广东省数字电网技术企业重点实验室(南方电网数字电网研究院),广东省,广州市,510663
纸质出版:2026
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徐全, 1, 马溪原, 等. 数字电网先进控制技术综述与展望[J]. 电网技术, 2026,50(3):1184-1210.
XU Quan, 1, MA Xiyuan, et al. Review and Prospect of Advanced Control Technologies for Digital Power Grid[J]. 2026, 50(3): 1184-1210.
徐全, 1, 马溪原, 等. 数字电网先进控制技术综述与展望[J]. 电网技术, 2026,50(3):1184-1210. DOI: 10.13335/j.1000-3673.pst.2025.1416.
XU Quan, 1, MA Xiyuan, et al. Review and Prospect of Advanced Control Technologies for Digital Power Grid[J]. 2026, 50(3): 1184-1210. DOI: 10.13335/j.1000-3673.pst.2025.1416.
随着“双碳”战略深入推进,新能源高比例接入引发电网惯量支撑弱化、动态特性复杂化、源荷双侧强随机性等系统性挑战,传统控制方法在应对这些新挑战时,逐渐显现出响应速度、适应性与协同能力等方面的不足。数字电网作为新型电力系统的核心支撑,其多层级协同控制架构为破解上述难题提供了关键路径,而先进控制技术作为其核心中枢,其理论创新已成为保障新型电力系统安全稳定运行的刚性需求。聚焦数字电网中新能源充分消纳和电网安全稳定运行两大核心挑战,系统综述先进控制技术研究进展与应用:针对新型电力系统强非线性动态特性与海量异构设备协同难题,先进控制技术在突破传统控制响应迟滞与适应性瓶颈方面展现出核心价值,其通过模型驱动或数据驱动范式,可有效提升系统控制精度,但仍面临复杂场景泛化性不足、多目标优化冲突等共性问题。为满足全域资源协同响应与毫秒级决策需求,研究提出了“云-边-端-芯”分层控制架构,云侧稳控依托全局态势感知实现毫秒级安全边界决策;边侧群控通过分布式资源动态聚合显著提升响应效率;端侧数控保障分布式能源的精准电压频率支撑;芯侧智控则以微型化AI芯片突破嵌入式设备的算力瓶颈。最后结合技术瓶颈与发展趋势,提出分级协同控制的未来发展路径,着力构建数字电网“云-边-端-芯”四层级闭环控制,构建支撑高韧性、低碳化数字电网的分层优化体系。
With the in-depth advancement of the "dual carbon" strategy
the high proportion of new energy integration into the power grid has brought about systemic challenges such as weakened inertia support
complex dynamic characteristics
and strong randomness on both the supply and demand sides. Traditional control methods have fundamental limitations in response speed
adaptability
and coordination. As the core support of the new power system
the digital power grid's multi-level coordinated control architecture provides a key path to address these challenges. Advanced control technology
as the core hub
has become a fundamental requirement for ensuring the safe and stable operation of the new power system. This paper focuses on two core challenges in the digital power grid: the full integration of new energy and the maintenance of power grid security and stability. It systematically reviews the research progress and applications of advanced control technology. In response to the strong nonlinear dynamic characteristics and coordination difficulties of massive heterogeneous devices in the new power system
advanced control technology has demonstrated significant value in overcoming the response lag and adaptability bottlenecks of traditional control. Using model- or data-driven paradigms can effectively improve system control accuracy
but it still faces common problems
such as insufficient generalization in complex scenarios and conflicts in multi-objective optimization. To meet the requirements of global resource collaborative response and millisecond-level decision-making
a "cloud-edge-device-chip" hierarchical control architecture has been proposed. The cloud-side stability control achieves millisecond-level safety boundary decision-making based on global situation awareness; the edge-side group control significantly improves response efficiency through dynamic aggregation of distributed resources; the device-side numerical control ensures precise voltage and frequency support for distributed energy; and the chip-side intelligent control breaks through the computing power bottleneck of embedded devices with miniaturized AI chips. Finally
based on technical bottlenecks and development trends
a future development path for hierarchical coordinated control is proposed
focusing on building a four-level closed-loop control system of "cloud-edge-device-chip" in the digital power grid and establishing a hierarchical optimization system to support a high-resilience
low-carbon digital power grid.
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