi Messaoud region of Algeria to balance technical performance, economic viability, and environmental sustainability. A hybrid system consisting of photovoltaic (PV) panels, wind turbines (WTs), fuel cells (FCs), and diesel generators (DGs) was modeled and optimized using a genetic algorithm (GA). The optimization process aims to minimize the annual cost of the system while ensuring high reliability, as measured by the loss of power supply probability, and maximizing the use of renewable energy. A particle swarm optimization (PSO) approach was also implemented for comparison, highlighting the advantages of the GA in terms of cost distribution and system reliability. The optimized HRES demonstrated that renewable sources (PV and WT) provided 77% of the total energy demand, with an overall system cost of 0.18080 $·kWh−1, significantly lower than recent studies, which reported costs between 0.213 and 0.609 $·kWh−1. FCs contributed 14% to the load, whereas DGs were limited to 8% to minimize emissions, resulting in annual CO2 emissions of 10,865 kg and a relative emission rate of 3.608 gCO2eq·kWh−1. Economic analysis showed that DGs and FCs accounted for 44% and 24% of the annual cost, respectively, highlighting the impact of backup systems in ensuring reliability. Sensitivity analysis under varying load demands and renewable energy availability confirmed the robustness of the system, and the GA approach was found to be more effective than PSO in maintaining cost efficiency and reliability. Additionally, the social analysis highlighted a renewable fraction of 91.5%, emphasizing the contribution of the system to sustainable energy practices. These findings validate GA-based optimization as a superior method for designing cost-effective, reliable, and environmentally sustainable HRES, offering significant potential to reduce fossil fuel dependency in industrial applications. These results not only support the broader adoption of renewable energy systems in similar regions but also contribute valuable insights for future research and policy development in the field of energy sustainability. |
| format | Article |
| id | doaj-art-282ca0be866c4675b13c0f91ad19a227 |
| institution | DOAJ |
| issn | 2772-6835 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Energy Storage and Saving |
| spelling | doaj-art-282ca0be866c4675b13c0f91ad19a2272025-08-20T02:53:43ZengKeAi Communications Co., Ltd.Energy Storage and Saving2772-68352025-03-0141566910.1016/j.enss.2024.10.002A hybrid renewable energy system for Hassi Messaoud region of Algeria: Modeling and optimal sizingYacine Bourek0El Mouatez Billah Messini1Chouaib Ammari2Mohamed Guenoune3Boulerbah Chabira4Bipul Krishna Saha5Department of Electrical Engineering, Faculty of Applied Sciences, University of Ouargla, Ouargla, 30000, AlgeriaDepartment of Electrical Engineering, Faculty of Applied Sciences, University of Ouargla, Ouargla, 30000, Algeria; Laboratoire LAGE, Faculty of Applied Sciences, University of Ouargla, Ouargla, 30000, Algeria; School of Production Engineering and Management, Technical University of Crete, Chania, 73100, Greece; Sonatrach - Algerian Petroleum Institute - Hassi Messaoud School, Hassi Messaoud, 30001, Algeria; Corresponding author at: Department of Electrical Engineering, Faculty of Applied Sciences, University of Ouargla, Ouargla, 30000, Algeria.Department of Renewable Energy, Faculty of Hydrocarbons, Renewable Energy, Science, Earth and Universe, University Kasdi Merbah-Ouargla, Ouargla, 30000, AlgeriaSonatrach - Algerian Petroleum Institute - Hassi Messaoud School, Hassi Messaoud, 30001, AlgeriaSonatrach - Algerian Petroleum Institute - Hassi Messaoud School, Hassi Messaoud, 30001, Algeria; Laboratory of Image Processing and Radiation, University of Sciences and Technology Houari Boumediene, Algiers, 16111, AlgeriaInterdisciplinary Centre for Energy Research (ICER), Indian Institute of Science, Bangalore, 560012, IndiaThe growing global energy demand and the need to mitigate greenhouse gas emissions have driven the exploration of sustainable and efficient energy solutions. In Algeria, where the energy sector relies heavily on fossil fuels, integrating renewable energy systems is essential for enhancing energy security and reducing environmental impacts. This study focuses on optimizing a hybrid renewable energy system (HRES) for off-grid applications in the Hassi Messaoud region of Algeria to balance technical performance, economic viability, and environmental sustainability. A hybrid system consisting of photovoltaic (PV) panels, wind turbines (WTs), fuel cells (FCs), and diesel generators (DGs) was modeled and optimized using a genetic algorithm (GA). The optimization process aims to minimize the annual cost of the system while ensuring high reliability, as measured by the loss of power supply probability, and maximizing the use of renewable energy. A particle swarm optimization (PSO) approach was also implemented for comparison, highlighting the advantages of the GA in terms of cost distribution and system reliability. The optimized HRES demonstrated that renewable sources (PV and WT) provided 77% of the total energy demand, with an overall system cost of 0.18080 $·kWh−1, significantly lower than recent studies, which reported costs between 0.213 and 0.609 $·kWh−1. FCs contributed 14% to the load, whereas DGs were limited to 8% to minimize emissions, resulting in annual CO2 emissions of 10,865 kg and a relative emission rate of 3.608 gCO2eq·kWh−1. Economic analysis showed that DGs and FCs accounted for 44% and 24% of the annual cost, respectively, highlighting the impact of backup systems in ensuring reliability. Sensitivity analysis under varying load demands and renewable energy availability confirmed the robustness of the system, and the GA approach was found to be more effective than PSO in maintaining cost efficiency and reliability. Additionally, the social analysis highlighted a renewable fraction of 91.5%, emphasizing the contribution of the system to sustainable energy practices. These findings validate GA-based optimization as a superior method for designing cost-effective, reliable, and environmentally sustainable HRES, offering significant potential to reduce fossil fuel dependency in industrial applications. These results not only support the broader adoption of renewable energy systems in similar regions but also contribute valuable insights for future research and policy development in the field of energy sustainability.http://www.sciencedirect.com/science/article/pii/S2772683524000414Hybrid renewable energy systemGenetic algorithmOptimal sizing of HRESHydrogen energy storageEnergy system efficiency improvementAlgeria energy transition |
| spellingShingle | Yacine Bourek El Mouatez Billah Messini Chouaib Ammari Mohamed Guenoune Boulerbah Chabira Bipul Krishna Saha A hybrid renewable energy system for Hassi Messaoud region of Algeria: Modeling and optimal sizing Energy Storage and Saving Hybrid renewable energy system Genetic algorithm Optimal sizing of HRES Hydrogen energy storage Energy system efficiency improvement Algeria energy transition |
| title | A hybrid renewable energy system for Hassi Messaoud region of Algeria: Modeling and optimal sizing |
| title_full | A hybrid renewable energy system for Hassi Messaoud region of Algeria: Modeling and optimal sizing |
| title_fullStr | A hybrid renewable energy system for Hassi Messaoud region of Algeria: Modeling and optimal sizing |
| title_full_unstemmed | A hybrid renewable energy system for Hassi Messaoud region of Algeria: Modeling and optimal sizing |
| title_short | A hybrid renewable energy system for Hassi Messaoud region of Algeria: Modeling and optimal sizing |
| title_sort | hybrid renewable energy system for hassi messaoud region of algeria modeling and optimal sizing |
| topic | Hybrid renewable energy system Genetic algorithm Optimal sizing of HRES Hydrogen energy storage Energy system efficiency improvement Algeria energy transition |
| url | http://www.sciencedirect.com/science/article/pii/S2772683524000414 |
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