基于电力系统动态碳排放因子的建筑低碳运行方法

IF 2.4 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
IET Smart Grid Pub Date : 2022-09-29 DOI:10.1049/stg2.12085
Le Bu, Xingying Chen, Lei Gan, Kun Yu, Yue Zhou, Jiawei Cao, Yuan Cao
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引用次数: 2

摘要

建筑能源的节能减碳是实现全球“碳中和”目标的重要途径。常见的建筑低碳运营策略依靠价格激励来引导用户行为,难以让用户意识到其能耗行为对碳排放的影响。本文利用电力系统的动态碳排放因子(CEF)向建筑用户发布能耗和碳排放信息。同时,在建筑信息模型中考虑了围护结构和外部温度的差异效应。为提高建筑和电力系统的综合减碳能力,建立了兼顾建筑和电力碳排放的建筑低碳能耗战略优化方法。仿真结果表明,该方法有效地协调了建筑物虚拟储能与需求响应。通过将动态能源碳交易成本纳入目标函数,将碳减排的目标信号传递给用户,从而在动态CEF中考虑可再生能源的波动性和其他随机能源行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Low-carbon operation method of the building based on dynamic carbon emission factor of power system

Low-carbon operation method of the building based on dynamic carbon emission factor of power system

Energy conservation and carbon reduction in building energy is an important way to achieve the global goal of ‘carbon neutrality’. Common low-carbon operation strategies of buildings rely on price incentives to guide users’ behaviour, which is difficult to make users aware of the impact of their energy consumption behaviour on carbon emissions. In this paper, the power system's dynamic carbon emission factors (CEF) were used to release information on energy consumption and carbon emission to building users. At the same time, the differential effects of building envelope and external temperature in the Building Information Modelling were considered. An optimisation method of building low-carbon energy consumption strategy considering both the building and power carbon emission was established to improve the comprehensive carbon reduction ability of the building and power system. The simulation results show that the proposed method effectively coordinates the building virtual energy storage and demand response. By incorporating the dynamic energy carbon transaction cost into the objective function, the target signal of carbon reduction is transmitted to users so that the volatility of the renewable Energy and other random energy behaviours can be considered in the dynamic CEF.

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来源期刊
IET Smart Grid
IET Smart Grid Computer Science-Computer Networks and Communications
CiteScore
6.70
自引率
4.30%
发文量
41
审稿时长
29 weeks
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