中国电力 ›› 2025, Vol. 58 ›› Issue (4): 21-30, 192.DOI: 10.11930/j.issn.1004-9649.202409069

• 电-碳协同下分布式能源系统运营关键技术 • 上一篇    下一篇

考虑不确定性和绿证交易的虚拟电厂与配电网分布式优化

汪进锋1,2(), 李金鹏2(), 许银亮2(), 刘海涛3(), 何锦雄3, 许建远3   

  1. 1. 广东电网有限责任公司电力科学研究院,广东 广州 510080
    2. 清华大学 深圳国际研究生院,广东 深圳 518000
    3. 广东电网有限责任公司茂名供电局,广东 茂名 525000
  • 收稿日期:2024-09-18 录用日期:2024-12-17 发布日期:2025-04-23 出版日期:2025-04-28
  • 作者简介:
    汪进锋(1985),男,博士研究生,从事新型电力系统与配电技术研究,E-mail:stare0405@163.com
    李金鹏(2000),男,通信作者,硕士研究生,从事电力系统分析研究,E-mail:lijp23@mails.tsinghua.edu.cn
    许银亮(1983),男,博士,副教授,博士生导师,从事电力系统分析、虚拟电厂、低碳能源系统研究,E-mail:xu.yinliang@sz.tsinghua.edu.cn
    刘海涛(1981),男,高级工程师,从事电网规划研究,E-mail:52433252@qq.com
  • 基金资助:
    中国南方电网有限责任公司科技项目(030900KC23120011,GDKJXM20231514)。

Distributed Optimization for VPP and Distribution Network Operation Considering Uncertainty and Green Certificate Market

WANG Jinfeng1,2(), LI Jinpeng2(), XU Yinliang2(), LIU Haitao3(), HE Jinxiong3, XU Jianyuan3   

  1. 1. Guangdong Power Grid Co., Ltd. Electric Power Research Institute, Guangzhou 510080, China
    2. Tsinghua Shenzhen International Graduate School, Shenzhen 518000, China
    3. Guangdong Power Grid Co., Ltd. Maoming Power Supply Bureau, Maoming 525000, China
  • Received:2024-09-18 Accepted:2024-12-17 Online:2025-04-23 Published:2025-04-28
  • Supported by:
    This work is supported by Science and Technology Project of CSG (No. 030900KC23120011, No. GDKJXM20231514).

摘要:

为应对日益增长的可再生能源规模带来的不确定性问题,提出一种考虑不确定性的虚拟电厂分布式优化方法。在虚拟电厂侧,采用基于场景的随机优化模型,考虑了光伏、风电出力的随机特性。在配电网侧,考虑从输电网购电的电价不确定性,分别建立了基于信息差距决策理论的两阶段鲁棒优化模型和机会模型,以增强模型对电价变化的鲁棒性或在波动电价中获取潜在的收益。通过自适应的交替方向乘子算法在虚拟电厂与配电网之间分布式地求解模型,以保护双方的隐私。结果表明,所提模型在不确定条件下较鲁棒模型灵活性强,能够更好地平衡风险和效益,分布式算法收敛性能优异,较集中式算法能够更充分利用计算资源。

关键词: 虚拟电厂, 配电网, 可交易绿证市场, 不确定性, 分布式优化

Abstract:

In order to cope with the uncertainties brought by the growing scale of renewable energy, this paper proposed a distributed optimization for virtual power plant (VPP) considering uncertainties. On the VPP side, a scenario-based stochastic optimization model was used to depict the stochastic characteristics of photovoltaic and wind power output. On the distribution network side, considering the uncertainty of electricity prices when purchasing power from the grid, a two-stage robust optimization model and an opportunity model based on information gap decision theory were established to enhance the model's robustness against electricity price fluctuations or to capture potential benefits amidst volatile electricity prices. The problem was solved distributedly between the VPP and the distribution network through the alternating direction multiplier method algorithm to protect their privacy. The results show that the proposed model is more flexible than the robust model and can better balance the risks and benefits under uncertain conditions. The distributed algorithm has a good convergence performance and can better utilize computing resources compared to the centralized algorithm.

Key words: virtual power plant, distribution network, tradable green certificate market, uncertainty, distributed optimization