中国科技核心期刊
(中国科技论文统计源期刊)
  Scopus收录期刊

石油科学通报 ›› 2026, Vol. 11 ›› Issue (5): 1469-1479. doi: 10.3969/j.issn.2096-1693.2026.02.038

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质能网智能调控范式与关键技术

宫敬1,*(), 魏生远1, 杨毅2, 刁洪涛2, 陆洋帆1, 金凤1, 虞维超2, 温凯1   

  1. 1 中国石油大学(北京)石油工程学院/油气管道输送安全国家工程研究中心/城市燃气输配技术北京市重点实验室/石油工程教育部重点实验室, 北京 102249
    2 国家管网集团油气调控中心, 北京 100013
  • 收稿日期:2026-03-30 修回日期:2026-04-15 出版日期:2026-10-15 发布日期:2026-10-31
  • 通讯作者: *宫敬(1962年—),二级教授,博导,主要从事多相流与流动安全保障理论、油气管道仿真与输送技术、油气储运系统数字化与智能化等方向研究,ydgj@cup.edu.cn。

Paradigm and key technologies for intelligent dispatch and control of substance-energy network

GONG Jing1,*(), WEI Shengyuan1, YANG Yi2, DIAO Hongtao2, LU Yangfan1, JIN Feng1, YU Weichao2, WEN Kai1   

  1. 1 College of Petroleum Engineering/National Engineering Research Center for Pipeline Safety/Beijing Key Laboratory of Urban Oil and Gas Distribution Technology/MOE Key Laboratory of Petroleum Engineering, China University of Petroleum, Beijing 102249, China
    2 PipeChina Oil & Gas Control Center, Beijing 100013, China
  • Received:2026-03-30 Revised:2026-04-15 Online:2026-10-15 Published:2026-10-31
  • Contact: *ydgj@cup.edu.cn。

摘要:

在新型能源体系加快构建和多能源深度耦合发展的背景下,传统面向单一载体、单一网络的调控模式已难以适应质能网多能多网协同运行需求。为此,本文围绕质能网多能流强耦合、多时间尺度动态演化及源荷双侧强不确定性等特征,系统研究了质能网智能调控范式与关键技术。首先,提出了面向质能网的一体化调控系统框架,由基础设施层、感知通信层、预测评估层、协同决策层以及执行控制层5个层次构成,反映其由物理设施到数字映射、由状态认知到协同决策、由控制执行到反馈演进的整体逻辑;其次,凝练了实时监控预警与应急保障、全局协同调控与绿色能源优化配置、全链条计量配送3大基础模块,形成覆盖感知、决策与评估的调控闭环,目标为构建全域感知预警体系,在极端情景下维持关键供能并推动系统快速恢复,在常规工况下实现多网络、多区域、多载体协同运行,促进绿色能源在更大范围内实现高效配置、协同消纳,以及在物理流动与价值结算之间建立清晰、可追溯的对应关系,支撑质能网实现精细化运营、市场化交易与低碳化治理。在此基础上,构建了以资源与需求预测、状态感知与估计、统一链路仿真建模、调度决策与主动控制为主线的闭环技术链路,并总结了各环节支撑质能网智能化与智慧化升级的关键技术,旨在为质能网一体化调控体系构建及相关关键技术研发提供方向参考。

关键词: 质能网, 智能调控, 协同运行, 供需平衡, 绿色能源

Abstract:

Against the backdrop of the accelerated development of the new energy system and the deepening integration of multiple energy sources, traditional dispatch and control modes oriented toward a single carrier and a single network can no longer meet the coordinated operational requirements of the substance-energy network. To address this challenge, this study systematically investigates the paradigm and key technologies of intelligent dispatch and control for the substance-energy network, focusing on the strong coupling among multiple energy and material flows, the dynamic evolution across multiple time scales, and the pronounced uncertainties on both the supply side and the demand side. First, an integrated dispatch and control framework for the substance-energy network is proposed. The framework consists of five layers, namely the resources and infrastructure layer, the sensing and communication layer, the prediction-evaluation layer, the coordinated decision-making layer, and the feedback-evolution layer. This framework reflects the overall logic from physical foundation to digital mapping, from state cognition to coordinated decision-making, and from control execution to feedback evolution, thereby forming a unified architecture for the coordinated perception, analysis, decision-making and regulation of multi-network integrated systems. Second, three fundamental modules are identified and refined, including real-time monitoring, early warning and emergency support; global coordinated dispatch and control and optimal allocation of green energy; and a full-chain metering and delivery system. These modules together form a closed-loop dispatch and control framework covering perception, decision-making and evaluation. The objectives are to establish a system-wide perception and early warning framework, maintain critical energy supply and support rapid recovery under extreme scenarios, realize coordinated operation across multiple networks, regions and carriers under normal conditions, promote the efficient allocation and coordinated accommodation of green energy on a wider scale, and build a clear and traceable correspondence between physical flows and value settlement, thereby supporting refined operation, market-oriented trading and low-carbon governance of the substance-energy network. On this basis, a closed-loop technical chain is further constructed, consisting of resource and demand forecasting, state perception and estimation, unified-chain simulation and modeling, and dispatch decision-making and active control. The corresponding key technologies of each link are further summarized, including forecasting methods under multiple uncertainties, multimodal sensing and state estimation, unified modeling and simulation of coupled energy-material processes, and coordinated dispatch and active control under complex operating conditions. This study aims to provide a reference for the construction of the integrated dispatch and control system and the development of related key technologies for the substance-energy network.

Key words: substance-energy network, intelligent dispatch and control, coordinated operation, supply-demand balance, green energy

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