Bilevel Optimal Economic Dispatch of CNG Main Station Considering Demand Response
Compressed natural gas (CNG) main stations are critical components of the urban energy infrastructure for CNG distribution. Due to its high electrification and significant power consumption, researching the economic operation of the CNG main station in demand response (DR)-based electricity pricing...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/16/7/3080 |
| _version_ | 1797608022743187456 |
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| author | Yongliang Liang Zhiqi Li Yuchuan Li Shuwen Leng Hongmei Cao Kejun Li |
| author_facet | Yongliang Liang Zhiqi Li Yuchuan Li Shuwen Leng Hongmei Cao Kejun Li |
| author_sort | Yongliang Liang |
| collection | DOAJ |
| description | Compressed natural gas (CNG) main stations are critical components of the urban energy infrastructure for CNG distribution. Due to its high electrification and significant power consumption, researching the economic operation of the CNG main station in demand response (DR)-based electricity pricing environments is crucial. In this paper, the dehydration process is considered in the CNG main station energy consumption model to enhance its participation in DR. A bilevel economic dispatch model for the CNG main station is proposed, considering critical peak pricing. The upper-level and lower-level models represent the energy cost minimization problems of the pre-system and rear-system, respectively, with safety operation constraints. The bilevel programming model is solved using a genetic algorithm combined with a bilevel programming method, which has better efficiency and convergence. The proposed optimization scheme has better control performance and stability, reduces the daily electricity cost by approximately 21.04%, and decreases the compressor switching frequency by 50.00% without changing the CNG filling demand, thus significantly extending the compressor’s service life. Moreover, the average comprehensive power cost of processing one unit of CNG reduces 20.62%. |
| first_indexed | 2024-03-11T05:38:46Z |
| format | Article |
| id | doaj.art-600da33902e14d5282e355337b830493 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-11T05:38:46Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-600da33902e14d5282e355337b8304932023-11-17T16:37:06ZengMDPI AGEnergies1996-10732023-03-01167308010.3390/en16073080Bilevel Optimal Economic Dispatch of CNG Main Station Considering Demand ResponseYongliang Liang0Zhiqi Li1Yuchuan Li2Shuwen Leng3Hongmei Cao4Kejun Li5School of Electrical Engineer, Shandong University, Jinan 250061, ChinaSchool of Electrical Engineer, Shandong University, Jinan 250061, ChinaDepartment of Electrical & Electronic Engineering, Imperial College London, London SW7 2AZ, UKHuaneng Shandong Power Generation Co., Ltd., Jinan 250013, ChinaHuaneng Shandong Power Generation Co., Ltd., Jinan 250013, ChinaSchool of Electrical Engineer, Shandong University, Jinan 250061, ChinaCompressed natural gas (CNG) main stations are critical components of the urban energy infrastructure for CNG distribution. Due to its high electrification and significant power consumption, researching the economic operation of the CNG main station in demand response (DR)-based electricity pricing environments is crucial. In this paper, the dehydration process is considered in the CNG main station energy consumption model to enhance its participation in DR. A bilevel economic dispatch model for the CNG main station is proposed, considering critical peak pricing. The upper-level and lower-level models represent the energy cost minimization problems of the pre-system and rear-system, respectively, with safety operation constraints. The bilevel programming model is solved using a genetic algorithm combined with a bilevel programming method, which has better efficiency and convergence. The proposed optimization scheme has better control performance and stability, reduces the daily electricity cost by approximately 21.04%, and decreases the compressor switching frequency by 50.00% without changing the CNG filling demand, thus significantly extending the compressor’s service life. Moreover, the average comprehensive power cost of processing one unit of CNG reduces 20.62%.https://www.mdpi.com/1996-1073/16/7/3080integrated energy user (IEU)CNG main stationbilevel programminggenetic algorithmeconomic dispatchdemand response |
| spellingShingle | Yongliang Liang Zhiqi Li Yuchuan Li Shuwen Leng Hongmei Cao Kejun Li Bilevel Optimal Economic Dispatch of CNG Main Station Considering Demand Response Energies integrated energy user (IEU) CNG main station bilevel programming genetic algorithm economic dispatch demand response |
| title | Bilevel Optimal Economic Dispatch of CNG Main Station Considering Demand Response |
| title_full | Bilevel Optimal Economic Dispatch of CNG Main Station Considering Demand Response |
| title_fullStr | Bilevel Optimal Economic Dispatch of CNG Main Station Considering Demand Response |
| title_full_unstemmed | Bilevel Optimal Economic Dispatch of CNG Main Station Considering Demand Response |
| title_short | Bilevel Optimal Economic Dispatch of CNG Main Station Considering Demand Response |
| title_sort | bilevel optimal economic dispatch of cng main station considering demand response |
| topic | integrated energy user (IEU) CNG main station bilevel programming genetic algorithm economic dispatch demand response |
| url | https://www.mdpi.com/1996-1073/16/7/3080 |
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