Offshore Oilfield Hybrid Renewable Power Systems Based on AI Algorithm
This paper proposes a structural optimization model for the offshore oilfield interconnected power system. The model focuses on evaluating the reliability of the system. It is found that the N−1 fault is the primary fault mode leading to severe power loss due to the probability of fault occurrence a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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EDP Sciences
2020-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/51/e3sconf_reee2020_02002.pdf |
| _version_ | 1819180233010446336 |
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| author | Yu Qingguang Jiang Zhicheng Liu Yuming Long Gaoxiang |
| author_facet | Yu Qingguang Jiang Zhicheng Liu Yuming Long Gaoxiang |
| author_sort | Yu Qingguang |
| collection | DOAJ |
| description | This paper proposes a structural optimization model for the offshore oilfield interconnected power system. The model focuses on evaluating the reliability of the system. It is found that the N−1 fault is the primary fault mode leading to severe power loss due to the probability of fault occurrence and the fault consequence according to the statistics of the historical fault information of the offshore oilfield power system. Considering the characteristics of the offshore oil extraction process, the priority of load removal in different processes under different fault conditions is different. Comprehensively considering the above factors, the model uses the minimum load shedding model that considers the load priority level in the objective function to calculate the power outage losses in all N−1 fault states of the system. The test results of numerical examples prove that the optimized solution of the structural optimization model can achieve a better balance between economy and reliability. |
| first_indexed | 2024-12-22T22:11:05Z |
| format | Article |
| id | doaj.art-c29dd50e624143a18b25c9bba150737b |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-12-22T22:11:05Z |
| publishDate | 2020-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-c29dd50e624143a18b25c9bba150737b2022-12-21T18:10:53ZengEDP SciencesE3S Web of Conferences2267-12422020-01-011910200210.1051/e3sconf/202019102002e3sconf_reee2020_02002Offshore Oilfield Hybrid Renewable Power Systems Based on AI AlgorithmYu Qingguang0Jiang Zhicheng1Liu Yuming2Long Gaoxiang3State Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua UniversityState Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua UniversityState Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua UniversityState Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua UniversityThis paper proposes a structural optimization model for the offshore oilfield interconnected power system. The model focuses on evaluating the reliability of the system. It is found that the N−1 fault is the primary fault mode leading to severe power loss due to the probability of fault occurrence and the fault consequence according to the statistics of the historical fault information of the offshore oilfield power system. Considering the characteristics of the offshore oil extraction process, the priority of load removal in different processes under different fault conditions is different. Comprehensively considering the above factors, the model uses the minimum load shedding model that considers the load priority level in the objective function to calculate the power outage losses in all N−1 fault states of the system. The test results of numerical examples prove that the optimized solution of the structural optimization model can achieve a better balance between economy and reliability.https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/51/e3sconf_reee2020_02002.pdf |
| spellingShingle | Yu Qingguang Jiang Zhicheng Liu Yuming Long Gaoxiang Offshore Oilfield Hybrid Renewable Power Systems Based on AI Algorithm E3S Web of Conferences |
| title | Offshore Oilfield Hybrid Renewable Power Systems Based on AI Algorithm |
| title_full | Offshore Oilfield Hybrid Renewable Power Systems Based on AI Algorithm |
| title_fullStr | Offshore Oilfield Hybrid Renewable Power Systems Based on AI Algorithm |
| title_full_unstemmed | Offshore Oilfield Hybrid Renewable Power Systems Based on AI Algorithm |
| title_short | Offshore Oilfield Hybrid Renewable Power Systems Based on AI Algorithm |
| title_sort | offshore oilfield hybrid renewable power systems based on ai algorithm |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/51/e3sconf_reee2020_02002.pdf |
| work_keys_str_mv | AT yuqingguang offshoreoilfieldhybridrenewablepowersystemsbasedonaialgorithm AT jiangzhicheng offshoreoilfieldhybridrenewablepowersystemsbasedonaialgorithm AT liuyuming offshoreoilfieldhybridrenewablepowersystemsbasedonaialgorithm AT longgaoxiang offshoreoilfieldhybridrenewablepowersystemsbasedonaialgorithm |