arXiv:2504.07131cs.AIstat.ML2025-04

用决策树将可靠性约束嵌入发电规划,提升系统稳定性。

Embedding Reliability Verification Constraints into Generation Expansion Planning

  • 用加权斜决策树学习可靠运行区域
  • 生成可融入规划模型的线性约束,支持长期最优决策
  • 适用于电力系统规划者,解决可靠性与经济性冲突

发电规划面临随机生产模拟与优化模型间数学结构不兼容的问题,制约了可靠性约束的集成。本文提出一种将可靠性验证约束嵌入发电扩容规划的方法,利用加权斜决策树(WODT)技术构建模型。针对每一年的规划周期,基于可靠性评估模拟生成带标签的发电组合数据集,并训练WODT模型。通过深度优先搜索提取可靠可行区域,并以析取约束形式表达。随后采用凸包建模技术将其转化为混合整数线性形式,嵌入考虑机组组合的发电扩容规划模型中。在德州电力可靠性理事会(ERCOT)长期规划案例中验证了该方法的有效性,实现了可靠且最优的规划方案。

原文摘要 · Abstract (English)

Generation planning approaches face challenges in managing the incompatible mathematical structures between stochastic production simulations for reliability assessment and optimization models for generation planning, which hinders the integration of reliability constraints. This study proposes an approach to embedding reliability verification constraints into generation expansion planning by leveraging a weighted oblique decision tree (WODT) technique. For each planning year, a generation mix dataset, labeled with reliability assessment simulations, is generated. An WODT model is trained using this dataset. Reliability-feasible regions are extracted via depth-first search technique and formulated as disjunctive constraints. These constraints are then transformed into mixed-integer linear form using a convex hull modeling technique and embedded into a unit commitment-integrated generation expansion planning model. The proposed approach is validated through a long-term generation planning case study for the Electric Reliability Council of Texas (ERCOT) region, demonstrating its effectiveness in achieving reliable and optimal planning solutions.

发电规划可靠性决策树优化建模

Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。