Heat Current Method Research Articles

Thermal conductivity calculation using homogeneous non-equilibrium molecular dynamics simulation with Allegro

In this study, we derive the heat flux formula for the Allegro model, one of machine-learning interatomic potentials using the equivariant deep neural network, to calculate lattice thermal conductivity using the homogeneous non-equilibrium molecular dynamics (HNEMD) method based on the Green-Kubo formula. Allegro can construct more advanced atomic descriptors than conventional ones, and can be applied to multicomponent and large-scale systems, providing a significant advantage in estimating the thermal conductivity of anharmonic materials, such as thermoelectric materials. In addition, the spectral heat current (SHC) method, recently developed for the HNEMD framework (HNEMD-SHC), allows the calculation of not only the total thermal conductivity but also its frequency components. The verification of the heat flux and the demonstration of HNEMD-SHC method are performed for the extremely anharmonic low-temperature phase of Ag2Se.

Modeling and performance analysis of a new integrated solid oxide fuel cell and photovoltaic‐thermal energy supply system by heat current method

AbstractEfficient and reliable utilization of renewable energy at the user's end is the key to achieving a low‐carbon life. This paper proposed a new distributed energy system around the comprehensive utilization of solar energy by integrating solid oxide fuel cell (SOFC), energy storage equipment, photovoltaic thermal (PVT) collector, and heat pump. By integrating the use of SOFC and PVT, we can further minimize reliance on fossil fuels, while employing the coupling of PVT and heat pump effectively mitigates the inherent challenges of solar energy's variability and intermittency, all while enhancing overall system efficiency. On this basis, we apply the heat current method to construct a cross‐scale heat current model of the components and the system by considering the energy transfer, conversion, and storage characteristics of the system. By employing this model, we simulate the system's operation throughout an entire typical day, assess the COP enhancement of the PVT‐coupled heat pump system, analyze the influence of diverse operating conditions on daily system performance, and evaluate the economy of the energy storage devices in the system.

Multi-scale simulation and optimization on a thermal management system of intermediate circuit and experiment validation

In the system-level simulations of heat transfer systems, the characteristics of heat exchangers are often considered constant or used in empirical formulas, which affect the accuracy of the system model. Herein a multi-scale simulation method to analyze the heat transfer characteristics of a thermal management system, including an intermediate loop is proposed. The system model is developed based on the heat current method and flow resistance models. By applying COMSOL LiveLink for MATLAB module, a multi-scale model is obtained, which combines three-dimensional numerical models of the heat exchangers with the system model. Compared to the experimental results, the relative errors associated with the outlet temperatures and heat transfer rate are less than 1.1% and 8.2 %, respectively, thus validating the model. Discussions on the effects of the geometric structure of the heat exchangers on the system show that a plate heat exchanger with 12 plates and a plate spacing of 8 mm is better. For achieving systematic maximum heat dissipation for a certain pumping power consumption, a multi-scale optimization method is proposed by coupling the Lagrange function and numerical model. The results show that the total heat transfer rate improves by 5.89 %, from 8314.81 W to 8804.35 W.

A Comprehensive Study of a Low-Grade Heat-Driven Cooling and Power System Based on Heat Current Method

A Comprehensive Study of a Low-Grade Heat-Driven Cooling and Power System Based on Heat Current Method

An efficient yet accurate optimization algorithm for thermal systems integrating heat current method and generalized Benders decomposition

Thermal system optimization is critical for energy conservation but challenging due to highly complicated systems and nonlinear governing equations. Herein, an efficient yet accurate optimization algorithm based on generalized Benders decomposition (GBD) is developed to address this challenge. It decomposes the entire optimization into a subproblem and a master problem. The subproblem performs the system simulation by developing a hybrid simulation method, which uses GBD and fixed-point iteration sequentially for acceleration. The master problem is constructed based on the gradients of the objective with respect to decision variables, where the solution of every iteration gives an approximation of the optimal solution. The two generated problems are iteratively solved in an alternating manner to converge towards the optimal solution. Test results of a supercritical carbon dioxide recompression system indicate that the hybrid simulation method expands the convergence region to ∼167 % which is nearly 4 times larger than that of the fixed-point iteration, and consumes about 10 % calculation time compared with sequential modular method. The optimization algorithm reproduces the results obtained from the genetic algorithm but reduces the calculation time for an order-of-magnitude and has higher stability. The high efficiency and accuracy suggest the proposed algorithm as a powerful system optimization tool.

Heat flow topology-driven thermo-mass decoupling strategy: Cross-scale regularization modeling and optimization analysis

The liquid desiccant dehumidification (LDD) is both eco-friendly and highly effective in humidity control, widely investigated across diverse angles. This study expands the application of the newly devised heat current method to examine the liquid desiccant dehumidification process. It introduces a new regularized temperature, which includes using a heat flow topology driven thermo-mass decoupling strategy, and constructing the heat current model by defining both the thermal resistance and moisture resistance. It significantly extends the application of the heat current method, clarifying the thermo-mass coupling energy transfer mechanism. The findings indicate that key factors influencing system performance indicators include total thermal conductivity (αA), solution mass flow rate (ms), air-solution mass flow rate ratio (RA/S,D), and heat source temperature (tH). Furthermore, under the influence of distinct thermal conductivities, the optimal output values for performance indicators, including moisture removal rate, exergy efficiency and entransy efficiency, are determined as 8.4 g/s, 71.2%, and 12.3%, respectively. The results of synergistic influence analysis reveal that, for the performance indicator entransy efficiency, msand RA/S,D display a significant degree of synergistic influence, resulting in a strong positive effect and benefiting 68.53% of the total area. Multi-objective optimization indicates a trade-off relationship among the system performance evaluation indicators moisture removal rate, exergy efficiency and entransy efficiency, with optimal solution values of 3.25 g/s, 65.92%, and 12.01%, respectively.

Optimization of the aero-engine thermal management system with intermediate cycle based on heat current method

Reliability and efficiency of the aero-engine thermal management system (ATMS) is of great importance to ensure the required working condition. Conventional methods on modeling ATMS are complex and difficult to solve for optimizing the whole system under multiple conditions. This study combines the heat current method and artificial neural network (ANN) to develop the optimization models with the objectives of maximum heat transfer rate and minimum thermal conductivity respectively. The ATMS experimental platform with intermediate cycle using water as the simulated medium is constructed to verify the optimization reliability. After optimization, the maximum heat transfer rate of ATMS is increased from 7740 W to 8402 W by 8.6%. The minimum thermal conductivity decreases from 1628 W/K to 1032 W/K by 36.6% comparing with the initial working condition. While considering the conditions of artificial control on the fuel oil side, the optimal thermal conductivity decreases from 1628 W/K to 1101 W/K by 32.3%. The optimal findings provide powerful guidance for improving the heat dissipation and reducing weight of the aircraft.

Operation optimization of distributed energy systems considering nonlinear characteristics of multi-energy transport and conversion processes

The various energies in distributed energy system (DES) have different transmission and storage characteristics but are tightly coupled through transport and conversion processes, hindering their accurate and efficient analysis severely. To meet this challenge, this work builds a holistic DES model that fully considers the nonlinearity of energy transport and conversion processes in residential quarters based on the heat current method. A two-layer iterative algorithm is further proposed to realize the efficient optimization calculation, and the operation cost of the DES in the whole day reaches $7873.68 after optimization. The optimization results reveal that the operational states of various devices have established a tight spatiotemporal coupling across different moments and buildings, and the nonlinear characteristics in heat transfer, power transmission, and power-heat conversion processes substantially influence the system's operation. Comparatively, neglecting nonlinear heat transfer constraints results in substantial deviations, with a notable reduction in the fluctuation of heat output from each piece of equipment. The average and maximum relative errors in heat stored within the heat storage device (HS) are 31.9% and 81.8%, respectively. Conversely, overlooking the bus voltage constraint leads to an overestimation of heat stored in HS, with the average relative error in heat stored reaching 49.5%.

Operation Optimization of Thermal Management System of Deep Metal Mine Based on Heat Current Method and Prediction Model

With the increasing depth of metal mining, thermal damage has become a serious problem that restricts mining. The thermal management system of refrigeration and ventilation is an indispensable technology in the mining of deep metal mines, which plays a key role in improving the thermal and humid environment of mines. Optimizing the performance of refrigeration and ventilation systems to reduce energy consumption has become a focus of researchers’ attention. Based on the heat current method, this research establishes the overall heat transfer and flow constraint model of the refrigeration and ventilation system, and proposes an iterative algorithm that combines the refrigerator energy consumption model and the artificial neural network model of heat exchangers. The Lagrange multiplier method is used to optimize the system with the goal of minimizing the total power consumption of the system. The results show that under 9.1 kW cooling load conditions, the total energy consumption of the system reduces by 16.5%, and the COP of the refrigerator increases by 11.6%. The optimization results provide significant guidance for the production and energy consumption reduction of the deep metal mines.

A novel transfer matrix-based method for steady-state modeling and analysis of thermal systems

Performance analysis and optimization of thermal systems are unprecedentedly crucial in pursuing higher energy efficiency. However, the precise modeling and high-efficiency calculation of modern, complex thermal systems are still challenging. Here we present a transfer matrix-based system modeling method to tackle these challenges. The transfer matrix of heat exchangers is defined to describe the temperature mapping relation between inlet and outlet nodes. Heat-work conversion devices are described by the working fluid temperature variation. The system modeling follows a three-step procedure: (1) building system transfer matrix by aggregating component models; (2) separate given and unknown node temperatures by removing redundant rows and columns in the system transfer matrix; (3) rearrange the reduced system transfer matrix to calculate internal and outlet node temperatures. The constructed system model does not introduce unnecessary simplifications and describes the system’s nonlinearity accurately. The proposed modeling method is first presented and validated on a parallel-series and a multi-loop heat exchanger network. Numerical results with both constant and varying fluid properties confirm the method’s validity. Case studies on three thermodynamic systems further validate the method’s capability and efficiency. The proposed method is finally compared with conventional modeling methods and heat current method to highlight its features and advantages.

Experiment and Simulation on a Refrigeration Ventilation System for Deep Metal Mines

Significant harm from heat has become a key restriction for deep metal mining with increasing mining depth. This paper proposes a refrigeration ventilation system for deep metal mines combined with an existing air cycling system and builds an experimental platform with six stope simulation boxes. Using the heat current method and the driving-resistance balance relationship, the heat transfer and flow constraints of the system were constructed. An artificial neural network was used to establish models of heat exchangers and refrigerators with historical experimental data. Combining the models of the system and stope simulation box, an algorithm that iterates the water outlet temperature of the evaporator and condenser of the refrigerator was proposed to design the coupled simulation model. The heat balance analysis and comparison of the air outlet temperatures of the stope, as well as the heat transfer rates of the heat exchangers with the experimental data, validated the coupled simulation model. Additionally, the effects of cooling fans and the air inlet temperature of the cooling tower were discussed, which provided a powerful modelling method for the coupled model of a refrigeration ventilation system, helps to reduce energy consumption, and improves the sustainability of mining production.

Cross-scale modeling and optimization analysis of the solid oxide fuel cell cogeneration system based on the heat current method

The multi-scale, multi-component, multi-process, and multi-parameter characteristics increase intermediate variables and complexity of modeling and analysis of solid oxide fuel cell cogeneration systems. This paper applied the standard thermal resistance for constructing the heat current model to analyze the overall heat transfer performance of the external heat exchangers. On this basis, the research introduced the equivalent electric circuit for presenting the internal electrochemical process and then proposed the overall cross-scale modeling of the solid oxide fuel cell cogeneration system from the internal heat and mass transfer and electrochemical processes to the various external heat exchangers. Moreover, considering the internal and external multi-processes, the system's overall constraints were derived. The simulation results show that the total energy utilization rate of the solid oxide fuel cell cogeneration system is 79.12 %. Besides, the influences of water-to-carbon ratio, excess air coefficient, thermal conductances of each heat exchanger, and ambient temperature on the system performance were developed. The optimal operation parameters are given for improving the maximum net power generation of the system. Finally, the proposed cross-scale modeling method is feasible and convenient for analyzing and improving the solid oxide fuel cell cogeneration system.

Experiment and simulation on a thermal management scheme of intermediate circulation based on heat current method

With the increment of Mach number, the heat dissipation load of aeroengine increases significantly. Systematic thermal management has become an urgent problem to be solved. The intermediate cycle system is one of the widely used thermal management solutions. This paper builds an experiment platform of thermal management system of aeroengine including intermediate cycle to explore the influence of working condition on the systematic heat transportation. Water is selected as the working medium in the experiment. The experiment results show all the temperatures of working medium decrease with the flow rate increment of working medium in fuel oil circuit. The temperature of working medium flowing to the afterburner increases with the temperature increment of lube oil circuit1 and 2. But only the temperature of working medium flowing to the main combustor increases while the temperatures of lube oil circuit1 increase. At last, using heat current method and flow resistance model builds the systematic simulation model. The relative errors between the simulation and experimental values are all less than 5%. The simulation results show all the temperatures of working medium increase with the increment of fuel oil circuit temperature. The working medium temperature flowing to the afterburner and lube oil circuit2 increases with the flow rate increment of lube oil circuit3. It reveals the heat transfer principle of the intermediate circulation thermal system under different working states and provides a powerful guidance for the systematic analysis and design.

Operation optimization of a refrigeration ventilation system for the deep metal mine

With the increment of the depth of metal mines, the energy conservation of refrigeration ventilation for deep metal mines has attracted more attention. This study uses the heat current method and artificial neural network to model the refrigeration ventilation system of deep metal mines, and establishes the systematic flow constraints using the driving-drag balance relationship. A global operational optimization model is built using a Lagrange multiplier method to minimize the pumping power consumption. An iterative algorithm combined with the stope model is proposed by coupling the water outlet temperature of the evaporator and condenser. Subsequently, the optimal frequency of the variable frequency pumps is obtained. The operation of the optimal data on the experimental platform showed that the pumping power consumption of the cooling tower loop decreased the most by 72.84%, and the total energy consumption of system decreased by 25.79%. Additionally, the influences of the inlet air temperature of the air cooler, fan frequency, and inlet air temperature of the cooling tower on the system power consumption are analyzed and provides guidance on energy saving and consumption reduction for refrigeration ventilation systems in deep metal mines.

Decentralized Dispatch of Distributed Multi-Energy Systems With Comprehensive Regulation of Heat Transport in District Heating Networks

Distributed Energy Systems(DES) interconnected with Electric Power Network(EPN) and District Heating Network(DHN) have drawn great attention recently as they promote user-side coordination of multi-energy flows. However, the difference in physical nature between electric power transmission and heat transport has brought difficulties to the modelling and decentralized optimization. In this article, a new DHN model considering delay and storage features of pipeline heat migration and heat transfer between fluids is proposed through trigonometric expansion of the decision series and the heat current method. The model comprehensively characterizes the heat transport in the system and a dispatch problem considering hybrid regulation of fluid flow rates and temperatures in DHN is then established. A primal-decomposition-based decentralized gradient descent method in accompany with Alternating Direction Method of Multipliers(ADMM) is proposed to optimize the DESs in a fully decentralized manner. Case study on two test systems validates the effectiveness of the proposed model and method to further harness the potential of DHN, which reduce renewable energy curtailment by 17.3% and 27.0% respectively.

Matrixed modeling method and entropy generation minimization analysis of heat supply system based on standard thermal resistance

AbstractComplex implicit expressions and many intermediate parameters are not conducive to the application of entropy generation optimization to the performance of thermal and energy systems from component and system perspectives. In this paper, we derived matrix heat transport equations of three primary heat exchanger networks according to the heat current method. Based on the matrix equations, we established the matrixed model of a typical heat supply system and obtained the corresponding matrix equation reflecting the power topology structure of the system. Moreover, we derived and reconstructed a single heat exchanger's entropy generation rate expression based on the standard thermal resistance, which was only related to inlet temperatures, structural parameters, and operating parameters. The total system entropy generation rate was then derived and minimized by the Lagrange multiplier method. The optimization results provided the optimal distribution of the mass flow rate of each fluid. Besides, the influence of the heat transfer rate and outer loop inlet temperature on the optimization results revealed that local equipment parameters and conditions could affect the system's minimum entropy generation. The total entropy generation rate decreases by 17.5% when the outer loop inlet temperature was increased from 274 to 280 K. In conclusion, the matrixed modeling and entropy generation analysis are feasible for thermal system modeling and optimization.

Dynamic flow optimization for a three-loop fluid heat dissipation system in spacecraft

Dynamic optimization of the fluid loop is critical for the active thermal control system (ATCS) for future spacecraft. In this paper, the dynamic heat transfer model of a three-loop fluid heat dissipation system is constructed by the transient heat current modeling method to analyze the optimal control problem of dynamic flow allocation. A sequential quadratic programming (SQP) algorithm combined with the exact external penalty function method is designed to solve the difficulty of temperature path constraints. Simulation results show that the proposed method effectively improves the optimization effect of temperature path constraints and significantly reduces the computational time. Compared with the results of mean allocation flow (unoptimized) and steady flow optimization, the dynamic flow allocation reduced the residual heat by 6.9% and 21.5%, respectively, while meeting all the temperature constraints. In addition, the total flow rate needs to be increased at least by 48% to meet all temperature constraints and achieve similar heat dissipation capacity, when the flow allocation was designed as steady variables. The comparison results indicate that the dynamic flow allocation effectively improves the heat dissipation efficiency of the parallel fluid loop system and ensures the payload temperatures within the constraints.

Simulation and optimization of the waste heat recovery system of the ship power system based on the heat current method

AbstractWaste heat recovery technique is of great importance to improve the coefficient and reduce the emission of greenhouse gas for ship power system. This paper builds the model of a waste heat recovery system of single pressure Rankine cycle with heat current method. Combining with the thermo‐electrical analogy method, the global heat current model of waste heat recovery system is obtained, which indicates the direction of heat flow, the distribution of thermal resistance and the relationship of temperatures. Applying the law of Kirchhoff builds a mathematical model of a system with no intermediate nodes temperatures. Considering the variation of physical property and distribution of thermal resistance in phase change heat exchanger, a double nested iteration solving algorithm is proposed. The results show that the heat transfer rates of economizer, superheater evaporator, condenser, and steam receivers are 9.1, 70.42, 143.89, 19.03, 171.98, and 17.28 kW, respectively. With the objective of maximum output of turbine, applying the genetic algorithm obtains the optimal mass flow rate of cycle water, which is 0.53 kg/s and improves the output of turbine from 53.25 to 147.45 kW. Discussions on the optimization model show that decreasing extraction ratio and increasing the mass flow rates of air discharge of compressor will increase the output work of turbine. Both the optimal mass flow rate of cycle water and maximum output work decrease rapidly at first and then change little while the circulation ratio increases. Particularly, the relative variations of mass flow rate and output work are less than 2% while the circulation ratio is larger than 4.

A comprehensive model and its optimal dispatch of an integrated electrical-thermal system with multiple heat sources

As essential parts of the combined heat supply network with multiple heat sources, the electrical-heating and heat storage technology can simultaneously achieve the goal of clean heating and renewable energy accommodation. The paper introduces the integrated electrical-thermal system with multiple heat sources that consist of combined heat and power (CHP), coal-fired boiler (CB), and electrical boiler (EB) with thermal energy storage (TES). Considering the integration of electrical and thermal networks, we construct a comprehensive model that includes the electrical energy transmission and the overall heat transfer and storage processes based on the heat current method. Based on the comprehensive model, the optimal dispatch of the integrated system is discussed, and an iteration solving method is proposed, which can achieve acceptable convergence and solving efficiency. The simulation results show the combined operation of multiple heat sources has higher system operation efficiency but not necessarily a higher utilization rate of renewable energy. In the test system the combined operation of CHP and coal-fired boiler can reduce the coal consumption of the system by 2%. However, the wind utilization of the system decreases by 4.17%. Moreover, the introduction of an electrical boiler with a TES device can improve the system's flexibility and reduce wind curtailment, wherein the test system is 12.11% more wind consumption. Further, the heat load level can affect the operation efficiency of CHP, the combined operation of multiple heat sources can achieve the balance between reducing coal consumption and increasing renewable energy power generation.

Heat current method-based real-time coordination of power and heat generation of multi-CHP units with flexibility retrofits

Real-time coordination and optimization of multiple combined heat and power (CHP) units under off-design conditions benefits overall efficiency improvement, whereas the coupling of power and heat generations among multi-units makes the system more complex. The existing software cannot tackle model accuracy and prompt optimization simultaneously. Herein, a heat current method-based real-time coordination method of power and heat generation is proposed. An optimization platform consisting of four software modules and corresponding hardware is developed to search for the optimal operating state of multi-units in a CHP plant with flexibility retrofits. After system modeling based on the heat current method, the data acquisition and curation module reads data from the distributed control system (DCS) server and then the parameter identification module provides the characteristic parameters of each component for optimization. The hierarchical and categorized algorithm is applied to solve the heat current-based model of the integrated cogeneration system, and the genetic algorithm is used for optimization. The information output module displays the optimized results on the DCS client interface. The platform is deployed in a practical plant with two connected CHP units. Field test results show that the reduction of standard coal consumption of the whole plant reaches up to 3.10 g/kWh.