Multi-Objective Optimization Design for a Hybrid Energy System Using the Genetic Algorithm
To secure a stable energy supply and bring renewable energy to buildings within a reasonable cost range, a hybrid energy system (HES) that integrates both fossil fuel energy systems (FFESs) and new and renewable energy systems (NRESs) needs to be designed and applied. This paper presents a methodolo...
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-04-01
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| Series: | Energies |
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| Online Access: | http://www.mdpi.com/1996-1073/8/4/2924 |
| _version_ | 1811303726904770560 |
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| author | Myeong Jin Ko Yong Shik Kim Min Hee Chung Hung Chan Jeon |
| author_facet | Myeong Jin Ko Yong Shik Kim Min Hee Chung Hung Chan Jeon |
| author_sort | Myeong Jin Ko |
| collection | DOAJ |
| description | To secure a stable energy supply and bring renewable energy to buildings within a reasonable cost range, a hybrid energy system (HES) that integrates both fossil fuel energy systems (FFESs) and new and renewable energy systems (NRESs) needs to be designed and applied. This paper presents a methodology to optimize a HES consisting of three types of NRESs and six types of FFESs while simultaneously minimizing life cycle cost (LCC), maximizing penetration of renewable energy and minimizing annual greenhouse gas (GHG) emissions. An elitist non-dominated sorting genetic algorithm is utilized for multi-objective optimization. As an example, we have designed the optimal configuration and sizing for a HES in an elementary school. The evolution of Pareto-optimal solutions according to the variation in the economic, technical and environmental objective functions through generations is discussed. The pair wise trade-offs among the three objectives are also examined. |
| first_indexed | 2024-04-13T07:53:09Z |
| format | Article |
| id | doaj.art-18176cb712904b9b8a6d38f8aa82166c |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-13T07:53:09Z |
| publishDate | 2015-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-18176cb712904b9b8a6d38f8aa82166c2022-12-22T02:55:28ZengMDPI AGEnergies1996-10732015-04-01842924294910.3390/en8042924en8042924Multi-Objective Optimization Design for a Hybrid Energy System Using the Genetic AlgorithmMyeong Jin Ko0Yong Shik Kim1Min Hee Chung2Hung Chan Jeon3Urban Development Institute, Incheon National University, Incheon 406-772, KoreaDivision of Architecture & Urban Planning, Incheon National University, Incheon 406-772, KoreaCentre for Sustainable Architecture and Building System Research, School of Architecture, Chung-Ang University, Seoul 156-756, KoreaDepartment of Architectural Engineering, Suwon University, Hwaseong 445-743, KoreaTo secure a stable energy supply and bring renewable energy to buildings within a reasonable cost range, a hybrid energy system (HES) that integrates both fossil fuel energy systems (FFESs) and new and renewable energy systems (NRESs) needs to be designed and applied. This paper presents a methodology to optimize a HES consisting of three types of NRESs and six types of FFESs while simultaneously minimizing life cycle cost (LCC), maximizing penetration of renewable energy and minimizing annual greenhouse gas (GHG) emissions. An elitist non-dominated sorting genetic algorithm is utilized for multi-objective optimization. As an example, we have designed the optimal configuration and sizing for a HES in an elementary school. The evolution of Pareto-optimal solutions according to the variation in the economic, technical and environmental objective functions through generations is discussed. The pair wise trade-offs among the three objectives are also examined.http://www.mdpi.com/1996-1073/8/4/2924hybrid energy systemgenetic algorithmmulti-objective optimizationlife cycle costpenetration of renewable energygreenhouse gas emissions |
| spellingShingle | Myeong Jin Ko Yong Shik Kim Min Hee Chung Hung Chan Jeon Multi-Objective Optimization Design for a Hybrid Energy System Using the Genetic Algorithm Energies hybrid energy system genetic algorithm multi-objective optimization life cycle cost penetration of renewable energy greenhouse gas emissions |
| title | Multi-Objective Optimization Design for a Hybrid Energy System Using the Genetic Algorithm |
| title_full | Multi-Objective Optimization Design for a Hybrid Energy System Using the Genetic Algorithm |
| title_fullStr | Multi-Objective Optimization Design for a Hybrid Energy System Using the Genetic Algorithm |
| title_full_unstemmed | Multi-Objective Optimization Design for a Hybrid Energy System Using the Genetic Algorithm |
| title_short | Multi-Objective Optimization Design for a Hybrid Energy System Using the Genetic Algorithm |
| title_sort | multi objective optimization design for a hybrid energy system using the genetic algorithm |
| topic | hybrid energy system genetic algorithm multi-objective optimization life cycle cost penetration of renewable energy greenhouse gas emissions |
| url | http://www.mdpi.com/1996-1073/8/4/2924 |
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