Primary energy savings through thermal storage in district heating networks

Verda, Vittorio; Colella, Francesco

doi:10.1016/j.energy.2011.04.015

Cited by 203 publications

(88 citation statements)

References 20 publications

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“…The tank sizing results give similar results to the one integrated in the micro-CHP SOFC system by CFCL BlueGen. The curve trend is in good agreement with [26][27][28]. We can see that stratification become less effective with time as the heat conduction increases.…”

Section: Tank Sizingsupporting

confidence: 78%

“…The effective conductivity acts by increasing the water thermal conductivity to include turbulent mixing in the thermocline which is one of the major contributor to the loss of the thermodynamic availability of the stored energy during the charging and discharging processes. The combined effect of thermal diffusion, heat loss via the tank walls and inlet flow induced mixing was quantified by establishing an interface and allowing the thermocline to degrade over time [26,27]. Under what conditions and to what extent these assumptions are justified can be determined only by experiment.…”

Section: Stratified Storage Heat Tank Model Designmentioning

confidence: 99%

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Modelling of a Solid Oxide Fuel Cell CHP System Coupled with a Hot Water Storage Tank for a Single Household

et al. 2015

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Abstract:In this paper a solid oxide fuel cell (SOFC) system for cogeneration of heat and power integrated with a stratified heat storage tank is studied. The use of a storage tank with thermal stratification allows one to increase the annual operating hours of CHP: heat can be produced when the request is low (for instance during the night), taking advantage of thermal stratification to increases the heat recovery performance. A model of the SOFC system is presented to estimate the energy required to meet the average electric energy demand of the residence. Two fuels are considered, namely syngas produced by gasification and natural gas. The tank model considers the temperature gradients over the tank height. The results of the numerical simulation are used to size the SOFC system and storage heat tank to provide energy for a small household using two different fuels. In particular it was shown that in the case of syngas, due to larger system heat output, a larger tank volume was required in order to accumulate unused heat over the night. The detailed description of the tank model will be useful to energy system modelers when sizing hot water tanks. Problem formulation is reported also using a Matlab script.

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Section: Tank Sizingsupporting

confidence: 78%

Section: Stratified Storage Heat Tank Model Designmentioning

confidence: 99%

Modelling of a Solid Oxide Fuel Cell CHP System Coupled with a Hot Water Storage Tank for a Single Household

et al. 2015

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“…Yet, the operational optimization of entire energy systems can only be realized with complex various energy-economic models [27,136,137]. The efforts in optimization range from the operational planning of distributed energy systems (DES) under the consideration of costs for fuels, maintenance and the investment [129] for integrating high price scenarios in which CHP units produce electricity related to the market situation in a deregulated electricity market [130,131,138].…”

Section: From Purely Structural Planning Towards Operational Planningmentioning

confidence: 99%

“…When thermal storages are discharged in peak load times, oil-driven boilers can be replaced. The base load for heat is covered with combined heat and power plants (CHP), whereby the simultaneously produced electricity is supplied to the electricity network [129]. Due to the rising share of the fluctuating energy resources, the combination of CHP and well-planned thermal energy storage facilities ensure grid stability.…”

Section: Planning Of Decentralized Storage Facilitiesmentioning

confidence: 99%

GIS-Based Planning and Modeling for Renewable Energy: Challenges and Future Research Avenues

Resch

Sagl

Törnros

et al. 2014

IJGI

124

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Abstract:In the face of the broad political call for an -energy turnaround‖, we are currently witnessing three essential trends with regard to energy infrastructure planning, energy generation and storage: from planned production towards fluctuating production on the basis of renewable energy sources, from centralized generation towards decentralized generation and from expensive energy carriers towards cost-free energy carriers. These changes necessitate considerable modifications of the energy infrastructure. Even though most of these modifications are inherently motivated by geospatial questions and challenges, the integration of energy system models and Geographic Information Systems (GIS) is still in its infancy. This paper analyzes the shortcomings of previous approaches in using GIS in renewable energy-related projects, extracts distinct challenges from these previous efforts and, finally, defines a set of core future research avenues for GIS-based energy infrastructure planning with a focus on the use of renewable energy. These future OPEN ACCESS ISPRS Int. J. Geo-Inf. 2014, 3 663 research avenues comprise the availability base data and their -geospatial awareness‖, the development of a generic and unified data model, the usage of volunteered geographic information (VGI) and crowdsourced data in analysis processes, the integration of 3D building models and 3D data analysis, the incorporation of network topologies into GIS, the harmonization of the heterogeneous views on aggregation issues in the fields of energy and GIS, fine-grained energy demand estimation from freely-available data sources, decentralized storage facility planning, the investigation of GIS-based public participation mechanisms, the transition from purely structural to operational planning, data privacy aspects and, finally, the development of a new dynamic power market design.Keywords: integration of GIS and energy system models; GIS and renewable energy; GIS-based energy infrastructure planning; future research challenges; fluctuating renewables; structural planning of local energy systems; operation optimization

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“…The possibility of using a dynamic simulation tool with the aim of studying interactions of cogeneration heat pump/district heating network, with a particular emphasis on the network to heat storage capacity, is examined in [6]. In [7] the use of storage systems that are charged at night and used during the start-up transients is examined for peak-shaving purpose. This is shown to be a very effective measure for reducing the boiler utilization and enhance cogeneration.…”

Section: Introductionmentioning

confidence: 99%

Thermal peak load shaving through users request variations

Verda¹

2016

Int. J. Thermo

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Peak shaving is a relatively new approach aimed at increasing the primary energy efficiency in District Heating Systems. This is mainly performed using thermal storage units that can be charged when the thermal request is small, usually at night, and discharged to cover peak requests. Thermal storage typically allows one increasing the utilization of waste heat, renewables and cogeneration systems while reducing the use of boilers. An alternative option to conventional thermal storage is "virtual storage". This consists in modifying the thermal request profiles of buildings in order to reduce their contributions in peak hours. Such modifications rely on the thermal capacity of buildings in order to comply with end-user requirements on the internal temperatures. The analysis of possible operational strategies should be performed using an integrated simulation, which considers both the thermos-fluid dynamic behavior of the network and the thermal behavior of the buildings. In this paper, a physical tool specifically conceived for the analysis of peak shaving in large networks through virtual storage is presented and applied to a portion of the Turin district heating network. Detailed information about thermal requests of buildings obtained from a pervasive metering system is used in order to characterize their behavior. This piece of information is then adopted for constraining and checking possible different operational strategies. Two different scenarios are analyzed and compared with current operation in terms of primary energy consumption, showing that primary energy savings of the order of 5% can be achieved without affecting the comfort perceived by the users.

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Primary energy savings through thermal storage in district heating networks

Cited by 203 publications

References 20 publications

Modelling of a Solid Oxide Fuel Cell CHP System Coupled with a Hot Water Storage Tank for a Single Household

Modelling of a Solid Oxide Fuel Cell CHP System Coupled with a Hot Water Storage Tank for a Single Household

GIS-Based Planning and Modeling for Renewable Energy: Challenges and Future Research Avenues

Thermal peak load shaving through users request variations

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