scholarly journals A Parametric Study of a Solar-Assisted House Heating System with a Seasonal Underground Thermal Energy Storage Tank

2020 ◽  
Vol 12 (20) ◽  
pp. 8686 ◽  
Author(s):  
Le Minh Nhut ◽  
Waseem Raza ◽  
Youn Cheol Park
Keyword(s):  
Mathematical Model ◽  
Energy Storage ◽  
South Korea ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Storage Tank ◽  
Fossil Fuels ◽  
Weather Conditions ◽  
Heating System ◽  
Thickness Effect

The requirement for energy is increasing worldwide as populations and economies develop. Reasons for this increase include global warming, climate change, an increase in electricity demand, and paucity of fossil fuels. Therefore, research in renewable energy technology has become a central topic in recent studies. In this study, a solar-assisted house heating system with a seasonal underground thermal energy storage tank is proposed based on the reference system to calculate the insulation thickness effect, the collector area, and an underground storage tank volume on the system performance according to real weather conditions at Jeju Island, South Korea. For this purpose, a mathematical model was established to calculate its operating performance. This mathematical model used the thermal response factor method to calculate the heat load and heat loss of the seasonal underground thermal energy storage tank. The results revealed that on days with different weather conditions, namely, clear weather, intermittent clouds sky, and overcast sky, the obtained solar fraction was 45.8%, 17.26%, and 0%, respectively. Using this method, we can save energy, space, and cost. This can then be applied to the solar-assisted house heating system in South Korea using the seasonal underground thermal energy storage tank.

scholarly journals Experimental study of a large temperature difference thermal energy storage tank for centralized heating systems

2018 ◽  
Vol 22 (1 Part B) ◽  
pp. 613-621 ◽  
Author(s):  
Jian Sun ◽  
Jing Hua ◽  
Lin Fu ◽  
Shigang Zhang
Keyword(s):  
Energy Storage ◽  
Thermal Energy ◽  
Temperature Difference ◽  
Thermal Energy Storage ◽  
Storage Tank ◽  
Experimental System ◽  
Heating System ◽  
Large Temperature ◽  
Low Grade ◽  
Disturbance Factor

Decreasing the backwater temperature of the primary pipe in a centralized heating system is one successful way to increase the heating capacity and recover different kinds of industrial low-grade heat from the system. A new system combining an energy storage tank and a heat pump is introduced in this study as the key device in this system, so the temperature difference of this thermal storage tank could be over 25?C. To improve the thermal energy storage tank design, a mathematical model considering disturbance factor is given, an experimental system is built, and good agreement is found when the experimental results are compared with simulation results.

Near Optimal Receding Horizon Control of Thermal Energy Storage

2021 ◽  
pp. 1-13
Author(s):  
Omer Ahmed Qureshi ◽  
Peter R. Armstrong
Keyword(s):  
Energy Storage ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Energy Savings ◽  
Search Algorithm ◽  
Cost Savings ◽  
Weather Conditions ◽  
Receding Horizon Control ◽  
Receding Horizon ◽  
Favorable Weather

Abstract Efficient plant operation can be achieved by properly loading and sequencing available chillers to charge and discharge a thermal energy storage (TES) reservoir at optimal rates and times. TES charging sequences are often determined by heuristic rules that typically aim to reduce utility costs under time of use rates. However, such rules of thumb may result in significantly sub optimal performance on somedays. Rigorous optimization, on the other hand, is computationally expensive and can be unreliable as well if not carefully implemented. Receding Horizon Control (RHC) using the novel finite search algorithm is reliable and can reach ~80% of achievable energy efficiency and/or peak shifting capacity has been our target. A novel algorithm is developed to reliably achieve near optimal control for charging the stratified sensible cool storage reservoir of a chiller plant. The algorithm provides a constant COP (or cost per ton-hour) for 24-hr dispatch plan under which chillers operate during most favorable weather conditions. Analysis of four hot climates, ranging from humid to dry, indicates 2.4~2.6% energy savings under a flat electricity rate relative to the same plant operating without TES. Annual cost savings from 6% to 9% was found for electricity billed under a simple (10am-10pm) time-of-use rate with no demand charge and no ratchet component.

Analytical Analysis of Thermal Energy Storage Performance of Room Heating System by Solar Energy

2013 ◽  
Vol 6 (2) ◽  
pp. 135-145
Author(s):  
Tadahmun A. Yassen ◽  
Hussain H. Al-Kayiem ◽  
Maki H. Khalaf ◽  
Nassir D. Dhamin
Keyword(s):  
Energy Storage ◽  
Solar Energy ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Heating System ◽  
Analytical Analysis ◽  
Storage Performance

scholarly journals Development and experimental testing of a compact thermal energy storage tank using paraffin targeting domestic hot water production needs

2020 ◽  
Vol 19 ◽  
pp. 100573 ◽  
Author(s):  
George Dogkas ◽  
John Konstantaras ◽  
Maria K. Koukou ◽  
Michail Gr. Vrachopoulos ◽  
Christos Pagkalos ◽  
...  
Keyword(s):  
Energy Storage ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Storage Tank ◽  
Experimental Testing ◽  
Hot Water ◽  
Water Production ◽  
Domestic Hot Water

scholarly journals Domestic hot water consumption vs. solar thermal energy storage: The optimum size of the storage tank

2012 ◽  
Vol 97 ◽  
pp. 897-906 ◽  
Author(s):  
M.C. Rodríguez-Hidalgo ◽  
P.A. Rodríguez-Aumente ◽  
A. Lecuona ◽  
M. Legrand ◽  
R. Ventas
Keyword(s):  
Energy Storage ◽  
Thermal Energy ◽  
Water Consumption ◽  
Thermal Energy Storage ◽  
Storage Tank ◽  
Hot Water ◽  
Solar Thermal ◽  
Optimum Size ◽  
Solar Thermal Energy ◽  
Domestic Hot Water

Near Optimal Model Predictive Control of Thermal Energy Storage

2020 ◽  
Author(s):  
O. A. Qureshi ◽  
P. R. Armstrong
Keyword(s):  
Energy Storage ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
High Reliability ◽  
Operating Cost ◽  
Weather Conditions ◽  
Preliminary Evaluation ◽  
Novel Algorithm

Abstract Efficient plant operation can be achieved by properly loading and sequencing available chillers to charge a thermal energy storage (TES) reservoir. TES charging sequences are often determined by heuristic rules that typically aim to reduce utility costs under time of use rates. However, such rules of thumb are in most cases far from optimal even for this task. Rigorous optimization, on the other hand, is computationally expensive and can be unreliable as well if not carefully implemented. Model-predictive control (MPC) that is reliable, as well as effective, in TES application must be developed. The goal is to develop an algorithm that can reach ∼80% of achievable energy efficiency and peak shifting capacity with very high reliability. A novel algorithm is developed to reliably achieve near optimal control for charging cool storage in chiller plants. Algorithm provides a constant COP (or cost per ton-hour) for 24-hr dispatch plan at which plant operates during most favorable weather conditions. Preliminary evaluation of this novel algorithm has indicated up to 6% improvement in plant annual operating cost relative to the same plant operating without TES. TOU rate used in both cases charges 7.4cents/kWh during off peak hours and 9.8cents/kWh during peak hours (Peak hours are 10 am to 10 pm).

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