scholarly journals Toward efficient numerical modeling and analysis of large-scale thermal energy storage for renewable district heating

2020 ◽  
Vol 279 ◽  
pp. 115840 ◽  
Author(s):  
Abdulrahman Dahash ◽  
Fabian Ochs ◽  
Alice Tosatto ◽  
Wolfgang Streicher
Keyword(s):  
Numerical Modeling ◽  
Energy Storage ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Large Scale ◽  
District Heating ◽  
Modeling And Analysis

Numerical modeling and analysis of dual medium thermocline thermal energy storage

2018 ◽  
Vol 16 ◽  
pp. 218-230 ◽  
Author(s):  
Bhaskar Rahul Nandi ◽  
Santanu Bandyopadhyay ◽  
Rangan Banerjee
Keyword(s):  
Numerical Modeling ◽  
Energy Storage ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Modeling And Analysis

scholarly journals Design Aspects for Large-scale Pit and Aquifer Thermal Energy Storage for District Heating and Cooling

2018 ◽  
Vol 149 ◽  
pp. 585-594 ◽  
Author(s):  
Thomas Schmidt ◽  
Thomas Pauschinger ◽  
Per Alex Sørensen ◽  
Aart Snijders ◽  
Reda Djebbar ◽  
...  
Keyword(s):  
Energy Storage ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Large Scale ◽  
District Heating ◽  
Heating And Cooling ◽  
Aquifer Thermal Energy Storage

scholarly journals Congestion management via increasing integration of electric and thermal energy infrastructures

2021 ◽  
Vol 238 ◽  
pp. 05005
Author(s):  
Alvaro Gonzalez-Castellanos ◽  
Priyanko Guha Thakurta ◽  
Aldo Bischi
Keyword(s):  
Energy Storage ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Large Scale ◽  
District Heating ◽  
Congestion Management ◽  
Mixed Integer ◽  
Electrical Network ◽  
Independent Variables ◽  
Two Independent Variables

Congestion caused in the electrical network due to renewable generation can be effectively managed by integrating electric and thermal infrastructures, the latter being represented by large scale District Heating (DH) networks, often fed by large combined heat and power (CHP) plants. The CHP plants could further improve the profit margin of district heating multi-utilities by selling electricity in the power market by adjusting the ratio between generated heat and power. The latter is possible only for certain CHP plants, which allow decoupling the two commodities generation, namely the ones provided by two independent variables (degrees-of-freedom) or by integrating them with thermal energy storage and Power-to-Heat (P2H) units. CHP units can, therefore, help in the congestion management of the electricity network. A detailed mixed-integer linear programming (MILP) optimization model is introduced for solving the network-constrained unit commitment of integrated electric and thermal infrastructures. The developed model contains a detailed characterization of the useful effects of CHP units, i.e., heat and power, as a function of one and two independent variables. A lossless DC flow approximation models the electricity transmission network. The district heating model includes the use of gas boilers, electric boilers, and thermal energy storage. The conducted studies on IEEE 24 bus system highlight the importance of a comprehensive analysis of multi-energy systems to harness the flexibility derived from the joint operation of electric and heat sectors and managing congestion in the electrical network.

scholarly journals Development and Analysis of a Multi-Node Dynamic Model for the Simulation of Stratified Thermal Energy Storage

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4275 ◽  
Author(s):  
Nora Cadau ◽  
Andrea De Lorenzi ◽  
Agostino Gambarotta ◽  
Mirko Morini ◽  
Michele Rossi
Keyword(s):  
Energy Storage ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Supply And Demand ◽  
District Heating ◽  
Energy Systems ◽  
High Flow ◽  
Market Penetration ◽  
Flow Rates ◽  
Smart Energy Systems

To overcome non-programmability issues that limit the market penetration of renewable energies, the use of thermal energy storage has become more and more significant in several applications where there is a need for decoupling between energy supply and demand. The aim of this paper is to present a multi-node physics-based model for the simulation of stratified thermal energy storage, which allows the required level of detail in temperature vertical distribution to be varied simply by choosing the number of nodes and their relative dimensions. Thanks to the chosen causality structure, this model can be implemented into a library of components for the dynamic simulation of smart energy systems. Hence, unlike most of the solutions proposed in the literature, thermal energy storage can be considered not only as a stand-alone component, but also as an important part of a more complex system. Moreover, the model behavior has been analyzed with reference to the experimental results from the literature. The results make it possible to conclude that the model is able to accurately predict the temperature distribution within a stratified storage tank typically used in a district heating network with limitations when dealing with small storage volumes and high flow rates.

scholarly journals Optimized Layouts of Borehole Thermal Energy Storage Systems in 4th Generation Grids

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4405 ◽  
Author(s):  
Hoofar Hemmatabady ◽  
Julian Formhals ◽  
Bastian Welsch ◽  
Daniel Otto Schulte ◽  
Ingo Sass
Keyword(s):  
Energy Storage ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Heating Temperature ◽  
Storage System ◽  
District Heating ◽  
Temperature Shift ◽  
Heat Pumps ◽  
Optimal Designs ◽  
Practical Implementation

Borehole thermal energy storage (BTES) systems are a viable option to meet the increasing cooling demand and to increase the sustainability of low-temperature district heating and cooling (DHC) grids. They are able to store the rejected heat of cooling cycles on a seasonal basis and deliver this heat during the heating season. However, their efficient practical implementation requires a thorough analysis from technical, economic and environmental points of view. In this comparative study, a dynamic exergoeconomic assessment is adopted to evaluate various options for integrating such a storage system into 4th generation DHC grids in heating dominated regions. For this purpose, different layouts are modeled and parameterized. Multi-objective optimization is conducted, varying the most important design variables in order to maximize exergetic efficiency and to minimize levelized cost of energy (LCOE). A comparison of the optimal designs of the different layouts reveals that passive cooling together with maximizing the heating temperature shift, accomplished by a heat pump, lead to optimal designs. Component-wise exergy and cost analysis of the most efficient designs highlights that heat pumps are responsible for the highest share in inefficiency while the installation of BTES has a high impact in the LCOE. BTES and buffer storage tanks have the lowest exergy destruction for all layouts and increasing the BTES volume results in more efficient DHC grids.

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