scholarly journals Calculation of the power of thermal energy consumed for heating the reactor of a bioenergy plant

2021 ◽  
Vol 264 ◽  
pp. 04069
Author(s):  
Nodira Imomova ◽  
Ochil Komilov ◽  
Jurabek Majitov ◽  
Jukhriddin Ergashov ◽  
Kamol Usmonov
Keyword(s):  
Power Consumption ◽  
Boundary Conditions ◽  
Heat Equation ◽  
Thermal Energy ◽  
Temperature Difference ◽  
Heat Sources ◽  
Additional Source ◽  
Additional Heat ◽  
Bioenergy Plant ◽  
Biogas Reactor

The issues of calculating the power of thermal energy consumed for heating biomass in the reactor of a bioenergy plant are considered. Based on the Fourier heat equation, a solution for the axisymmetric cylindrical problem under boundary conditions of the first kind is obtained, and the power of additional heat sources in a cylindrical biogas reactor is calculated. The influence of the height of the bioreactor and the temperature difference of the biomass on the power consumption of an additional source of thermal energy is analyzed

scholarly journals Linear evolution equations on the half-line with dynamic boundary conditions

2021 ◽  
pp. 1-33
Author(s):  
D. A. SMITH ◽  
W. Y. TOH
Keyword(s):  
Boundary Conditions ◽  
Heat Equation ◽  
Evolution Equations ◽  
Half Line ◽  
Robin Problem ◽  
Dynamic Boundary Conditions ◽  
Transform Method ◽  
Linear Evolution ◽  
Robin Condition ◽  
Linear Evolution Equations

The classical half-line Robin problem for the heat equation may be solved via a spatial Fourier transform method. In this work, we study the problem in which the static Robin condition $$bq(0,t) + {q_x}(0,t) = 0$$ is replaced with a dynamic Robin condition; $$b = b(t)$$ is allowed to vary in time. Applications include convective heating by a corrosive liquid. We present a solution representation and justify its validity, via an extension of the Fokas transform method. We show how to reduce the problem to a variable coefficient fractional linear ordinary differential equation for the Dirichlet boundary value. We implement the fractional Frobenius method to solve this equation and justify that the error in the approximate solution of the original problem converges appropriately. We also demonstrate an argument for existence and unicity of solutions to the original dynamic Robin problem for the heat equation. Finally, we extend these results to linear evolution equations of arbitrary spatial order on the half-line, with arbitrary linear dynamic boundary conditions.

scholarly journals Efficient Operation Method of Aquifer Thermal Energy Storage System Using Demand Response

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3129
Author(s):  
Jewon Oh ◽  
Daisuke Sumiyoshi ◽  
Masatoshi Nishioka ◽  
Hyunbae Kim
Keyword(s):  
Energy Storage ◽  
Power Consumption ◽  
Thermal Energy ◽  
Demand Response ◽  
Thermal Energy Storage ◽  
Heat Storage ◽  
Storage System ◽  
Total Power ◽  
Operation Method ◽  
Total Power Consumption

The mass introduction of renewable energy is essential to reduce carbon dioxide emissions. We examined an operation method that combines the surplus energy of photovoltaic power generation using demand response (DR), which recognizes the balance between power supply and demand, with an aquifer heat storage system. In the case that predicts the occurrence of DR and performs DR storage and heat dissipation operation, the result was an operation that can suppress daytime power consumption without increasing total power consumption. Case 1-2, which performs nighttime heat storage operation for about 6 h, has become an operation that suppresses daytime power consumption by more than 60%. Furthermore, the increase in total power consumption was suppressed by combining DR heat storage operation. The long night heat storage operation did not use up the heat storage amount. Therefore, it is recommended to the heat storage operation at night as much as possible before DR occurs. In the target area of this study, the underground temperature was 19.1 °C, the room temperature during cooling was about 25 °C and groundwater could be used as the heat source. The aquifer thermal energy storage (ATES) system in this study uses three wells, and consists of a well that pumps groundwater, a heat storage well that stores heat and a well that used heat and then returns it. Care must be taken using such an operation method depending on the layer configuration.

scholarly journals Artificial Neural Network Simulation of Energetic Performance for Sorption Thermal Energy Storage Reactors

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3294
Author(s):  
Carla Delmarre ◽  
Marie-Anne Resmond ◽  
Frédéric Kuznik ◽  
Christian Obrecht ◽  
Bao Chen ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Energy Storage ◽  
Thermal Energy ◽  
Temperature Difference ◽  
Thermal Energy Storage ◽  
Heat Storage ◽  
Experimental Results ◽  
Physical Models ◽  
Artificial Neural

Sorption thermal heat storage is a promising solution to improve the development of renewable energies and to promote a rational use of energy both for industry and households. These systems store thermal energy through physico-chemical sorption/desorption reactions that are also termed hydration/dehydration. Their introduction to the market requires to assess their energy performances, usually analysed by numerical simulation of the overall system. To address this, physical models are commonly developed and used. However, simulation based on such models are time-consuming which does not allow their use for yearly simulations. Artificial neural network (ANN)-based models, which are known for their computational efficiency, may overcome this issue. Therefore, the main objective of this study is to investigate the use of an ANN model to simulate a sorption heat storage system, instead of using a physical model. The neural network is trained using experimental results in order to evaluate this approach on actual systems. By using a recurrent neural network (RNN) and the Deep Learning Toolbox in MATLAB, a good accuracy is reached, and the predicted results are close to the experimental results. The root mean squared error for the prediction of the temperature difference during the thermal energy storage process is less than 3K for both hydration and dehydration, the maximal temperature difference being, respectively, about 90K and 40K.

Sidewall finite-conductivity effects in confined turbulent thermal convection

2002 ◽  
Vol 473 ◽  
pp. 201-210 ◽  
Author(s):  
ROBERTO VERZICCO
Keyword(s):  
Boundary Conditions ◽  
Thermal Convection ◽  
Lateral Wall ◽  
Finite Conductivity ◽  
Mean Flow ◽  
Number Range ◽  
Additional Heat ◽  
Low Aspect Ratio ◽  
Temperature Boundary ◽  
The Mean

The effects of a sidewall with finite thermal conductivity on confined turbulent thermal convection has been investigated using direct numerical simulation. The study is motivated by the observation that the heat flowing through the lateral wall is not always negligible in the low-aspect-ratio cells of several recent experiments. The extra heat flux modifies the temperature boundary conditions of the flow and therefore the convective heat transfer. It has been found that, for usual sidewall thicknesses, the heat travelling from the hot to the cold plates directly through the sidewall is negligible owing to the additional heat exchanged at the lateral fluid/wall interface. In contrast, the modified temperature boundary conditions alter the mean flow yielding significant Nusselt number corrections which, in the low Rayleigh number range, can change the exponent of the Nu vs. Ra power law by 10%.

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