中国电力2026，Vol.59Issue(2)：1-12,12.DOI:10.11930/j.issn.1004-9649.202511033
考虑发电与碳排放不确定性的园区综合能源系统分布鲁棒优化
Distributionally robust optimization of park-level integrated energy systems considering uncertainties in power generation and carbon emissions
摘要
Abstract
Under the"dual carbon"goals,the park-level integrated energy system(PIES),as an important carrier for achieving multi-energy complementarity and low-carbon transition,has attracted extensive attention.However,its operation is affected by multiple sources of uncertainty,such as wind power output fluctuations and indirect carbon emission intensity of the power grid,which poses challenges to both economic efficiency and carbon performance of the system.To this end,this paper proposes a distributionally robust optimization method for PIES considering the uncertainty of power generation and carbon emissions.A hybrid fuzzy set is constructed based on the Wasserstein distance and moment information,while chance constraints are employed to handle wind power uncertainty.Meanwhile,a polyhedral uncertainty set is used to characterize the fluctuations in carbon emission intensity,and user-side demand response is incorporated to enhance system flexibility.The proposed model is transformed into a solvable mixed-integer linear programming(MILP)problem through the column-and-constraint generation(C&CG)algorithm and Karush-Kuhn-Tucker(KKT)conditions.Case study results demonstrate that the proposed method enhances economic efficiency while ensuring system robustness,and effectively coordinates the relationship between renewable energy accommodation,carbon emission constraints,and economic operation.关键词
园区综合能源系统/分布鲁棒机会约束/碳排放强度不确定性/列和约束生成算法/KKTKey words
park-level integrated energy system/distribu-tionally robust chance constraint/uncertainty of carbon emission intensity/column-and-constraint generation algorithm/KKT引用本文复制引用
张啸林,杜尔顺,张光斗,王佳旭,宋亮,刘昱良..考虑发电与碳排放不确定性的园区综合能源系统分布鲁棒优化[J].中国电力,2026,59(2):1-12,12.基金项目
国家重点研发计划资助项目(2023YFB2407304). This work is supported by National Key Research and Development Program of China(No.2023YFB2407304). （2023YFB2407304）
