Quantifying Demand Balancing in Bidirectional Low Temperature Networks

Wirtz, Marco; Kivilip, Lukas; Remmen, Peter; Müller, Dirk

doi:10.1016/j.enbuild.2020.110245

Cited by 45 publications

(19 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The efficiency and profitability of bidirectional 5GDHC systems strongly depends on the heating and cooling demand profiles of the connected buildings and their simultaneity. In particular, the efficiency of 5GDHC systems can be calculated using a metric called Demand Overlap Coefficient (DOC) (Wirtz et al 2020). For discrete, equally spaced time intervals t ∈ T , the DOC of all buildings b ∈ B in a district is defined by Equation 1:…”

Section: Use Casementioning

confidence: 99%

“…The calculation resulted in a DOC equals to 0.38. According to Wirtz et al (2020), for DOCs larger than 0.3, a heating and cooling supply with a 5GDHC system has a higher exergy efficiency compared to a reference system. Since the calculation of the DOC is based only on heating and cooling building demand, no models related to the district energy network were needed in this case study.…”

Section: Use Casementioning

confidence: 99%

See 1 more Smart Citation

Towards an automated generator of urban building energy loads from 3D building models

Maccarini¹,

Mans²,

Sørensen

et al. 2021

Linköping Electronic Conference Proceedings

View full text Add to dashboard Cite

Buildings in cities are one of the major contributors of carbon emissions worldwide. Thus, improving building energy efficiency is one of the key strategies towards sustainable urbanization. Urban building energy modeling (UBEM) is a valuable methodology to tackle these challenges, as it provides users with the energy demand of the building stock, scenarios evaluation, peak loads and other useful analyses. This paper presents an open-source tool to automatically convert 3D building models into ready-to-run Modelica models for urban energy simulations. The software enables users to create 3D building geometries, perform data enrichment and execute model generation of reduced order Modelica models. The software is written in Python and it has been developed as an add-on for the 3D creation application Blender. The first part of the paper describes the general approach and the architecture of the tool. In the second part, a demonstration of the tool's capabilities is illustrated.

show abstract

Section: Use Casementioning

confidence: 99%

Section: Use Casementioning

confidence: 99%

Towards an automated generator of urban building energy loads from 3D building models

Maccarini¹,

Mans²,

Sørensen

et al. 2021

Linköping Electronic Conference Proceedings

View full text Add to dashboard Cite

show abstract

“…The results of its application to a case study that consisted of a German university campus with 17 buildings, most of them with heating and cooling demands, showed that, in comparison with a reference scenario consisting of individual heating, ventilation and air conditioning (HVAC) plants (driven by electric boilers, air-source heat pumps, and chillers), the 5GDHC system designed reduced both the total annualised costs and CO 2 emissions by 42% and 56%, respectively. In [44], the same authors introduced and evaluated the demand overlap coefficient (DOC) on the same case study to assess the simultaneity of the heating and cooling demands in different district configurations. With respect to the reference scenario, the results showed that the 5GDHC systems supplying the district with a DOC higher than 0.3 have a higher exergy efficiency, whereas just the ones with a DOC higher than 0.45 imply a lower specific supply cost.…”

Section: Recent Publications About 5gdhc Systems and Urban Excess Heat Recoverymentioning

confidence: 99%

Fifth-Generation District Heating and Cooling Substations: Demand Response with Artificial Neural Network-Based Model Predictive Control

et al. 2020

View full text Add to dashboard Cite

District heating and cooling (DHC) is considered one of the most sustainable technologies to meet the heating and cooling demands of buildings in urban areas. The fifth-generation district heating and cooling (5GDHC) concept, often referred to as ambient loops, is a novel solution emerging in Europe and has become a widely discussed topic in current energy system research. 5GDHC systems operate at a temperature close to the ground and include electrically driven heat pumps and associated thermal energy storage in a building-sited energy transfer station (ETS) to satisfy user comfort. This work presents new strategies for improving the operation of these energy transfer stations by means of a model predictive control (MPC) method based on recurrent artificial neural networks. The results show that, under simple time-of-use utility rates, the advanced controller outperforms a rule-based controller for smart charging of the domestic hot water (DHW) thermal energy storage under specific boundary conditions. By exploiting the available thermal energy storage capacity, the MPC controller is capable of shifting up to 14% of the electricity consumption of the ETS from on-peak to off-peak hours. Therefore, the advanced control implemented in 5GDHC networks promotes coupling between the thermal and the electric sector, producing flexibility on the electric grid.

show abstract

“…Low-temperature networks are even commonly integrated into existing high-temperature systems as a sub-network [7]. However, during the last several years, the new generation has been defined, usually called 5th generation [8,9], which enables the higher utilization of low-temperature waste heat sources and unlocks the possibility of bidirectionality in thermal networks [10]. In other words, some customers can serve both as end-users and suppliers of the network [11].…”

Section: Introductionmentioning

confidence: 99%

Technical and Economic Assessment of Supermarket and Power Substation Waste Heat Integration into Existing District Heating Systems

et al. 2022

View full text Add to dashboard Cite

District heating systems are almost always located in densely populated urban areas where various heat sources are available, such as cooling and refrigeration systems in supermarkets, shopping malls, and power transformers. These urban sources often have a large share of waste heat, which is usually emitted into the environment. This waste heat could be used to partially cover the thermal load in district heating systems. The biggest challenge for their integration is the spatial distribution of urban heat sources in relation to the existing heat network and the temporal distribution of the availability of waste heat energy throughout the year. In this paper, we have developed an economic assessment model for the integration of urban heat sources into existing district heating systems. By the hourly merit order of waste heat utilization technologies based on pinch analysis, we have defined the most suitable integration of urban heat sources into existing district heating systems. Different temperature regimes of the urban source and the existing heat network have been considered. Finally, the method was tested on the case study of a supermarket and power substation located in Zagreb, while the sensitivity analysis was carried out with a focus on various technical and economic boundary conditions.

show abstract

Quantifying Demand Balancing in Bidirectional Low Temperature Networks

Cited by 45 publications

References 35 publications

Towards an automated generator of urban building energy loads from 3D building models

Towards an automated generator of urban building energy loads from 3D building models

Fifth-Generation District Heating and Cooling Substations: Demand Response with Artificial Neural Network-Based Model Predictive Control

Technical and Economic Assessment of Supermarket and Power Substation Waste Heat Integration into Existing District Heating Systems

Contact Info

Product

Resources

About