scholarly journals Numerical comparison of two operating modes of thermal energy storage tank for compression heat storage in adiabatic compressed air energy storage

2020 ◽  
Vol 30 ◽  
pp. 101558 ◽  
Author(s):  
Chidiebere Diyoke ◽  
Ugochukwu Ngwaka
2019 ◽  
Vol 141 (6) ◽  
Author(s):  
Khashayar Hakamian ◽  
Kevin R. Anderson ◽  
Maryam Shafahi ◽  
Reza Baghaei Lakeh

Power overgeneration by renewable sources combined with less dispatchable conventional power plants introduces the power grid to a new challenge, i.e., instability. The stability of the power grid requires constant balance between generation and demand. A well-known solution to power overgeneration is grid-scale energy storage. Compressed air energy storage (CAES) has been utilized for grid-scale energy storage for a few decades. However, conventional diabatic CAES systems are difficult and expensive to construct and maintain due to their high-pressure operating condition. Hybrid compressed air energy storage (HCAES) systems are introduced as a new variant of old CAES technology to reduce the cost of energy storage using compressed air. The HCAES system split the received power from the grid into two subsystems. A portion of the power is used to compress air, as done in conventional CAES systems. The rest of the electric power is converted to heat in a high-temperature thermal energy storage (TES) component using Joule heating. A computational approach was adopted to investigate the performance of the proposed TES system during a full charge/storage/discharge cycle. It was shown that the proposed design can be used to receive 200 kW of power from the grid for 6 h without overheating the resistive heaters. The discharge computations show that the proposed geometry of the TES, along with a control strategy for the flow rate, can provide a 74-kW microturbine of the HCAES with the minimum required temperature, i.e., 1144 K at 0.6 kg/s of air flow rate for 6 h.


2021 ◽  
Vol 12 (1(43)2021) ◽  
pp. 24-42
Author(s):  
Oktawia DOLNA ◽  
◽  
Robert MATYSKO ◽  
Weronika WISNIEWSKA,

The article content constitutes the answer to a growing interest of a heat-flow processes automatisation applied into detached houses heating sector. The paper contains a brief description of a usage of the PID and fuzzy controllers. The methods of the controller’s setting selections (e.g. Ziegler-Nichols method), which are alternative to the classical ones, have been also presented within the paper. The optimization of the controllers’ settings for the executive systems of a thermodynamic cycle is also available in the paper. It was carried out based on the minimum heat flux increase time in the condenser unit of a heat storage tank. For this purpose the Simplex Neldera- Meada algorithm was used. In the article, the results of the changeable work of the thermal energy storage tank have also been presented. The analysis was carried out in the Matlab Simulink environment.


Author(s):  
Kent Udell ◽  
Michael Beeman

The performance of CAES is evaluated for various configurations, with and without thermal energy storage. First, a conventional compressed air energy storage process is modeled using a time series iterative forward differencing method to simulate the round trip efficiency, exergy storage, cavern temperatures and pressures, and the gas expander exit temperature of a CAES plant. The computational model was validated experimentally by comparing trended data of the compression cycle of a 280 HP Gardener-Denver tandem horizontal two-stage compressor to computational results. It was found that the process of cooling the compressors resulted in a large exergy loss and the inefficiencies of the expanders lead to higher temperature gas being exhausted back to ambient pressures. Second, Advanced Adiabatic Compressed Air Energy Storage (AACAES) was simulated to study the effectiveness of storing the thermal energy removed from the compressors to be added to the compressed air as it enters the expanders at a later time. Third, the concept of increasing the capacity of the thermal energy storage systems to allow recharge with concentrated solar heat was explored. It was found that the thermal efficiency of converting the solar thermal energy to power would be high (> 60%). Further, the expander exhaust temperature and exergy are high (> 500 K), implying that additional waste heat energy recovery will be possible. Taken together, the results of this study show that an integrated, high efficiency, on-demand, water-free, solar energy delivery system is possible if combined with an AACAES system.


Author(s):  
Reza Baghaei Lakeh ◽  
Ian C. Villazana ◽  
Sammy Houssainy ◽  
Kevin R. Anderson ◽  
H. Pirouz Kavehpour

The share of renewable energy sources in the power grid is showing an increasing trend world-wide. Most of the renewable energy sources are intermittent and have generation peaks that do not correlate with peak demand. The stability of the power grid is highly dependent on the balance between power generation and demand. Compressed Air Energy Storage (CAES) systems have been utilized to receive and store the electrical energy from the grid during off-peak hours and play the role of an auxiliary power plant during peak hours. Using Thermal Energy Storage (TES) systems with CAES technology is shown to increase the efficiency and reduce the cost of generated power. In this study, a modular solid-based TES system is designed to store thermal energy converted from grid power. The TES system stores the energy in the form of internal energy of the storage medium up to 900 K. A three-dimensional computational study using commercial software (ANSYS Fluent) was completed to test the performance of the modular design of the TES. It was shown that solid-state TES, using conventional concrete and an array of circular fins with embedded heaters, can be used for storing heat for a high temperature hybrid CAES (HTH-CAES) system.


Energy ◽  
2019 ◽  
Vol 188 ◽  
pp. 115993 ◽  
Author(s):  
Qian Zhou ◽  
Dongmei Du ◽  
Chang Lu ◽  
Qing He ◽  
Wenyi Liu

Energy ◽  
2016 ◽  
Vol 103 ◽  
pp. 182-191 ◽  
Author(s):  
Sixian Wang ◽  
Xuelin Zhang ◽  
Luwei Yang ◽  
Yuan Zhou ◽  
Junjie Wang

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