上海交通大学学报

上海交通大学学报

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考虑多能互补和直流外送的发输电分布鲁棒规划方法

贺杨烊1，张程铭2，王浩宇3，李勇4，范程4，邰能灵1   

  1. （1. 上海交通大学 智慧能源创新学院，上海 200240；2. 国网浙江省电力有限公司电力科学研究院，杭州 310000；3. 国家电网有限公司华东分部，上海 200120；4. 新疆丝路坤元能源有限责任公司乌鲁木齐 830000
  • 出版日期:2025-06-25 发布日期:2025-06-25
  • 作者简介:贺杨烊（1993—），助理研究员，从事直流输电系统研究。

Distributionally Robust Planning Method of Power Generation and Transmission Considering Multi-Energy Complementary and Direct Current Transmission#br#

HE Yangyang1，ZHANG Chengming2，WANG Haoyu3，LI Yong4，FAN Cheng4，TAI Nengling1   

  1. 1. College of Smart Energy, Shanghai Jiao Tong University, Shanghai 200240, China；2. State Grid Zhejiang Electric Power Research Institute, Hangzhou 310000, China；3. East China Branch of State Grid Corporation of China, Shanghai 200120, China；4. Xinjiang Silu Kunyuan Energy Co., Ltd., Urumqi 830000, China
  • Online:2025-06-25 Published:2025-06-25

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摘要： 具有强不确定性的新能源大规模并网给电力系统的规划与运行带来极大挑战。针对新能源电力系统的发输电联合规划问题，该文提出一种考虑多能互补和直流外送的发输电分布鲁棒规划方法。首先，以最小化年规划综合费用为目标，建立考虑风蓄互补和直流外送功率可调的发输电联合规划模型。然后，考虑风电出力的强不确定性，采用改进的生成对抗网络构造典型规划场景，并在此基础上建立了基于概率场景模糊集的发输电两阶段分布鲁棒规划模型，并采用一种无需对偶且可并行计算的列与约束生成算法求解。最后，基于修改的Garver-6 节点系统进行算例分析，验证了所提分布鲁棒规划方法能够形成兼顾经济性提升和保守性可控的发输电联合规划方案。

关键词: 多能互补, 直流外送, 发输电规划, 分布鲁棒优化, 生成对抗网络

Abstract: The large-scale integration of new energy resource with strong uncertainty brings great challenges to the planning and operation of power systems. In this paper, a distributionally robust planning method of generation and transmission considering the multi-energy complementarity and DC transmission optimization is proposed. Firstly, considering wind-pumped storage complementarity and DC transmission power adjustment, a joint planning
model of generation and transmission is established with the objective of minimizing the annual comprehensive planning cost. On this basis, considering the strong uncertainty of wind power output, a two-stage distributionally robust planning model of generation and transmission based on probability scenario ambiguity sets is constructedand and solved by a parallel computable column-and-constraint generation algorithm. A modified generative adversarial network is adopted to generate typical planning scenarios. Finally, simulation with Graver-6 node system verifies that the proposed planning method can form a planning scheme that balances economic improvement and conservative control.

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

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