用于降低区域供热网络峰值负荷和返回温度的智能控制器的测试和评估

IF 5.4 Q2 ENERGY & FUELS
Tijs Van Oevelen , Thomas Neven , Aurélien Brès , Ralf-Roman Schmidt , Dirk Vanhoudt
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引用次数: 1

摘要

TEMPO项目开发了一种智能需求响应控制系统,旨在实时优化区域供暖(DH)网络的回水管和供水管的温度水平。返回温度主要取决于需求侧。控制器通过控制客户的热负荷来优化其值。然而,网络供应温度在生产侧是可直接控制的。供应温度控制的能力是双重的。一方面,将网络供电温度降低到尽可能接近客户热需求确定的极限。另一方面,激活管道的固有热容量以临时储存热量,从而及时转移热负荷。这为建筑需求响应提供了额外的能源灵活性潜力。在本研究中,智能控制系统的两个功能已在布雷西亚(意大利)DH网络的一部分中进行了测试。基于云的平台用于收集来自各种来源的实时数据,并传达由智能控制器计算的控制信号。本文介绍了控制器的测试结果和性能评估。分析表明,日流量加权平均回流温度平均可降低近1K,瞬时可降低高达15K。使用供应温度控制,通过改变热负荷,日峰值负荷能源供应可以平均减少262kWh(34%)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Testing and evaluation of a smart controller for reducing peak loads and return temperatures in district heating networks

Testing and evaluation of a smart controller for reducing peak loads and return temperatures in district heating networks

A smart demand response control system aiming towards real-time operational optimisation of district heating (DH) network temperature levels, both in the return and supply pipes, has been developed in the TEMPO project. The return temperature is mainly dependent on the demand side. The controller optimises its value through control of the customers’ heat load. The network supply temperature, however, is directly controllable on the production side. The capabilities of supply temperature control are twofold. On the one hand, lowering the network supply temperature as close as possible to the limits determined by customer thermal demands. On the other hand, activating the intrinsic thermal capacity of the piping to temporarily store heat and thereby shifting the heat load in time. This provides additional energy flexibility potential on top of building demand response.

In this study, the two features of the smart control system have been tested in a part of the DH network of Brescia (Italy). A cloud-based platform is used to collect real-time data from various sources and to communicate control signals calculated by the smart controller. The article presents the results of the tests and an evaluation of the controller performance. The analysis indicates that daily flow-weighted average return temperature reductions of almost 1 K on average can be achieved, and up to 15 K instantaneously. Using supply temperature control, the daily peak load energy supply could be reduced by 262 kWh (34%) on average, by shifting the heat load.

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来源期刊
Smart Energy
Smart Energy Engineering-Mechanical Engineering
CiteScore
9.20
自引率
0.00%
发文量
29
审稿时长
73 days
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