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当前位置：工程学研究 > 2026年 5卷 (3)期

Open Access Article

Journal of Engineering Research. 2026; 5: (3) ; 61-68 ; DOI: 10.12208/j.jer.20260052.

Integrated research on smart energy management technology for public space buildings based on digital twin and artificial intelligence
基于数字孪生与人工智能的公共空间建筑能源智慧化管理技术集成研究

作者： 张桂平¹ *, 秦俊非¹, 连进¹, 梁军平², 梁冉²

1中铁建电气化局集团第一工程有限公司河南洛阳

2清华大学北京

*通讯作者：张桂平,单位：中铁建电气化局集团第一工程有限公司河南洛阳；

发布时间: 2026-07-21 总浏览量: 5 下载量: 加载中...

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摘要

大型公共空间建筑既要满足特异化功能要求，又承担公共服务职能，其能源管理面临客流波动明显、功能分区用能差异较大以及运行安全约束复杂等问题。研究通过文献梳理与问题归纳，分析传统能源管理及数字孪生、人工智能的应用基础，并围绕功能需求、数据感知、智能研判和执行权限进行技术要素集成。在“特异化功能优先、服务体验适配、能耗精准调控”的目标下，构建由功能导向数字化建模与编码、运行与能耗全域实时感知、运行约束下分层智能研判、分级柔性协同调控组成的闭环能源智慧化管理技术路线，并通过分级权限机制协调功能运行安全、公众舒适度与节能需求。该技术路线为大型公共空间建筑由“供给侧保障”向“需求侧驱动”的能源管理转变提供了系统化思路，也为后续开展案例验证与参数优化提供了技术基础。

关键词： 大型公共空间建筑；数字孪生；人工智能；能源智慧化管理；需求侧驱动

Abstract

Large-scale public space buildings must meet specialized functional requirements while fulfilling public service roles; consequently, their energy management faces challenges such as significant fluctuations in foot traffic, varying energy consumption across functional zones, and complex operational safety constraints. Through a review of existing literature and a summary of key issues, this study analyzes traditional energy management alongside the foundational applications of digital twins and artificial intelligence. It integrates technical elements—specifically functional requirements, data sensing, intelligent analysis, and execution authority. Guided by the objectives of prioritizing specialized functions, adapting to public service experience requirements, and achieving precise energy consumption control, the study establishes a closed-loop smart energy management technical framework. This framework comprises function-oriented digital modeling and coding, comprehensive real-time sensing of operations and energy consumption, hierarchical intelligent analysis under operational constraints, and tiered, flexible, collaborative control. A hierarchical authority mechanism is employed to balance functional operational safety, public comfort, and energy-saving requirements. This technical framework offers a systematic approach for transitioning large-scale public space buildings from “supply-side assurance” to “demand-side driven” energy management, while also providing a technical foundation for subsequent case studies and parameter optimization.

Key words： Large-scale public space buildings; Digital twin; Artificial intelligence; Smart energy management; Demand-side driven

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引用本文

张桂平, 秦俊非, 连进, 梁军平, 梁冉, 基于数字孪生与人工智能的公共空间建筑能源智慧化管理技术集成研究[J]. 工程学研究, 2026; 5: (3) : 61-68.

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