Distributionally Robust Optimization-Based Decomposition Method for Medium- and Long-Term Contracts of Large-Scale Energy Bases

SUN Tian; WANG Guoyang; LI Yinxiao; FAN Menghua; TANG Chenghui; GUO Hongye

doi:10.11930/j.issn.1004-9649.202504023

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Distributionally Robust Optimization-Based Decomposition Method for Medium- and Long-Term Contracts of Large-Scale Energy Bases

更新时间：2025-12-20

- Distributionally Robust Optimization-Based Decomposition Method for Medium- and Long-Term Contracts of Large-Scale Energy Bases
- Vol. 58, Issue 11, Pages: 38-48(2025)
- 作者机构：
  
  1. 北京电力交易中心有限公司,北京,100031
  2. 新型电力系统运行与控制全国重点实验室（清华大学电机工程与应用电子技术系）,北京,100084
  3. 国网能源研究院有限公司,北京,102209
- 作者简介：
- 基金信息：
- DOI：10.11930/j.issn.1004-9649.202504023
  CLC：
- Published Online：01 December 2025，
  
  Published：01 December 2025
- 稿件说明：
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孙田, 王国阳, 李寅晓, 范孟华, 唐程辉, 郭鸿业. 基于分布鲁棒优化的大型能源基地中长期合同分解方法[J]. 中国电力, 2025, 58(11): 38-48.

SUN Tian, WANG Guoyang, LI Yinxiao, et al. Distributionally Robust Optimization-Based Decomposition Method for Medium- and Long-Term Contracts of Large-Scale Energy Bases[J]. 2025, 58(11): 38-48.
孙田, 王国阳, 李寅晓, 范孟华, 唐程辉, 郭鸿业. 基于分布鲁棒优化的大型能源基地中长期合同分解方法[J]. 中国电力, 2025, 58(11): 38-48. DOI： 10.11930/j.issn.1004-9649.202504023.

SUN Tian, WANG Guoyang, LI Yinxiao, et al. Distributionally Robust Optimization-Based Decomposition Method for Medium- and Long-Term Contracts of Large-Scale Energy Bases[J]. 2025, 58(11): 38-48. DOI： 10.11930/j.issn.1004-9649.202504023.

摘要

随着大型能源基地的逐步建设投产，其配套火电机组的中长期合同电量需要分解到小时级尺度以制定调度计划。针对中长期合同分解与省间送电要求难以协同的问题，提出基于分布鲁棒优化的大型能源基地中长期合同分解方法。首先，在满足标准送电曲线的要求下，以尽可能完成火电合同电量与最小化发电成本为目标成本建立确定性中长期合同分解优化模型。其次，基于由历史样本形成的经验分布与Wasserstein球构建可再生能源出力不确定性的模糊集，并依此建立分布鲁棒优化模型。最后，基于强对偶定理与仿射调整策略将模型转化为混合整数线性规划问题进行求解。算例结果表明所提方法能够有效兼顾决策的激进性与保守性，支撑电力市场环境下大型能源基地的优化调度。

Abstract

With the gradual construction and commissioning of large-scale energy bases

the medium- and long-term contracted energy of their supporting thermal power units needs to be decomposed into hourly scales for dispatching plans. To address the challenge of coordinating the decomposition of contract energy with inter-provincial power transmission requirements

a distributionally robust optimization-based decomposition method for medium- and long-term contracts of large-scale energy bases is proposed. Firstly

a deterministic optimization model for medium- and long-term contract decomposition is developed to maximize thermal power contract fulfillment and minimize generation costs while complying with standard transmission curve requirements. Secondly

a fuzzy set for renewable energy output uncertainty is constructed based on the empirical distribution formed from historical samples and a Wasserstein ball

and accordingly a distributionally robust optimization model is established. Finally

the model is transformed into a mixed-integer linear programming problem based on the strong duality theorem and affine adjustment strategy. The case study results demonstrate that the proposed method effectively balances the aggressiveness and conservatism of decisions

supporting the optimal dispatch of large-scale energy bases in electricity market environment.

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references

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