2022
DOI: 10.1016/j.enconman.2022.116163
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A study on data-driven hybrid heating load prediction methods in low-temperature district heating: An example for nursing homes in Nordic countries

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Cited by 18 publications
(3 citation statements)
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“…Another main finding of all these studies is the need of developing accurate models in order to forecast not only the thermal energy demand profiles [13,14] but also the distributed thermal production at the prosumers' sites, preferably including network dynamics and thermal transients [15]. This, coupled with the correct choice of the prosumer substation architecture, represents a key factor for the thermal prosumer diffusion.…”
Section: Introductionmentioning
confidence: 99%
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“…Another main finding of all these studies is the need of developing accurate models in order to forecast not only the thermal energy demand profiles [13,14] but also the distributed thermal production at the prosumers' sites, preferably including network dynamics and thermal transients [15]. This, coupled with the correct choice of the prosumer substation architecture, represents a key factor for the thermal prosumer diffusion.…”
Section: Introductionmentioning
confidence: 99%
“…This, coupled with the correct choice of the prosumer substation architecture, represents a key factor for the thermal prosumer diffusion. Indeed, temperatures play a major role in the overall efficiency of the DH system [14]. In detail, on one hand, traditional DH benefits from high temperature differences between the supply and return pipes (to limit the flowrates and hence the pumping power) and from low temperatures in the return pipe (that are desirable since they increase the centralized heat production efficiency and decrease the network heat losses), but this may clash with the requirements for the bidirectional heat exchange at the thermal prosumers' sites [16].…”
Section: Introductionmentioning
confidence: 99%
“…Several studies have been conducted to improve efficiency and to show the effectiveness of District Heating & Cooling (DHC) systems. For example, the work in [1] predicts the short and long-term heating demand in nursing homes in the Nordic countries through linear regression and artificial neural networks. Based on the findings, the authors propose installing heat pumps in low-temperature District Heating (DH) to meet the load requirements.…”
Section: Introductionmentioning
confidence: 99%