Distributionally Robust Planning Method for Power Generation and Transmission Considering Multi-Energy Complementarity and Direct Current Transmission

doi:10.16183/j.cnki.jsjtu.2024.252

Abstract

Abstract:

The large-scale integration of highly uncertain renewable energy poses significant challenges to the planning and operation of power systems. To address the joint generation and transmission planning problem in renewable-dominated power systems, this paper proposes a distributionally robust planning method considering multi-energy complementarity and direct current (DC) transmission. First, with the objective of minimizing total annual planning costs, a joint generation-transmission planning model incorporating wind-storage complementarity and adjustable DC transmission is established. Then, considering the high uncertainty of wind power output, an improved generative adversarial network is adopted to construct typical planning scenarios. On this basis, a two-stage distributionally robust generation-transmission planning model based on probabilistic scenario fuzzy sets is constructed and solved using a parallelizable column-and-constraint generation algorithm that requires no dual formulation. Finally, case studies on a modified Graver-6 node system verify that the proposed method yields a planning scheme that balances improved economic performance with controllable conservativeness.

Key words: multi-energy complementarity, direct current (DC) transmission, generation and transmission planning, distributionally robust optimization (DRO), generative adversarial network

CLC Number:

TM743

HE Yangyang, ZHANG Chengming, WANG Haoyu, LI Yong, FAN Cheng, TAI Nengling. Distributionally Robust Planning Method for Power Generation and Transmission Considering Multi-Energy Complementarity and Direct Current Transmission[J]. Journal of Shanghai Jiao Tong University, 2026, 60(6): 915-924.

Figures/Tables 9

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References 21

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规划方法	投建机组			投建线路(数量)	费用/亿美元
规划方法	节点	容量/MW	数量	投建线路(数量)	年投资费用	弃风惩罚费用	运行费用	年综合费用
1	2 6	60 240,120	2 2,1	2-6(3),3-6(2), 4-6(3),3-5(1)	0.6142	0.0082	0.6711	1.2853
2	6	240	2	2-6(3),4-6(2), 3-5(1),3-6(1)	0.4587	0.0001	0.5154	0.9741
3	6	240	2	2-6(3),4-6(2), 3-5(1),3-6(1)	0.4587	0	0.4624	0.9211
4	2 6	60 240	2 2	2-6(3),3-6(2), 4-6(1),3-5(1)	0.4972	0.0092	0.4923	0.9895
5	2 6	60 240	2 2	2-6(3),3-6(1), 4-6(1),3-5(1)	0.4955	0	0.4637	0.9592

优化方法	投建机组			投建线路(数量)	费用/亿美元
优化方法	节点	容量/MW	数量	投建线路(数量)	年投资费用	运行费用	年综合费用
SO	6	240	2	2-6(3),4-6(2), 3-5(1),3-6(1)	0.4587	0.4869	0.9456
RO	2 6	60 240,120	2 2,1	2-6(3),3-6(3), 4-6(3),3-5(1)	0.6202	0.4472	1.0674
DRO	2 6	60 240	2 2	2-6(3),3-6(1), 4-6(1),3-5(1)	0.4955	0.4637	0.9592

γ_∞	年综合费用/亿美元
γ_∞	考虑综合范数约束	仅考虑1-范数约束
0.5	0.9169	1.0215
0.8	0.9378	1.0215
0.9	0.9541	1.0215
0.99	0.9586	1.0215

γ₁	年综合费用/亿美元
γ₁	考虑综合范数约束	仅考虑∞-范数约束
0.5	0.9188	0.9592
0.8	0.9276	0.9592
0.9	0.9541	0.9592
0.99	0.9592	0.9592

历史场景数	年综合费用/ 亿美元	历史场景数	年综合费用/ 亿美元
100	1.0155	1000	0.9592
500	0.9851	5000	0.9488