Reliability-Constrained AC Power Flow-Based Co-Optimization Planning of Generation and Transmission Systems With Uncertainties
As the penetration of renewable energy continues to grow, power system expansion planning needs new techniques to balance the cost to achieve high renewable targets while maintaining a certain level of flexibility and reliability in the presence of uncertainties. Firstly, this paper presents a long-...
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| Format: | Article |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9233331/ |
| _version_ | 1818917725193371648 |
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| author | Zongchuan Zhou Chuan He Tianqi Liu Xiaojing Dong Kun Zhang Dongsheng Dang Baorui Chen |
| author_facet | Zongchuan Zhou Chuan He Tianqi Liu Xiaojing Dong Kun Zhang Dongsheng Dang Baorui Chen |
| author_sort | Zongchuan Zhou |
| collection | DOAJ |
| description | As the penetration of renewable energy continues to grow, power system expansion planning needs new techniques to balance the cost to achieve high renewable targets while maintaining a certain level of flexibility and reliability in the presence of uncertainties. Firstly, this paper presents a long-term stochastic co-optimization planning model, for minimizing the total investment cost and operation cost. A linearized AC power flow model which could accurately retain bus voltages, reactive power and network losses is implemented to better accommodate renewable generation. Besides generating units and transmission lines, capacitor banks and static Var compensators are included as reactive compensation equipment. Furthermore, the proposed model also includes probabilistic reliability criterion LOLE, which is incorporated as constraints to derive reliable and economic co-planning decisions. Then the proposed model is reformulated as a mixed-integer second order cone programming problem which could be readily solved by off-the-shelf commercial solvers. Finally, numerical case studies illustrate the effectiveness of the proposed reliability-constrained co-optimization planning approach considering uncertainties. |
| first_indexed | 2024-12-20T00:38:38Z |
| format | Article |
| id | doaj.art-20614f2b62514b74b837ad05d5006384 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-20T00:38:38Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-20614f2b62514b74b837ad05d50063842022-12-21T19:59:41ZengIEEEIEEE Access2169-35362020-01-01819421819422710.1109/ACCESS.2020.30325609233331Reliability-Constrained AC Power Flow-Based Co-Optimization Planning of Generation and Transmission Systems With UncertaintiesZongchuan Zhou0Chuan He1https://orcid.org/0000-0002-8978-2410Tianqi Liu2Xiaojing Dong3Kun Zhang4Dongsheng Dang5Baorui Chen6Economic and Technological Research Institute, State Grid Ningxia Electric Power Company Ltd., Yinchuan, ChinaCollege of Electrical Engineering, Sichuan University, Chengdu, ChinaCollege of Electrical Engineering, Sichuan University, Chengdu, ChinaEconomic and Technological Research Institute, State Grid Ningxia Electric Power Company Ltd., Yinchuan, ChinaEconomic and Technological Research Institute, State Grid Ningxia Electric Power Company Ltd., Yinchuan, ChinaEconomic and Technological Research Institute, State Grid Ningxia Electric Power Company Ltd., Yinchuan, ChinaCollege of Electrical Engineering, Sichuan University, Chengdu, ChinaAs the penetration of renewable energy continues to grow, power system expansion planning needs new techniques to balance the cost to achieve high renewable targets while maintaining a certain level of flexibility and reliability in the presence of uncertainties. Firstly, this paper presents a long-term stochastic co-optimization planning model, for minimizing the total investment cost and operation cost. A linearized AC power flow model which could accurately retain bus voltages, reactive power and network losses is implemented to better accommodate renewable generation. Besides generating units and transmission lines, capacitor banks and static Var compensators are included as reactive compensation equipment. Furthermore, the proposed model also includes probabilistic reliability criterion LOLE, which is incorporated as constraints to derive reliable and economic co-planning decisions. Then the proposed model is reformulated as a mixed-integer second order cone programming problem which could be readily solved by off-the-shelf commercial solvers. Finally, numerical case studies illustrate the effectiveness of the proposed reliability-constrained co-optimization planning approach considering uncertainties.https://ieeexplore.ieee.org/document/9233331/Co-optimization planningreliabilityuncertaintiesAC power flowstochastic optimization |
| spellingShingle | Zongchuan Zhou Chuan He Tianqi Liu Xiaojing Dong Kun Zhang Dongsheng Dang Baorui Chen Reliability-Constrained AC Power Flow-Based Co-Optimization Planning of Generation and Transmission Systems With Uncertainties IEEE Access Co-optimization planning reliability uncertainties AC power flow stochastic optimization |
| title | Reliability-Constrained AC Power Flow-Based Co-Optimization Planning of Generation and Transmission Systems With Uncertainties |
| title_full | Reliability-Constrained AC Power Flow-Based Co-Optimization Planning of Generation and Transmission Systems With Uncertainties |
| title_fullStr | Reliability-Constrained AC Power Flow-Based Co-Optimization Planning of Generation and Transmission Systems With Uncertainties |
| title_full_unstemmed | Reliability-Constrained AC Power Flow-Based Co-Optimization Planning of Generation and Transmission Systems With Uncertainties |
| title_short | Reliability-Constrained AC Power Flow-Based Co-Optimization Planning of Generation and Transmission Systems With Uncertainties |
| title_sort | reliability constrained ac power flow based co optimization planning of generation and transmission systems with uncertainties |
| topic | Co-optimization planning reliability uncertainties AC power flow stochastic optimization |
| url | https://ieeexplore.ieee.org/document/9233331/ |
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