A Flexibility-oriented robust transmission expansion planning approach under high renewable energy resource penetration
被引:6
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作者:
Yin, Xin
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机构:
South China Univ Technol, Sch Elect Power Engn, Guangzhou 510640, Guangdong, Peoples R ChinaSouth China Univ Technol, Sch Elect Power Engn, Guangzhou 510640, Guangdong, Peoples R China
Yin, Xin
[1
]
Chen, Haoyong
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机构:
South China Univ Technol, Sch Elect Power Engn, Guangzhou 510640, Guangdong, Peoples R ChinaSouth China Univ Technol, Sch Elect Power Engn, Guangzhou 510640, Guangdong, Peoples R China
Chen, Haoyong
[1
]
Liang, Zipeng
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机构:
Hong Kong Polytech Univ, Dept Elect Engn, Hong Kong, Peoples R China
Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore, SingaporeSouth China Univ Technol, Sch Elect Power Engn, Guangzhou 510640, Guangdong, Peoples R China
Liang, Zipeng
[2
,3
]
Zhu, Yanjin
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机构:
South China Univ Technol, Sch Elect Power Engn, Guangzhou 510640, Guangdong, Peoples R ChinaSouth China Univ Technol, Sch Elect Power Engn, Guangzhou 510640, Guangdong, Peoples R China
Zhu, Yanjin
[1
]
机构:
[1] South China Univ Technol, Sch Elect Power Engn, Guangzhou 510640, Guangdong, Peoples R China
[2] Hong Kong Polytech Univ, Dept Elect Engn, Hong Kong, Peoples R China
Transmission flexibility;
Renewable energy sources;
Transmission expansion planning;
Uncertainty;
Variability;
UNIT COMMITMENT MODEL;
OPERATIONAL FLEXIBILITY;
OPTIMIZATION;
IMPACT;
D O I:
10.1016/j.apenergy.2023.121786
中图分类号:
TE [石油、天然气工业];
TK [能源与动力工程];
学科分类号:
0807 ;
0820 ;
摘要:
High penetrations of renewable energy sources incorporated into transmission systems pose a substantial challenge to transmission expansion planning operations due to both the strong uncertainty of these sources and their high variability. However, most current robust transmission expansion planning studies focus exclusively on the issue of uncertainty, and neglect to optimize system flexibility in an effort to cope with the high variability of these sources. The present work addresses this critical issue by proposing a flexibility-oriented robust transmission expansion planning method developed according to the unit commitment characteristics of coal-fired and gas-fired generation units that fully considers the short-term flexibility requirements of electric power systems while maintaining high robustness to the uncertainties of RES outputs in long-term transmission expansion planning problems. The proposed complex model with unit commitment constraints containing massive binary variables is solved by first reducing the number of binary variables via the application of clustering techniques to identify generator units with similar generation properties, and then decreasing the complexity of the model further by relaxing the integer variables in the unit-clustered model. Finally, we develop generalized column-and-constraint generation algorithms that can solve the clustered model and the relaxed simplified model with greatly enhanced efficiency. Comparisons of the numerical results obtained by the proposed approach with existing state-of-the-art methods when applied to a simple Garver 6-node system and a realistically-sized power system demonstrate that the proposed method produces optimal RTEP solutions that account for both the uncertainty and variability of RES outputs. Moreover, the total cost of the proposed approach is 2.22x106$ less than that of the other state-of-the-art methods considered, which is of great significance in guiding practical transmission expansion planning applications.
机构:
Tsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing 100084, Peoples R ChinaTsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing 100084, Peoples R China
Zhuo, Zhenyu
Du, Ershun
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机构:
Tsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing 100084, Peoples R ChinaTsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing 100084, Peoples R China
Du, Ershun
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机构:
Zhang, Ning
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机构:
Kang, Chongqing
Xia, Qing
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机构:
Tsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing 100084, Peoples R ChinaTsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing 100084, Peoples R China
Xia, Qing
Wang, Zhidong
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机构:
State Grid Econ & Technol Res Inst Co Ltd, Beijing 102209, Peoples R ChinaTsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing 100084, Peoples R China
机构:
Shanghai Jiao Tong Univ, Minist Educ, Key Lab Control Power Transmiss & Convers, Shanghai, Peoples R ChinaShanghai Jiao Tong Univ, Minist Educ, Key Lab Control Power Transmiss & Convers, Shanghai, Peoples R China
Hu, Jingwei
Xu, Xiaoyuan
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机构:
Shanghai Jiao Tong Univ, Minist Educ, Key Lab Control Power Transmiss & Convers, Shanghai, Peoples R ChinaShanghai Jiao Tong Univ, Minist Educ, Key Lab Control Power Transmiss & Convers, Shanghai, Peoples R China
Xu, Xiaoyuan
Ma, Hongyan
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机构:
Donghua Univ, Shanghai 201620, Peoples R ChinaShanghai Jiao Tong Univ, Minist Educ, Key Lab Control Power Transmiss & Convers, Shanghai, Peoples R China
Ma, Hongyan
Yan, Zheng
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机构:
Shanghai Jiao Tong Univ, Minist Educ, Key Lab Control Power Transmiss & Convers, Shanghai, Peoples R ChinaShanghai Jiao Tong Univ, Minist Educ, Key Lab Control Power Transmiss & Convers, Shanghai, Peoples R China