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District cooling systems offer a promising alternative to conventional cooling, thanks to overall larger efficiencies and reduced carbon footprint. On the other hand they are characterized by large capital and operational costs that impede their diffusion. Optimizing the design and operation of these systems is therefore fundamental to fully exploit their potential. This paper proposes a novel optimization framework for the simultaneous optimization of design and operation of these systems. The model integrates a genetic algorithm at a master level with Mixed Integer Linear Programming models at a lower level. This approach enables the optimization of various aspects, including network topology, plant locations, supply temperatures and the selection of thermal storage technology. The study showed that in the specific case of Singapore, where the cost for space occupancy is significant, latent heat thermal storages are preferred. In addition, the results highlighted the cost benefits of thermal storage, as district cooling networks lacking it can be from 6.2% to 20.8% more expensive, depending on the scenario. Furthermore, the study demonstrated that the utilization of waste heat through absorption chillers enhances the economic feasibility of district cooling, lowering the payback time by up to 5 years. Lastly, it was observed that 3 °C increase of the indoor set point temperature could reduce the payback time by 3 years and increase the final net present value by 43%, as larger network supply temperatures allow chillers to operate with better performances. The developed model allows to estimate various crucial outcomes with few input parameters, representing a useful tool for both research and planning. • A hierarchical optimization model has been implemented. • NPV can be increased by 43% with an increase of 3 °C of indoor set point temperature. • When waste heat is available, payback time can decrease by up to 5 years. • District cooling without thermal storage is up to 20.8% more expensive. • Electricity cost influences the network topology and storage strategy. [ABSTRACT FROM AUTHOR]

The integration of renewable energy sources into existing district heating systems is imperative for the decarbonization of the global energy system. This transition is particularly challenging in existing systems that were originally supplied by fossil fuel plants and designed to operate with high supply temperatures. Reducing supply temperatures to facilitate the integration of low exergy heat may not be suitable for the existing infrastructure, due to both the heating devices or the thermal substations that may not support significant reductions or to the distribution infrastructure that can be unable to handle the required mass flow rate increases. To address these challenges, this paper focuses on the distribution infrastructure by introducing a physical-based approach to explore the current potential for supply temperature reduction of existing district heating infrastructures, taking into account the hydraulics of the system. Indeed, being able to identify the possible hydraulic bottlenecks arising in the network is essential to enable the transition of the networks and requires an accurate modelling of the fluid dynamic of the system. The methodology is fast and versatile, making it suitable for applications from small-scale to large-scale systems. An application to a real large-scale network is presented, proving the wide applicability of the methodology. Promising results in terms of temperature reduction are shown to be possible: the analyzed infrastructure is currently capable of shifting its operation from 120 °C to about 102 °C without considering invasive structural interventions on the network, and further reductions up to 90 °C are conceivable by assuming some adjustments to the system configuration. [ABSTRACT FROM AUTHOR]

[Display omitted] • The nonlinear model of the thermal network was represented using the Taylor series expansion form. • A multi-layer control framework was defined by the dynamic temporal scales of different devices and processes in HE-IES. • The dynamic thermal storage processes of the thermal network were controlled with CGPC based on continuous time. • A hybrid continuous-discrete time resolution was proposed to reduce the computation complexity of the overall control model. The heat-electricity integrated energy system (HE-IES) presents a promising opportunity for increasing renewable energy generation by fully utilizing the dynamic heat storage capabilities of the thermal network (TN). However, the dynamic characteristics of the TN and the response characteristics of devices in the HE-IES present challenges to system operation and control. To address these challenges, this study proposes a novel multi-layer control strategy that divides the system based on the component response status. The first layer aims to minimize the operating costs of the HE-IES, disregarding any dynamic effects. The second layer optimizes the dynamic operation of thermal subsystems by employing a TN's Taylor expansion model and continuous-time generalized predictive control. The third layer focuses on optimizing the power subsystem to enhance the share of renewable energy generation, using discrete-time model predictive control. To the best of our knowledge, this is the first study that utilizes continuous time models to control the dynamic operation of TNs and their thermal subsystems. Through case analysis, the proposed model achieves a 34.5% reduction in operating costs compared to a single-layer control strategy and a 2.7% reduction compared to a discrete-time multi-layer control strategy. These findings highlight the favorable economic performance of the proposed model. Additionally, the utilization of continuous-time model allows for effective capturing dynamic performance of the TN and enhances its role in system operation. [ABSTRACT FROM AUTHOR]

Due to the flame resistance and lubricity of ethylene glycol solution, an ethylene glycol piston pump can be used as motion sources for extreme operating conditions. In this paper, a novel variable liquid-properties thermal network model (VLTNM) is proposed to analyze the thermodynamic characteristics of piston pump. The VLTNM considers the interaction between the changes in properties of liquid passing through piston pump and the heat generated by motion, and calculates the heat transfer between solid and liquid through a thermal network. A numerical calculation model for VLTNM is established in MATLAB using simscape language, and the results show that the temperature rise of outlet liquid can be reduced by 10.36%, when the thermal conductivity of shell is doubled. The working pressure has a positive effect on temperature variation, which is more significant in high-temperature environments, while the volume fraction of ethylene glycol solution has a negative effect. Additionally, a high load helps to improve the efficiency of piston pump, while the temperature rise caused by high pressure can also reduce the efficiency. When the working pressure increases from 6 MPa to 10 MPa, the efficiency decline of piston pump increased by 1.12%. Besides, comparing the two models of variable and non-variable liquid properties, there is a significant deviation in steady temperature of outlet liquid. The deviation in low temperature is more prominent, with a deviation of 6.1% when the temperature of air is 10 °C. Finally, the predicted steady temperature by VLTNM is in good agreement with the experimental data in reference, with a prediction error of less than 2.01%. [ABSTRACT FROM AUTHOR]

The positioning precision of the ball screw system in machine tools is primarily affected by the thermal deformation of the screw. Hence, the adaptive prediction method must be established to calculate thermal errors of the ball screw system. First, based on heat transfer theory, a new adaptive moving thermal network model of the screw system with moving thermal excitation and varying operating conditions is proposed. The time-serial data of kinematic-pair representative temperatures and the time-serial position data of the moving nut are used as inputs. This adaptive model is used to determine the temperatures of the key elements in the supporting bearings and those of the moving nut and key points of the screw shaft. Further, the heat generation rate of each kinematic pair can be obtained simultaneously. Furthermore, a real-time prediction method of thermal errors of the screw system with moving thermal excitation under various operating conditions is presented. The effectiveness and robustness of the real-time prediction method of thermal errors was verified experimentally. This method is suitable for the rapid prediction of thermal errors of screw systems by monitoring the real-time kinematic-pair representative temperatures and real-time position of the moving nut. • A new adaptive moving thermal network model for a screw system is proposed. • Based on the moving network model, the real-time thermal error model is proposed. • The heat generation rates of the heat sources are simultaneously identified in real-time. • The presented model can be used for the multiple varying working conditions. • This model has self-adaptive ability and robustness. [ABSTRACT FROM AUTHOR]

• Time aggregation for district energy system optimisation. • Optimal selection of representative days, maintaining chronology. • Ability to represent seasonal thermal energy storage. • Validation of optimisation results, 10–30 times faster w.r.t. no time aggregation. • Application in genetic algorithm to design a solar district heating system. The design and operational optimisation of fourth generation district heating networks is a crucial step towards highly renewable energy systems of the future. In order to optimise such complex systems, a toolbox modesto (multi-objective district energy systems toolbox for optimisation) is being developed. Seasonal thermal energy storage is an essential technology to allow larger shares of renewable energy sources, yet large computational power is required for its representation in full-year operational optimisations, as a step towards district energy system optimal design. To decrease computational complexity, a technique with representative days able to include seasonal thermal energy storage systems is developed and validated. This methodology combines different part-solutions from literature, but also adds a novel aspect to safeguard the chronology of the optimisation problem. To validate the approach, the design optimisation of a fictitious solar district heating system with seasonal thermal energy storage is compared to different representative day optimisations in two steps. The operational optimisation is a linear optimisation problem, implemented using modesto; the design optimisation is built as a genetic algorithm, optimising the size of the storage and solar systems in the network. The validation exercise is done for the operational and for the design optimisation separately. This comparative study shows that modelling with representative days adequately mimics the behaviour for the presented case. Furthermore, a solution speed-up in the order of 10–30 times is shown for the representative optimisations with respect to the full year optimisation, in line with the reduction of the number of variables. [ABSTRACT FROM AUTHOR]

Highlights • Models to relate the surrounding and food temperatures was developed and verified. • Multilayers model was used to consider the spatial temperature distribution. • Spatial distribution of heat transfer coefficient was analyzed using simulation. Abstract Multilayer food temperature models considering the spatial temperature distribution in the food were developed to predict temporal temperature changes experienced by food during distribution considering the surrounding temperature, initial food temperature, and the predetermined surface heat transfer coefficient. Parameters used in the models were determined using the results of unsteady three-dimensional computational fluid dynamics simulations for the conjugated heat transfer problem between the food and surroundings. Models were validated by comparing model predictions with the food temperature experimentally measured under fluctuating temperature conditions with a mean absolute deviation of less than 1°C. The developed food temperature model was integrated with a freshness monitoring model to complete the real-time food quality monitoring system. Food quality prediction using the integrated food quality monitoring system was validated for eggs and milk. Quality predictions using the food temperature model showed better accuracy than when using a single point measurement of food temperature. [ABSTRACT FROM AUTHOR]

It is important to have practical methods for constructing and learning a good mathematical model for a building’s thermal system in the presence of unmeasured disturbances and using data from closed loop operation. With this goal in mind, this paper presents a mathematical framework that explains the asymptotic behavior of an estimated model under those conditions and that can aid in learning an accurate model. Some analytic results from the literature of system identification are extended and interpreted for building systems. A new identification approach for determining an accurate thermal network (RC) model for a multi-zone building is developed based on the analytic result, and its superior performance over a conventional grey-box modeling approach is demonstrated experimentally. [ABSTRACT FROM AUTHOR]

Simulation and optimisation of district heating and cooling networks requires efficient and realistic models of the individual network elements in order to correctly represent heat losses or gains, temperature propagation and pressure drops. Due to more recent thermal networks incorporating meshing decentralised heat and cold sources, the system often has to deal with variable temperatures and mass flow rates, with flow reversal occurring more frequently. This paper presents the mathematical derivation and software implementation in Modelica of a thermo-hydraulic model for thermal networks that meets the above requirements and compares it to both experimental data and a commonly used model. Good correspondence between experimental data from a controlled test set-up and simulations using the presented model was found. Compared to measurement data from a real district heating network, the simulation results led to a larger error than in the controlled test set-up, but the general trend is still approximated closely and the model yields results similar to a pipe model from the Modelica Standard Library. However, the presented model simulates 1.7 (for low number of volumes) to 68 (for highly discretized pipes) times faster than a conventional model for a realistic test case. A working implementation of the presented model is made openly available within the IBPSA Modelica Library. The model is robust in the sense that grid size and time step do not need to be adapted to the flow rate, as is the case in finite volume models. [ABSTRACT FROM AUTHOR]

In the present study, a new thermal resistance capacity circuit for the heat transfer modeling in borehole heat exchanger with low computation time is developed. Generally, the thermal circuit models result in sets of ordinary differential equations which are solved numerically. The system of equations derived from the traditional thermal resistance capacity model (TRCM) are usually stiff and lead to unstable results unless for a very small time steps which can increase the computation time significantly. Meanwhile, the system of ordinary differential equations derived from the present model is non-stiff and there is no time step limitation for the stability of the results. It is shown that the present model yields accurate and stable results even for large time steps. Finally, the two-dimensional model is extended to the three-dimensional model. The results of the three-dimensional solution of the present model are in good agreement with the numerical results and experimental measurements reported in the literature. [ABSTRACT FROM AUTHOR]

Optimal design and operation of district heating networks require accurate, but simple models to allow fast simulation. This paper describes the analytical derivation of such a model based on existing work regarding heat loss and dynamic temperature profile calculations in literature. The most important addition from this work is the incorporation and investigation of heat transfer from supply to return side in double pipes, something which is often (over)simplified in more commonly used models. The paper presents the mathematical derivations and the assumptions made in detail for the case of steady-state heat losses in double pipes. The resulting model is carefully examined in a parameter study, from which a number of interesting conclusions can be drawn. Firstly, the heat losses are found to be nearly independent of the mass flow rate in the range of mass flow rates usually encountered in thermal network pipes. The remaining heat loss calculation is simply based on temperature levels and thermal resistance factors, determined by the pipe dimensions and materials. Furthermore, it is found that heat losses from supply to return side should be incorporated in the analysis for better accuracy of the results, even more so with the increasing popularity of twin pipes with common insulation. [ABSTRACT FROM AUTHOR]

A novel CHP configuration is presented, which is fueled by low-temperature geothermal energy and delivers heat to a district heating (DH) system.This so-called “Preheat-parallel” configuration has a higher net electrical power output ( W ̇ net ) and a higher exergetic plant efficiency ( η ex ) than the convenient series and parallel configurations for the connection to a state-of-the-art 75/50 DH system.For the considered cases, W ̇ net and η ex are 1.3–6.4% and 0.4–1.9%-pts higher than for the parallel configuration, respectively.The highest values correspond to the highest heat demand.With respect to the series configuration W ̇ net and η ex are 2.1–9.9% and 0.7–3.0%-pts higher, respectively, where the highest values correspond to the lowest heat demand.Furthermore, the optimal CHP configuration - series, parallel or “Preheat-parallel” - is discussed.The optimal configuration depends on the DH system requirements.Supply and return temperatures in the range of T supply = 40 – 110 ° C and T return = 30 – 70 ° C are considered.We conclude that the series and parallel configurations have the best performance for the connection to low-temperature and high-temperature DH systems, respectively.However, for a wide range of T supply and T return , the “Preheat-parallel” configuration is the most appropriate.The preheating -effect is the main feature of the “Preheat-parallel” configuration, and is more useful for a large temperature difference T supply - T return and for low values of T return .Furthermore, we found that for high heat demands and small temperature differences T supply - T return , the “Preheat-parallel” or series configurations might perform better than the parallel configuration for the connection to a high-temperature DH system. [ABSTRACT FROM AUTHOR]

Simple models used for the simulation of the thermal performance of buildings usually assume constant (time-invariant) values of their parameters. This paper presents the simple and efficient solution for the simulation of the thermal performance of the building with the time-varying parameters of its thermal network with the use of the Matlab/Simulink. The lumped parameter thermal model taken from EN ISO 13790 was used to build the simulation model in the state space. Then it was validated for two different ventilation schedules, each for 20 European cities. Reference results of the annual heating and cooling needs were taken from the EnergyPlus detailed simulation, showing satisfactory accuracy of the developed model. An error analysis of the hourly indoor air temperature prediction was also performed. For this purpose, statistical goodness-of-fit criteria were used: the Mean Square Error (MSE), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Mean Absolute of Percentage Error (MAPE) and coefficient of determination (R 2 ). These metrics showed a very good quality of prediction of the presented model. [ABSTRACT FROM AUTHOR]

The development of a dynamic thermal battery model for hybrid and electric vehicles is realized. A thermal equivalent circuit model is created which aims to capture and understand the heat propagation from the cells through the entire pack and to the environment using a production vehicle battery pack for model validation. The inclusion of production hardware and the liquid battery thermal management system components into the model considers physical and geometric properties to calculate thermal resistances of components (conduction, convection and radiation) along with their associated heat capacity. Various heat sources/sinks comprise the remaining model elements. Analog equivalent circuit simulations using PSpice are compared to experimental results to validate internal temperature nodes and heat rates measured through various elements, which are then employed to refine the model further. Agreement with experimental results indicates the proposed method allows for a comprehensive real-time battery pack analysis at little computational expense when compared to other types of computer based simulations. Elevated road and ambient conditions in Mesa, Arizona are simulated on a parked vehicle with varying quiescent cooling rates to examine the effect on the diurnal battery temperature for longer term static exposure. A typical daily driving schedule is also simulated and examined. [ABSTRACT FROM AUTHOR]

The present study explores the implementation of district heating and cooling systems across a broad set of case studies reported in the literature. Topics addressed include their history, system identification, energy sources, design considerations, environmental impact, economic feasibility, performance analysis and the role of energy policy. The history of district heating and cooling systems reveals how available technology has influenced the configuration of district energy systems as more efficient and cleaner methods of providing heating and cooling have arisen. This leads to system identification based on primary energy sources, including the deployment of more and more renewable energy streams. Advantages and disadvantages of each energy source are examined in detail. Policies created by government and international entities will have a major impact on the future of research and development in district energy systems. Incentives may become necessary for creating favorable conditions for the efficient construction and utilization of district heating and cooling. Outcomes of these policies influence design considerations underlying any district energy system and their contribution in sustainability. Studies on greenhouse gas emissions along with the economic impacts of district energy construction are part of the design process and optimization of district energy systems should include economic and environmental considerations and not solely thermal efficiency. District heating and cooling systems are often integrated with components such as absorption chillers, cogeneration and thermal energy storage. Performance analysis using exergy and energy analysis have revealed several sources of irreversibility in district heating systems with these elements. If understood properly, these can greatly enhance system operation. Awareness and accommodation of the many factors discussed in this paper can improve the soundness of any district heating or cooling installation. [ABSTRACT FROM AUTHOR]

This paper proposed a two-dimensional thermal network model to predict the output of the finned tube energy storage system during the melting stage to solve the fast calculation of latent heat storage cooling equipment for high-energy airborne weapons. The thermal network model introduces effective thermal conductivity to consider the effect of natural convection on the melting of PCM. Numerical simulation and experiment verify the accuracy of a single tube under various working conditions and actual size heat exchangers, respectively. Compared with single-tube numerical simulation, the maximum average outlet temperature error is 0.634 °C, saving 99% of the simulation time. Compared with the experiment, the maximum temperature error of outlet temperature is 4.91%, and the average temperature error is 1.18%. Results are found to be in good agreement with numerical simulation and experiment. The performance of heat exchangers is evaluated by effectiveness under different conditions, including fin geometry, material, and periodic inlet. The results show that the structure with smaller fin thickness and interval has better effectiveness and latent heat storage, more benefits from increasing the fin thermal conductivity, and better stabilizes the outlet under the periodic inlet. It provides a reference for designing and optimizing energy storage systems. • A thermal network model for the finned tube latent heat storage system is established and verified. • The model considers natural convection, and the maximum experimental error of outlet temperature is 4.91%. • The model can save 99% of calculation time compared with the enthalpy-porosity method. • Optimize and analyze the actual size of the heat exchanger. [ABSTRACT FROM AUTHOR]

A simple mathematical model of a passive solar house is proposed. The physical model is the house integrated with a color-changed solar wall. Steady state heat transfer equations were set up to determine the temperatures of surfaces and air by using a thermal resistance network. The equations were solved using a Matlab procedure. Satisfactory correlation was obtained with experimental data. The optimization methods for thermal performance of passive solar houses will be presented in further work. [ABSTRACT FROM AUTHOR]

Identification approaches applied to semi-physical thermal network structures, so called gray-box modeling approaches, are popular in building science for energy audits, retrofit analysis and advanced building controls, e.g. model predictive control. However conventional identification approaches applied to thermal networks fail when there are significant unmeasured heat gains that influence building responses. This paper presents a method to obtain improved gray-box building models from closed loop data having significant unmeasured disturbances. The method estimates both physical parameters of a building thermal network model and also a disturbance model that characterizes the unmeasured inputs. The performance of the algorithm is demonstrated using numerical and experimental results. [ABSTRACT FROM AUTHOR]

Urban energy management nowadays has put more focus on residential houses energy consumption. Lots of machine learning based data-driven approaches have the abilities to characterize and forecast total energy consumption of commercial data. However, a paucity of research applying data-driven methods have been tested on the hour ahead energy consumption forecast for typical single family houses in the US. With the advances in smart metering, sub meter usages forecast in household-level is also getting more and more popular on smart building control and demand response program. The situation here inspires us to develop a hybrid model to address the problem of residential hour and day ahead load forecasting through the integration of data-driven techniques with a physics-based model. In this article, we report on the evaluations of five different machine learning algorithms, artificial neural network (ANN), support vector regression (SVR), least-square support vector machine (LS-SVM), Gaussian process regression (GPR) and Gaussian mixture model (GMM), applied to four residential data set that contains smart meters. Both total and non-air conditioning (AC) power consumption are forecasted for hour ahead and 24-h ahead. The variation of patterns captured from non-AC part is further input as internal heat gain to a physics-based model. The model uses a 2R-1C thermal network and an AC regression model. By utilizing this hybrid approach, we get AC load prediction and non-AC energy forecast simultaneously. Total energy consumption is further produced by summing up the two sub meters forecast for hybrid model. The results from new modeling are compared with those from pure data-driven techniques. The final result showing improvements of coefficient of variance between the best data-driven model and hybrid model are 6–10% and 2–15% for hour ahead and 24-h ahead, respectively. [ABSTRACT FROM AUTHOR]

Under long-term thermal cycles, the solder layers in IGBT modules degrade inevitably, which affects their heat dissipation performance and eventually leads to the failure of IGBT modules. In order to monitor the degradation degree of the IGBT chip solder layers according to the junction temperature, a thermal network model for monitoring the IGBT chip solder degradation based on feedback PI control is proposed. Firstly, the finite element simulation model of the IGBT module is established and the degradation degrees of the chip solder layers are defined in the simulation model. Then the thermal network model is extracted according to the finite element simulation model and the thermal impedance functions are fitted from the different power loss and chip solder degradation degrees. Meanwhile, a control loop with PI controller is established to regulate the thermal impedances. Finally, the accuracy of the proposed thermal network based on feedback PI control for chip solder degradation monitoring and junction temperature calculation is verified under different chip solder degradation degrees. • The specific degradation of chip solder is defined in IGBT module. • A thermal network based on feedback PI control is proposed. • The proposed thermal network can monitor the chip solder degradation degree. [ABSTRACT FROM AUTHOR]

This paper reviews the physical mechanisms and compact modeling approaches of two physical damages in MOS devices induced by electrostatic discharge (ESD) stresses; namely gate oxide breakdown and thermal failures. Theories underlying the failure mechanism are discussed and compact models that can be used to monitor ESD induced gate oxide breakdown and thermal failure are developed. Related work reported in the literature is discussed, and benchmarking of measurement data versus simulation results are included in support of the modeling work. [ABSTRACT FROM AUTHOR]

• Importance of contact orientation to anisotropic thermal conductivity is analysed. • Directed weighted thermal network is used to identify shortest heat transfer paths. • A directed thermal resistance is extracted from the new directed thermal network. • Directed resistance involves particle connectivity, contact quality and orientation. • Directed thermal resistance is well related to anisotropic thermal conductivity. The effective thermal conductivity of a granular material varies with the predominant heat transfers direction. The anisotropic effective thermal conductivity is known to be dominated by the microstructure in a dry material. However, no microstructural parameters that are well related to thermal anisotropy have been proposed. After analysing the heat transfer mechanisms at the particle scale, this work constructs new directed weighted thermal networks for both lattice and randomly distributed sphere packings, by considering particles as nodes and local heat transfer paths with thermal resistance as directed edges. With the implementation of graph theory to the directed weighted thermal networks, the shortest preferential heat transfer paths between nodes paired at opposite faces of a sample across the driving temperature gradient direction are identified. Based on the shortest heat transfer paths, a new sample-scale feature named " directed network thermal resistance " is computed for each sample. This new parameter accounts for particle connectivity, interparticle contact orientation and contact quality simultaneously. After computing the effective thermal conductivity of each sample in different directions using a weighted thermal network model, it is found that directed network thermal resistance is inversely proportional to anisotropic effective thermal conductivity. [ABSTRACT FROM AUTHOR]

The thermal losses in buildings are significant energy sinks. The Energy Semantic Network (ESN) is a new method for finding these losses at the design stage, as well as for the existing structures. The research purpose of ESN is to take into consideration the governing factors of building thermal performance (i.e. the insulation materials, the dimensions, the loads, and the schedules of people interactions), associate these factors with any building of choice, and to subject the model to range of dynamical changes, that will help to make the decisions for improving the building thermal performance. The current work is only an early stage on ESN, the end goal of ESN is to evaluate the thermal energy conservation technologies with respect to the dynamical thermal changes, and track the dominant sinks resulting from these changes. Currently, the energy conservation technologies present an opportunity for reducing the utility use, and, thereby, the savings in capital for long term performance. The thermal energy conservation problems are unique to every building, due to the storage and the supply of the energy in response to the seasonal demands, structure, and the nature of the building utilization (the involvement of people). With the current simulation software, such as Energy Plus, there exists a convenient way of simulating the annual building performance, without the tediousness of monitoring the physical building. However, in that case, any particular spontaneous effects may not be completely accounted. The ESN structure is intended to make up for the spontaneous effects, and be accountable for possible spikes in the energy use that may occur throughout the year. Such spikes in energy consumption do not have to be singular, because it is possible to assign an array of situations where energy losses occur and track them to the specific location. The use of ESN for tracking the energy losses can lead to a solution for preventing similar spikes in the future by isolating the most significant sink. The enclosed research on the ESN method includes the foundations of ESN, the case study of a hypothetical hotel located in Ontario, and a detailed Simulink representation of ESN. [ABSTRACT FROM AUTHOR]

Due to the cyclical nature of the high pressure casting process, there will be a thermal periodic steady state of the high pressure die casting dies (hpdc-dies) during operation. A continuous temperature pattern (as a function of time), that is recurring during each process step can be observed. The quality of the castings as well as the life span of the tools is highly dependent on these periodic temperature patterns. It would be state of the art to simulate the hpdc-process with highly-specialized process simulation software. However, because of the high initial costs and the necessary human and computational resources, their use during operation to adjust the parameters of the cooling management is generally not utilized. Instead, the input parameters of the cooling management are chosen by trial and error. This paper focuses on the development a simple linear thermal model to describe the temperature patterns within the die. This is helpful to control the cooling management more effectively during operation. Approaches of dynamic systems simulation are used to create a model of the energy transport phenomena within the hpdc-die. Here it is shown in general terms how to model fluid-cooled solids by the combination of n sub process steps in n state space models to depict the whole thermal cyclical process. The set up of sets of balance equations are shown with a simplified example, using formal matrix operations. The obtained results of the simulation are discussed and evaluated. The conclusions of measured data from the experimental hpdc-die are compared to the solution of the simulation using the thermal model approach described above. [ABSTRACT FROM AUTHOR]

Highlights: [•] More precise but still simple SPICE like model of the power MOSFET is presented. [•] Results prove the importance of temperature dependent resistors in the thermal network. [•] Importance and correctness of added buried heat source is shown. [•] Model is able to simulate destruction of the device during UIS with very good accuracy. [•] Comparison with analytical models was done and better accuracy was observed. [ABSTRACT FROM AUTHOR]

Highlights: [•] Grid configurations of TESs are developed and assessed. [•] Characteristics of various configurations of TESs are developed as functions of properties. [•] Functions for the discharge temperature and the discharge energy of the TES are developed. [ABSTRACT FROM AUTHOR]

Highlights: [•] Investigation of temperature profiles and thermal transients in Si power MOSFET. [•] New Cauer thermal network to predict longitudinal temperature profile as a function of time. [•] Thermal RC elements calculated assuming cylindrical heat propagation. [•] Thermal transient predicted compared with numerical electro-thermal simulations. [•] Accuracy of the thermal network increases by increasing the number of RC elements. [ABSTRACT FROM AUTHOR]

Abstract: Thermal load calculation based on dynamic models is widely used in simulation software and it is the method recommended by ASHRAE (American Society of Heating, Refrigeration and Air-Conditioning Engineers) and CEN (European Committee for Standardization, in French: Comité Européen de Normalisation). The principle is to make the heat balance for the air volume of a room space considered at uniform temperature and to calculate from this equation the load, i.e. the power needed to obtain the required indoor temperature. The problem is that, by doing so, the physical causality is not respected. If the model is approximated by a piece-wise linear dynamical system, this procedure results in an improper transfer function in the case of non-negligible thermal capacity of the indoor air. In order to point out this problem, a method to obtain state-space and transfer function models from thermal networks is introduced. Then, the transfer function representation is employed to show that changing the physical causality results in an improper transfer function. The practical consequence is that when the space temperature has a step variation, the calculated load tends to infinity if the simulation time step approaches zero. The issue of causality may be a problem in equation-based simulation software, such as Modelica, in which the equations do not represent causal relations: a wrong choice of the causality in a balance equation may result in an improper transfer functions. [Copyright &y& Elsevier]

Abstract: Domed roofs have been used in Iran and many other countries to cover large buildings such as mosques, shrines, churches, schools. They have been also employed in other buildings like bazaars or market places in Iran due to their favorable thermal performance. The aim of this research is to study about domed roofs thermal performance in order to determine how they can be helpful in reducing the maximum air temperature of inside buildings during the warm seasons considering all parameters like air flow around them, solar radiation, radiation heat transfer with the sky and the ground as well as some openings on the building. The results of the study show that the thermal performance of the investigated domed roof is better than the building with flat roof, particularly when the dome is covered with glazed tiles. In addition to their aesthetic values, domes covered with glazed tiles have thermal benefits of keeping the inside air of these buildings relatively cool during the summer. Moreover, openings cause passive air flow inside building, which is helpful for human comfort. [Copyright &y& Elsevier]

Abstract: Thermal actuators are extensively used in microelectromechanical systems (MEMS). Heat transfer through and around these microstructures are very complex. Knowing and controlling them in order to improve the performance of the micro-actuator, is currently a great challenge. This paper deals with this topic and proposes a dynamic thermal modelling of thermal micro-actuators. Thermal problems may be modelled using electrical analogy. However, current equivalent electrical models (thermal networks) are generally obtained considering only heat transfers through the thickness of structures having considerable height and length in relation to width (walls). These models cannot be directly applied to micro-actuators. In fact, micro-actuator configurations are based on 3D beam structures, and heat transfers occur through and around length. New dynamic and static thermal networks are then proposed in this paper. The validities of both types of thermal networks have been studied. They are successfully validated by comparison with finite elements simulation and analytical calculations. [Copyright &y& Elsevier]

Abstract: A two dimensional lumped parameter model (LPM) which provides the steady state solution of temperatures within axisymmetric single-sided, slotted axial flux generators is presented in this paper. The two dimensional model refers to the heat modelling in the radial and axial directions. The heat flow in the circumferential direction is neglected. In this modelling method, the solid components and the internal air flow domain of the axial flux machine are split into a number of interacting control volumes. Subsequently, each of these control volumes is represented by thermal resistances and capacitances to form a two dimensional axisymmetric LPM thermal circuit. Both conductive and convective heat transfers are taken into consideration in the LPM thermal circuit by using annular conductive and convective thermal circuits respectively. In addition, the thermal circuit is formulated out of purely dimensional information and constant thermal coefficients. Thus, it can be easily adapted to a range of machine sizes. CFD thermal modelling and experimental testing are conducted to validate the temperatures predicted from the LPM thermal circuit. It is shown that the LPM thermal circuit is capable of predicting the surface temperature accurately and potentially replacing the CFD modelling in the axial flux machine rapid design process. [Copyright &y& Elsevier]

Abstract: A new improved solution, Detached Variables-Parameters Coefficient (DVPC) method and Monte Carlo Ray Tracing (MCRT) method, is proposed to solve a thermal network problem in heat-transfer analysis of spacecraft. DVPC method emphasized directly on correcting the key Solar Absorption Coefficient (SAC) material parameter rather than the network conduction and radiation coefficients generally. MCRT method is contributed to reducing computation assumption and clarifying physical concepts and used to solve solar direct incidence area and network radiation transfer coefficient with different round circular angles and zenith angles of solar incidence radiation. Numerical simulation is carried out for temperature distribution of satellite. In steady stage, maximum temperature difference reaches up to 200 K and increasing the radio of absorptivity to emissivity will lead to temperature rise rapidly. In unsteady stage, maximum temperature value of satellite main body is lager than that of solar array. To begin with, cooling velocity increased rapidly and got to maximum value, then descended slowly and reached up to steady stage with 17 K discrepancy. Meanwhile, increasing SAC is better than that of decreasing to true value. [Copyright &y& Elsevier]

Abstract: A thermal network model is developed for studying the temperature variation of complicated structure satellite surfaces. The solar incident areas, the infrared and solar radiation transfer coefficients among surfaces are numerically simulated by means of Monte Carlo ray tracing (MCRT) method in model. The non-uniformity and the instability of solar radiation, which plays the important roles in simulating outer-space heat flux designation parameters by solar simulator, are studied for analysis variation of antenna temperature fields in detail. Results showed non-uniformity irradiation effects are greater than those of instability for this kind of geometry sheltering structure. [Copyright &y& Elsevier]

In densely populated areas, district energy systems can bring significant savings and an overall reduction of CO2 emissions. In particular, district cooling is a valid alternative to conventional cooling technologies. Among the issues related to district cooling there is the relative smaller temperature difference between supply and return respect to district heating. This increases the design and operational costs. Consequently a strong focus is needed on the optimization of district cooling networks. In this paper a mixed integer linear programming model (MILP) and a heuristic model have been developed and implemented for the topology optimization of district cooling networks. The models allow to estimate: (i) the optimal design, (ii) the set of buildings that is convenient to connect to a district cooling network. They have been applied to three different case studies and the main results obtained by the two methods have been assessed and compared. The heuristic method proved to be faster, especially for complex networks. On the other hand, the MILP is more precise and the maximum difference among the models in terms of objective function is about 1.3%. A graph clustering method has also been implemented to improve the performances of the heuristic approach by facilitating its convergence.The models through the optimizations can bring savings up to 3.16% of the total life-cycle cost depending on the case study. They could therefore represent a potential tool that supports decision makers in the planning phase of district cooling networks. • A MILP and a heuristic model were developed to optimize district cooling systems. • Topology, connections and diameters are optimized while respecting nonlinearities. • The heuristic is less accurate, but 98% faster than the MILP. • The models can bring savings up to 3.16% of the total life cycle. [ABSTRACT FROM AUTHOR]

[Display omitted] A low-cost lumped parameter model (LPM) is developed to simulate hydrogen storage in solid-state materials. The proposed LPM is a zero-dimensional model based on an analogous transient thermal resistance network that considers the whole storage system as a resistor–capacitor (RC) circuit with a current source. Combined with the mass conservation, sorption kinetics, and equation of state, the LPM is capable of predicting key thermofluidic quantities of the storage system, such as the storage bed temperature and pressure, hydrogen fraction and flowrate, and storage tank temperature. To test the applicability of the LPM, chemisorptive (Mg and LaNi 5) and physisorptive (activated carbon) solid-state materials are simulated for adsorption and desorption processes. For both material types, LPM achieves predictive accuracies comparable to three-dimensional computational fluid dynamics (CFD) simulations, especially for hydrogen fraction and storage times (with maximum errors less than 9.6%), for a fraction of the computational cost (23,734 times lower memory requirement and 126 times faster calculation time). In addition, several formulations of the bed thermal resistance are proposed and discussed in terms of their impact on the accuracy of the LPM predictions. For slender cylindrical tanks, an equivalent annulus formula achieves the best balance of simplicity and accuracy. [ABSTRACT FROM AUTHOR]

• Macro and micro-geometry parameters are used as decision variables. • Study of the impact of taking the complete transmission by two approaches. • The using of a genetic algorithm NSGA-II. This study aims to implement multi-objective optimization of a gear unit in order to minimize the power loss and the vibrational excitation generated by the meshing, via a multi-scale approach that extends from gear contact to the complete transmission. All these indicators are closely linked to the macro and micro-geometry definition of the gear pair. The optimization is carried out using a genetic algorithm, namely the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). The design variables chosen for the problem are the pressure angle and the helix angle, as macro-geometry characteristics of the gear, and/or the length and the amount of tooth profile modifications, as micro-geometry characteristics of the gear. Constraints are imposed in order to not exceed a maximum bending stress at the tooth root of the gear and to not fall below a minimum total contact ratio. From the results obtained, it is found that the multi-objective optimization with both micro and macro-geometry parameters simultaneously gives different results than those obtained with macro-geometry first and then micro-geometry parameters. In order to study the importance, or not, to take into account the complete gear unit, a comparison is made between the local power loss generated by gear tooth friction and the total power loss in the single stage gear unit in terms of design variables values. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, the use of an uneven nodal network in floor heating simulation with finite difference heat balance method is examined. Two floor heating test cases, homogenous and multilayer floor, are presented. Temperature distributions on the floor surface and heat flows through the floor surface are simulated with even and uneven gridding approaches. It is shown that the total number of nodes can be reduced by placing the densest gridding in sections where the curvature of the temperature gradient is steepest. [Copyright &y& Elsevier]

Optimal operation of generation units is crucial when looking for reduction in energy consumption and carbon emissions in multi-energy systems (i.e. multiple generation sources, energy networks and storages). This work proposes an innovative optimization approach that can be applied to energy systems composed by multiple small units for the production and conversion of electricity, heating and cooling. The optimization is conducted acting on the operation of the production units, the capacity and operation of thermal storage units and the application of demand side management to the thermal network. The optimization procedure is based on a two-level approach, combining a genetic algorithm and a linear programming approach and including a physical model of the district heating network. Multiple scenarios corresponding with typical days are considered. An application to a realistic system, which is optimized assuming an economic objective function, is performed. Results show that thermal storage installation can reduce costs of about 1.5 %, while its integration with demand-side management leads to a cost reduction up to 4 % and allows reducing the storage size. • A methodology for optimal operation of multi-energy systems is proposed. • The approach includes thermal demand management and storage installation. • The dynamics of the heating network are simulated by means of a physical model. • An application with heating, cooling and electricity demands is investigated. • The economic benefits related with flexible production are quantified. [ABSTRACT FROM AUTHOR]

Fast prediction of thermal behaviour of buildings and substation connected to district heating systems is an important aspect for implementing technique aimed at reducing primary energy consumption and consequently pollutant emission, such as demand side management, network expansion, renewable sources penetration, integration of waste heat. In this work, an approach to model the end-users connected to a district heating network (each building and each substation) is proposed. A physical model is used, which is calibrated through a proper approach using experimental data. The main strength of the work is that only data that are usually measured in district heating substations (temperature and mass flow rates in the substation) and building volume are required to obtain the model. This makes the model creation and its use automatic and applicable to a wide range of district heating systems also in case other data are not available. This characteristic is essential to make the model suitable for large networks including various thousands of substations. Results show that the model allows simulating the effects of modifications in district heating system operations in terms of building thermal request and temperature variation with an average errors lower than 5% for all the measures analysed. [Display omitted] • An approach to fast model buildings connected to district heating is proposed. • The model includes the entire building and the thermal substation. • The only requirements are volume and substation data (temperature and mass flow). • The automatic model creation makes the approach proper for large networks. • Results shows that average errors on the predicted quantities are lower than 5%. [ABSTRACT FROM AUTHOR]

In district energy applications, implementation of management strategies is crucial to achieve reductions in primary energy consumption and carbon dioxide emissions. The development of optimization tools to upgrade the operation of smart energy systems should take into account all the relevant elements of these complex infrastructures. In this paper, a global optimization approach, applied to district heating, cooling and electricity networks interconnected to each other, is proposed. The suggested approach combines the optimization of the production side, useful to understand how it is convenient to produce heat, cold and electricity, with demand-side management for district heating customers. This is reached by using a bi-level optimization structure, exploiting the genetic algorithm and linear programming. A physical model of the district heating network is included in the procedure to accurately reproduce the effects of demand-side management. The tool can be applied to different objective functions. In this paper, a multi-objective optimization is carried out with two different objective functions: the operation cost and the carbon dioxide emissions. Results show that, by choosing an intermediate trade-off among the two goals, it would be possible to have a 12% reduction in the emissions at the expense of a 25% increase in the operating cost. • A multi-objective optimization approach for multi-energy systems is proposed. • The approach allows the simultaneous optimization of production and demand. • A bi-level structure including genetic algorithm and linear programming is used. • Thermo-fluid-dynamic effects of demand response in heating networks are considered. • A case-study is analyzed considering both the economic and environmental aspects. [ABSTRACT FROM AUTHOR]

• Heat pipe cooling system allows for passive molten salt reactor cooling. • System allows significant reduction in the plant's overall auxiliary load. • Thermal network model shows highly efficient heat transfer form reactor to steam cycle. A Molten Salt Reactor (MSR) cooling concept is presented, using passive Multiple Evaporator and Condenser Loop Thermosyphons (MECLTS) to transfer heat from the reactor core to the steam cycle. This concept allows for the intermediary coolant salt system to be eliminated, reducing the associated auxiliary power load. Heat transfer using the MECLTS cooling method is investigated using a thermal network approach, and results are compared to a conventional active MSR cooling concept. In a conceptual 450 MW th MSR power plant the passive MECLTS cooled MSR improved net power output from 200 to 206.8 MW e compared to the conventional active cooling system. [ABSTRACT FROM AUTHOR]

Solder voids has an important impact on healthy operation of insulated-gate bipolar transistor (IGBT) modules, but voids damage is difficult to be estimated accurately by conventional methods due to the lack of calculation in mutual thermal effect between chips. So this paper proposes a base solder voids identification method by using case temperature, takes into account both self-thermal diffusion and coupling inside module, and adopts case temperature distribution on bottom of baseplate to assess voids damage indirectly. Firstly, finite element method (FEM) of IGBT module with base solder voids was established to study junction and case temperature response with different voids distribution, the practicability of base solder voids identification based on case temperature is verified. Then the influence mechanism of voids on case temperature was discussed theoretically, voids identification is extended to dynamic load conditions, temperature-to-thermal resistance conversion and dynamic thermal resistance reference calibration with different power loss ratio were realized by improved thermal network, recursive least square (RLS) algorithm was designed for dynamic identification of real-time identifiable thermal resistance, the difference between RLS results and thermal resistance reference was compared to confirm the severity of base solder voids, two or more groups of comparison results with different power conditions are used to complete the voids analysis. Finally, validity of proposed method is demonstrated by simulation. Compared with conventional method, it shows better ability in dynamic identification. • Influence of power distribution between chips on identification is considered. • Improved thermal network is used to illustrate base solder voids effect on case temperature. • Propose a complete base solder voids identification and voids effect analysis process. [ABSTRACT FROM AUTHOR]

Keeping the highest junction temperature of Insulated Gate Bipolar Transistor (IGBT) modules below the critical temperature is the key to ensuring the stability and reliability of power supplies in accelerator facilities. However, the existing junction temperature extraction methods are not suitable for liquid cooling IGBTs and can be improved in terms of speed and accuracy. In order to investigate the junction temperature of IGBT modules and the characteristics of their water-cooled plates, an electro-thermal model combining the thermal network method and the computational fluid dynamics analysis is proposed. Because the power loss is corrected by the double-pulse test, and the thermal resistance of the cold plate is improved by computational fluid dynamics simulation, the accuracy of the model is improved. The thermal network method guarantees that the model is fast and can be easily applied to various operating conditions. The method is used to analyze the performance of two cold plates, select the cooling conditions, and further increase the switching frequency on the premise of ensuring the reliability of the IGBT module. The accuracy of the method has verified by experimental results, and the applicable conditions and the estimated junction temperature error are also analyzed. [ABSTRACT FROM AUTHOR]

To aid in the integration of renewable and residual energy sources in the energy system, energy flexibility is required. By charging and discharging energy storage, energy flexibility can be created and heat demand and heat generation can be matched in time. One possible source of energy flexibility is the thermal capacity of the water in district heating network pipes. Effective use of this thermal energy storage requires efficient techniques to determine the available flexibility. The goal of this paper is to determine the required level of detail of a substation model to characterise network flexibility through simulation. The substation models differ in the assumptions that are made and range from a detailed, non-linear model to a simple, linear model. To analyse the results, we identify different phases occurring during a network flexibility activation. By determining if reduced models are as effective in reproducing important flexibility characteristics as more detailed and computationally expensive models, network flexibility characterisation can be simplified and sped up. Results show that the network flexibility can be adequately characterised even with very simple models, provided correct assumptions are made. • Four substation models are evaluated for network flexibility characterisation. • The concept of network flexibility phases is introduced. • The substation models are analysed using these phases. • Results show that a good primary return temperature estimation is crucial. • Some phases show a higher sensitivity to errors in primary return temperature. [ABSTRACT FROM AUTHOR]