Dynamic simulation of an integrated energy system for buildings in cold climates with thermal energy storage

2021 ◽  
Vol 47 ◽  
pp. 101459
Author(s):  
Meysam Farrokhi ◽  
Roghayyeh Motallebzadeh ◽  
Nader Javani ◽  
Abdolsalam Ebrahimpour
Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2944
Author(s):  
Luca Baldini ◽  
Benjamin Fumey

The article estimates energy flexibility provided to the electricity grid by integration of long-term thermal energy storage in buildings. To this end, a liquid sorption storage combined with a compression heat pump is studied for a single-family home. This combination acts as a double-stage heat pump comprised of a thermal and an electrical stage. It lowers the temperature lift to be overcome by the electrical heat pump and thus increases its coefficient of performance. A simplified model is used to quantify seasonal energy flexibility by means of electric load shifting evaluated with a monthly resolution. Results are presented for unlimited and limited storage capacity leading to a total seasonal electric load shift of 631.8 kWh/a and 181.7 kWh/a, respectively. This shift, referred to as virtual battery effect, provided through long-term thermal energy storage is large compared to typical electric battery capacities installed in buildings. This highlights the significance of building-integrated long-term thermal energy storage for provision of energy flexibility to the electricity grid and hence for the integration of renewables in our energy system.


2015 ◽  
Vol 52 (6) ◽  
pp. 22-37 ◽  
Author(s):  
P. Ivanova ◽  
O. Linkevics ◽  
A. Cers

Abstract The installation of thermal energy storage system (TES) provides the optimisation of energy source, energy security supply, power plant operation and energy production flexibility. The aim of the present research is to evaluate the feasibility of thermal energy system installation at Riga TPP–2. The six modes were investigated: four for non-heating periods and two for heating periods. Different research methods were used: data statistic processing, data analysis, analogy, forecasting, financial method and correlation and regression method. In the end, the best mode was chosen – the increase of cogeneration unit efficiency during the summer.


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