电力系统保护与控制2025，Vol.53Issue(4)：148-164,17.DOI:10.19783/j.cnki.pspc.240322
考虑源荷多重不确定性的园区综合能源系统优化策略
A PIES optimization strategy considering multiple uncertainties in source and load
摘要
Abstract
Reducing source-load uncertainty while balancing economic efficiency and low carbon emissions has become the focus of optimizing the scheduling of park-level integrated energy systems(PIES).To this end,an integrated framework of prediction,regulation,and decision-making is proposed.Firstly,a PIES incorporating combined heat and power(CHP),power to gas(P2G),and carbon capture and storage(CCS)is constructed.Secondly,a data prediction method based on the rime algorithm optimized convolutional neural network-support vector machine(RIME-CNN-SVM)is proposed,and the information gap decision theory(IGDT)is used to account for severe source-load uncertainties with unknown probability distribution.Finally,a low-carbon optimization scheduling strategy for PIES is established,considering source-load uncertainties,a tiered carbon trading mechanism,and penalties for abandoning wind and solar power.Through numerical analysis,the rationality and effectiveness of the proposed model are verified,demonstrating that the proposed method improves the accuracy of PIES scheduling while balancing economic efficiency and low-carbon emissions.关键词
RIME-CNN-SVM/IGDT/阶梯式碳交易/电转气与碳捕集/PIESKey words
RIME-CNN-SVM/IGDT/stepped carbon trading/P2G and CCS/PIES引用本文复制引用
赵琛,叶金池,和萍,李秋燕,王世谦..考虑源荷多重不确定性的园区综合能源系统优化策略[J].电力系统保护与控制,2025,53(4):148-164,17.基金项目
This work is supported by the National Natural Science Foundation of China(No.62203401). 国家自然科学基金项目资助(62203401) （No.62203401）
河南省科技攻关研究项目资助(232102241043) （232102241043）
