A surrogate-assisted point estimate method for hybrid probabilistic and interval power flow in distribution networks
The uncertain power flow analysis is essential to assessing the operating states of distribution networks under various uncertainties. The power flow calculations considering the single uncertainty have been well developed. However, different types of uncertainties may coexist in power systems. In o...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-11-01
|
| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484722014883 |
| _version_ | 1797900734198448128 |
|---|---|
| author | Chenxu Wang Yan Peng Yixi Zhou Junchao Ma Chengyu Lu Xiyun Yang |
| author_facet | Chenxu Wang Yan Peng Yixi Zhou Junchao Ma Chengyu Lu Xiyun Yang |
| author_sort | Chenxu Wang |
| collection | DOAJ |
| description | The uncertain power flow analysis is essential to assessing the operating states of distribution networks under various uncertainties. The power flow calculations considering the single uncertainty have been well developed. However, different types of uncertainties may coexist in power systems. In order to comprehensively assess the impacts of mixed uncertainties, this paper proposes a surrogate-assisted point estimate method to solve the hybrid probabilistic and interval power flow. By taking advantage of the point estimate method and high-fidelity surrogate model, the proposed method can accurately obtain the relevant results of power flow calculation with high efficiency. The numerical studies in IEEE 33-bus and 141-bus systems verify the accuracy and efficiency of the proposed method by comparing it with other well-known methods. |
| first_indexed | 2024-04-10T08:49:36Z |
| format | Article |
| id | doaj.art-ea16909bedf44eff8477aa16855f5d58 |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-04-10T08:49:36Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-ea16909bedf44eff8477aa16855f5d582023-02-22T04:31:08ZengElsevierEnergy Reports2352-48472022-11-018713721A surrogate-assisted point estimate method for hybrid probabilistic and interval power flow in distribution networksChenxu Wang0Yan Peng1Yixi Zhou2Junchao Ma3Chengyu Lu4Xiyun Yang5Electric Power Research Institute of State Grid Zhejiang Electric Power Corporation, Hangzhou 310014, China; Corresponding author.Electric Power Research Institute of State Grid Zhejiang Electric Power Corporation, Hangzhou 310014, ChinaState Grid Hangzhou Electric Power Supply Company, Hangzhou 310020, ChinaElectric Power Research Institute of State Grid Zhejiang Electric Power Corporation, Hangzhou 310014, ChinaElectric Power Research Institute of State Grid Zhejiang Electric Power Corporation, Hangzhou 310014, ChinaSchool of Control and Computer Engineering, North China Electric Power University, Beijing 102206, ChinaThe uncertain power flow analysis is essential to assessing the operating states of distribution networks under various uncertainties. The power flow calculations considering the single uncertainty have been well developed. However, different types of uncertainties may coexist in power systems. In order to comprehensively assess the impacts of mixed uncertainties, this paper proposes a surrogate-assisted point estimate method to solve the hybrid probabilistic and interval power flow. By taking advantage of the point estimate method and high-fidelity surrogate model, the proposed method can accurately obtain the relevant results of power flow calculation with high efficiency. The numerical studies in IEEE 33-bus and 141-bus systems verify the accuracy and efficiency of the proposed method by comparing it with other well-known methods.http://www.sciencedirect.com/science/article/pii/S2352484722014883Uncertain power flowHybrid uncertaintiesDistributed generatorsPoint estimate methodSurrogate model |
| spellingShingle | Chenxu Wang Yan Peng Yixi Zhou Junchao Ma Chengyu Lu Xiyun Yang A surrogate-assisted point estimate method for hybrid probabilistic and interval power flow in distribution networks Energy Reports Uncertain power flow Hybrid uncertainties Distributed generators Point estimate method Surrogate model |
| title | A surrogate-assisted point estimate method for hybrid probabilistic and interval power flow in distribution networks |
| title_full | A surrogate-assisted point estimate method for hybrid probabilistic and interval power flow in distribution networks |
| title_fullStr | A surrogate-assisted point estimate method for hybrid probabilistic and interval power flow in distribution networks |
| title_full_unstemmed | A surrogate-assisted point estimate method for hybrid probabilistic and interval power flow in distribution networks |
| title_short | A surrogate-assisted point estimate method for hybrid probabilistic and interval power flow in distribution networks |
| title_sort | surrogate assisted point estimate method for hybrid probabilistic and interval power flow in distribution networks |
| topic | Uncertain power flow Hybrid uncertainties Distributed generators Point estimate method Surrogate model |
| url | http://www.sciencedirect.com/science/article/pii/S2352484722014883 |
| work_keys_str_mv | AT chenxuwang asurrogateassistedpointestimatemethodforhybridprobabilisticandintervalpowerflowindistributionnetworks AT yanpeng asurrogateassistedpointestimatemethodforhybridprobabilisticandintervalpowerflowindistributionnetworks AT yixizhou asurrogateassistedpointestimatemethodforhybridprobabilisticandintervalpowerflowindistributionnetworks AT junchaoma asurrogateassistedpointestimatemethodforhybridprobabilisticandintervalpowerflowindistributionnetworks AT chengyulu asurrogateassistedpointestimatemethodforhybridprobabilisticandintervalpowerflowindistributionnetworks AT xiyunyang asurrogateassistedpointestimatemethodforhybridprobabilisticandintervalpowerflowindistributionnetworks AT chenxuwang surrogateassistedpointestimatemethodforhybridprobabilisticandintervalpowerflowindistributionnetworks AT yanpeng surrogateassistedpointestimatemethodforhybridprobabilisticandintervalpowerflowindistributionnetworks AT yixizhou surrogateassistedpointestimatemethodforhybridprobabilisticandintervalpowerflowindistributionnetworks AT junchaoma surrogateassistedpointestimatemethodforhybridprobabilisticandintervalpowerflowindistributionnetworks AT chengyulu surrogateassistedpointestimatemethodforhybridprobabilisticandintervalpowerflowindistributionnetworks AT xiyunyang surrogateassistedpointestimatemethodforhybridprobabilisticandintervalpowerflowindistributionnetworks |