Optimal Operation of Multiple Energy System Based on Multi-Objective Theory and Grey Theory
The manufacturing industry consumes electricity and natural gas to provide the power and heat required for manufacturing. Additionally, large amounts of electric energy and heat energy are used, and the electricity cost, amount of environmental pollution, and equipment maintenance cost are high. Thu...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/1/68 |
| _version_ | 1827668567489773568 |
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| author | Bo Hu Nan Wang Zaiming Yu Yunqing Cao Dongsheng Yang Li Sun |
| author_facet | Bo Hu Nan Wang Zaiming Yu Yunqing Cao Dongsheng Yang Li Sun |
| author_sort | Bo Hu |
| collection | DOAJ |
| description | The manufacturing industry consumes electricity and natural gas to provide the power and heat required for manufacturing. Additionally, large amounts of electric energy and heat energy are used, and the electricity cost, amount of environmental pollution, and equipment maintenance cost are high. Thus, optimizing the management of equipment with new energy is important to satisfy the load demand from the system. This paper formulates the scheduling problem of these multiple energy systems as a multi-objective linear regression model (MLRM), and an energy management system is designed focusing on the economy and on greenhouse gas emissions. Furthermore, a variety of optimization objectives and constraints are proposed to make the energy management scheme more practical. Then, grey theory is combined with the common MLRM to accurately represent the uncertainty in the system and to make the model better reflect the actual situation. This paper takes load fluctuation, total grid operation cost, and environmental pollution value as reference standards to measure the effect of the gray optimization algorithm. Lastly, the model is applied to optimize the energy supply plan and its performance is demonstrated using numerical examples. The verification results meet the optimized operating conditions of the multi-energy microgrid system. |
| first_indexed | 2024-03-10T03:44:32Z |
| format | Article |
| id | doaj.art-84617f5d27ba4f2da166fcaa46730437 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T03:44:32Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-84617f5d27ba4f2da166fcaa467304372023-11-23T11:24:58ZengMDPI AGEnergies1996-10732021-12-011516810.3390/en15010068Optimal Operation of Multiple Energy System Based on Multi-Objective Theory and Grey TheoryBo Hu0Nan Wang1Zaiming Yu2Yunqing Cao3Dongsheng Yang4Li Sun5State Grid Liaoning Electric Power Co., Ltd., Shenyang 110006, ChinaState Grid Liaoning Electric Power Co., Ltd., Shenyang 110006, ChinaState Grid Liaoning Electric Power Co., Ltd., Shenyang 110006, ChinaCollege of Physical Science and Technology, Yangzhou University, Yangzhou 225000, ChinaCollege of Information Science and Engineering, Northeastern University, Shenyang 110057, ChinaCollege of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150006, ChinaThe manufacturing industry consumes electricity and natural gas to provide the power and heat required for manufacturing. Additionally, large amounts of electric energy and heat energy are used, and the electricity cost, amount of environmental pollution, and equipment maintenance cost are high. Thus, optimizing the management of equipment with new energy is important to satisfy the load demand from the system. This paper formulates the scheduling problem of these multiple energy systems as a multi-objective linear regression model (MLRM), and an energy management system is designed focusing on the economy and on greenhouse gas emissions. Furthermore, a variety of optimization objectives and constraints are proposed to make the energy management scheme more practical. Then, grey theory is combined with the common MLRM to accurately represent the uncertainty in the system and to make the model better reflect the actual situation. This paper takes load fluctuation, total grid operation cost, and environmental pollution value as reference standards to measure the effect of the gray optimization algorithm. Lastly, the model is applied to optimize the energy supply plan and its performance is demonstrated using numerical examples. The verification results meet the optimized operating conditions of the multi-energy microgrid system.https://www.mdpi.com/1996-1073/15/1/68multiple energy systemoptimal operationmulti-objective linear regression model (MLRM)grey theory |
| spellingShingle | Bo Hu Nan Wang Zaiming Yu Yunqing Cao Dongsheng Yang Li Sun Optimal Operation of Multiple Energy System Based on Multi-Objective Theory and Grey Theory Energies multiple energy system optimal operation multi-objective linear regression model (MLRM) grey theory |
| title | Optimal Operation of Multiple Energy System Based on Multi-Objective Theory and Grey Theory |
| title_full | Optimal Operation of Multiple Energy System Based on Multi-Objective Theory and Grey Theory |
| title_fullStr | Optimal Operation of Multiple Energy System Based on Multi-Objective Theory and Grey Theory |
| title_full_unstemmed | Optimal Operation of Multiple Energy System Based on Multi-Objective Theory and Grey Theory |
| title_short | Optimal Operation of Multiple Energy System Based on Multi-Objective Theory and Grey Theory |
| title_sort | optimal operation of multiple energy system based on multi objective theory and grey theory |
| topic | multiple energy system optimal operation multi-objective linear regression model (MLRM) grey theory |
| url | https://www.mdpi.com/1996-1073/15/1/68 |
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