An islanding partition method of active distribution networks based on chance-constrained programming
Relationship between restored loads and chance level at different fault time. [Display omitted] •The uncertainties of islanding operation in ADNs were modelled.•A chance-constrained programming based model was built for islanding partition.•The effects of the chance level on the islanding partition...
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| Vydáno v: | Applied energy Ročník 242; s. 78 - 91 |
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| Hlavní autoři: | , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier Ltd
15.05.2019
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| Témata: | |
| ISSN: | 0306-2619, 1872-9118 |
| On-line přístup: | Získat plný text |
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| Abstract | Relationship between restored loads and chance level at different fault time.
[Display omitted]
•The uncertainties of islanding operation in ADNs were modelled.•A chance-constrained programming based model was built for islanding partition.•The effects of the chance level on the islanding partition strategies were explored.
With the high integration of uncontrollable distributed generators (NDGs) comprising photovoltaic arrays (PVs) and wind turbines (WTs), many technical issues have become increasingly prominent in the islanding operation of active distribution networks (ADNs). Such problems including branch overloading and voltage violations threaten the secure operation of distribution systems and a continuous power supply. To address the uncertainties of NDG outputs when implementing islanding partition strategies, this paper proposes a new method of the islanding partition of ADNs based on chance-constrained programming. First, power generation scenarios and probability distributions for these scenarios are generated according to historical data considering the time series characteristics and uncertainties of NDGs. Then, the chance-constrained description of islanding operation is expanded to consider the effect of uncertainties related to NDGs. Moreover, an islanding partition model of ADNs based on chance-constrained programming is established. By applying convex relaxation and introducing auxiliary variables, the model is converted to a mixed-integer quadratically constrained programming model that can be effectively solved. Finally, case studies involving the modified IEEE 33-node system, IEEE 123-node system and an actual distribution system are conducted to verify the effectiveness and scalability of the proposed method. |
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| AbstractList | With the high integration of uncontrollable distributed generators (NDGs) comprising photovoltaic arrays (PVs) and wind turbines (WTs), many technical issues have become increasingly prominent in the islanding operation of active distribution networks (ADNs). Such problems including branch overloading and voltage violations threaten the secure operation of distribution systems and a continuous power supply. To address the uncertainties of NDG outputs when implementing islanding partition strategies, this paper proposes a new method of the islanding partition of ADNs based on chance-constrained programming. First, power generation scenarios and probability distributions for these scenarios are generated according to historical data considering the time series characteristics and uncertainties of NDGs. Then, the chance-constrained description of islanding operation is expanded to consider the effect of uncertainties related to NDGs. Moreover, an islanding partition model of ADNs based on chance-constrained programming is established. By applying convex relaxation and introducing auxiliary variables, the model is converted to a mixed-integer quadratically constrained programming model that can be effectively solved. Finally, case studies involving the modified IEEE 33-node system, IEEE 123-node system and an actual distribution system are conducted to verify the effectiveness and scalability of the proposed method. Relationship between restored loads and chance level at different fault time. [Display omitted] •The uncertainties of islanding operation in ADNs were modelled.•A chance-constrained programming based model was built for islanding partition.•The effects of the chance level on the islanding partition strategies were explored. With the high integration of uncontrollable distributed generators (NDGs) comprising photovoltaic arrays (PVs) and wind turbines (WTs), many technical issues have become increasingly prominent in the islanding operation of active distribution networks (ADNs). Such problems including branch overloading and voltage violations threaten the secure operation of distribution systems and a continuous power supply. To address the uncertainties of NDG outputs when implementing islanding partition strategies, this paper proposes a new method of the islanding partition of ADNs based on chance-constrained programming. First, power generation scenarios and probability distributions for these scenarios are generated according to historical data considering the time series characteristics and uncertainties of NDGs. Then, the chance-constrained description of islanding operation is expanded to consider the effect of uncertainties related to NDGs. Moreover, an islanding partition model of ADNs based on chance-constrained programming is established. By applying convex relaxation and introducing auxiliary variables, the model is converted to a mixed-integer quadratically constrained programming model that can be effectively solved. Finally, case studies involving the modified IEEE 33-node system, IEEE 123-node system and an actual distribution system are conducted to verify the effectiveness and scalability of the proposed method. |
| Author | Zhao, Jinli Ji, Haoran Wang, Chengshan Zhang, Mengzhen Li, Peng Yu, Hao Song, Guanyu Wu, Jianzhong |
| Author_xml | – sequence: 1 givenname: Jinli surname: Zhao fullname: Zhao, Jinli organization: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China – sequence: 2 givenname: Mengzhen surname: Zhang fullname: Zhang, Mengzhen organization: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China – sequence: 3 givenname: Hao surname: Yu fullname: Yu, Hao email: tjuyh@tju.edu.cn organization: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China – sequence: 4 givenname: Haoran surname: Ji fullname: Ji, Haoran organization: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China – sequence: 5 givenname: Guanyu surname: Song fullname: Song, Guanyu organization: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China – sequence: 6 givenname: Peng orcidid: 0000-0003-4496-439X surname: Li fullname: Li, Peng organization: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China – sequence: 7 givenname: Chengshan surname: Wang fullname: Wang, Chengshan organization: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China – sequence: 8 givenname: Jianzhong surname: Wu fullname: Wu, Jianzhong organization: Institute of Energy, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK |
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| Keywords | Chance constrained Islanding partition Uncertainty Active distribution network Mixed-integer quadratically constrained programming |
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•The uncertainties of islanding operation in ADNs were... With the high integration of uncontrollable distributed generators (NDGs) comprising photovoltaic arrays (PVs) and wind turbines (WTs), many technical issues... |
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| Title | An islanding partition method of active distribution networks based on chance-constrained programming |
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