TRNSYS Model Research Articles

Optimizing Energy Efficiency with a Cloud-Based Model Predictive Control: A Case Study of a Multi-Family Building

The Energy Performance of Buildings Directive (EPBD) has set a target to achieve carbon-neutral building stock and generate 80% of its electricity from renewable sources by 2050. While Model Predictive Control (MPC) can contribute significantly to energy flexibility in buildings, its remote implementation remains relatively unexplored, especially in the residential sector. The purpose of this research is to demonstrate the reliability, robustness, and computational efficiency of a cloud-based application of an MPC called Smart Energy Management (SEM) on a multi-family residential building. The SEM was tested on a virtual building model in TRNSYS using an open-source distributed event streaming platform for data exchange and synchronization. Simplified models for thermal behavior prediction, including an R3C3 model of the building, were developed in C++. The SEM was evaluated in eight scenarios with varying weather conditions, optimization criteria, and runtime periods. The results demonstrate that the SEM maintains stability and robustness over a 2-week period with a 15-minute planning resolution while ensuring thermal comfort. The C++ implementation of the optimization algorithm enables SEM deployment on low-spec servers, supporting cost-effective applications in real buildings with minimal intervention.

Application of heat pump assisted solar evacuated tube water heater operated within passive solar house in severe cold region

Replace coal with solar energy to low-cost heating in severe cold regions can improve indoor air quality, but indoor thermal comfort is not fully guaranteed. Therefore, a dual-source heat pump (DSHP) assisted solar evacuated tube water heater heating system was used in a house with sunspace to meet the heating stable and cleaning. TRNSYS model verified by experiment was used to research performance and economy of system. Results found the higher ambient temperature and solar radiation, the more heat from sunspace, solar assisted heat pump (SAHP) and solar water heater, conversely, the longer heating time of air-source heat pump (ASHP). During heating season, solar fraction of heating was 51.6 %, solar heat collection efficiency was 46.0 %, EER was 3.35, COP were 2.81 (ASHP) and 3.65 (SAHP). Heating time proportion of ASHP, SAHP and solar water heating were 15.0 %, 40.3 %, 44.7 %, ASHP heating was accounting for 22 % and 50 % in November and January. The system, sunspace supplied 16707.1, 2307.6 kW h of heat for room, solar effective heat collection was 10107.0 kW h, power consumption was 5164.7 kW h, CO2 emission reduction was 14232.4 kg. The dynamic payback period of system was 6.78 years, as will be shortened with support of clean energy heating policy.

Energy, economic and environmental analysis of a photovoltaic-thermal integrated dual-source heat pump system under a system coefficient of performance − based switching strategy

The photovoltaic-thermal integrated dual-source heat pump system can offer performance improvement by addressing the limitations of a single heat pump system, which not only improves energy efficiency and system performance but also reduces pollutant emissions. However, the operational performance of the system is significantly affected by different switching strategies between two heat sources, which has not been given adequate attention from researchers. Therefore, this study introduced a system coefficient of performance − based switching strategy, which can alternate between air-source heat pump and solar water heat pump modes to make full use of air and solar energy, to optimize the operation of the photovoltaic-thermal integrated dual-source heat pump system and compare with the conventional water temperature of the heat storage tank − based switching strategy. A TRNSYS model of the system was developed and validated, and the simulated results demonstrated the better performance of system coefficient of performance − based switching strategy in energy, economic and environmental perspectives. The average photoelectric and photothermal conversion efficiency under system coefficient of performance − based switching strategy were higher than those under water temperature of the heat storage tank − based switching strategy by 1.1 % and 4.0 %, respectively, with average modified coefficient of performance of 7.43 and 6.55. Furthermore, the system not only achieved savings of 5.63 % in annual electrical cost and 5.33 % in yearly operational cost but also reduced standard coal by 19.25 kg and total pollutant emissions by 242.55 kg per year under system coefficient of performance − based switching strategy, compared to water temperature of the heat storage tank − based switching strategy.

Towards standalone commercial buildings in the Mediterranean climate using a hybrid metal hydride and battery energy storage system

Given the critical role of hybrid energy storage systems in the building sector for enhancing renewable energy reliability and integration, this study examines the techno-economic feasibility of adopting a dual-level energy storage system for a PV-driven commercial building in the Mediterranean climate. The proposed system encompasses both hydrogen metal hydride and battery storage units. Aimed at off-grid electrification, the optimal component sizing of the hybrid system is identified by establishing a statistical optimization framework using the response surface methodology. Dynamic simulations of the hybrid system are performed through a TRNSYS model coupled with a numerical code that simulates the metal hydride system. Regarding optimal net-zero solutions, it is shown that the share of the direct PV electricity supply to end-use fluctuates within a limited range for all scenarios, namely between 57.7 and 60.5 %, while the share of each storage system varies distinctively in each solution. The results indicate a striking difference between scenarios in terms of economic aspects; differences of $ 19,791 and $ 32,621 are observed between the minimum and maximum values of the initial investment and life cycle cost, respectively. The levelized cost of electricity varies between 0.354 and 0.403 $/kWh, in which the case having the lowest payback period (10.8 years) demonstrates the lowest levelized cost of electricity too. Furthermore, an inverse relationship between the levelized cost of hydrogen and production rate is observed; the lowest levelized cost and the highest annual production are achieved in the scenario with the lowest BESS capacity and the highest electrolyzer power and hydrogen storage volume, which are equal to 5.77 $/kg and 304.7 kg H2/yr, respectively.

Prediction of Greenhouse Microclimatic Parameters Using Building Transient Simulation and Artificial Neural Networks

In the realm of agricultural advancement, the relentless quest for agricultural efficiency amidst the vagaries of climate change has positioned greenhouse technology as a linchpin for secure and sustainable food production. The precise management of greenhouse microclimatic conditions i.e., the ability to accurately predict and maintain ideal temperature and relative humidity, is crucial for enhancing plant growth and health, optimizing resource use, and ensuring sustainable agricultural practices. However, maintaining optimal microclimatic conditions is a significant challenge due to the dynamic nature of external environmental influences. This study aims to address the critical need for advanced predictive tools that can enhance the control and management of greenhouse microclimates, thereby supporting sustainable agricultural practices and food security. Our research introduces a novel integration of building transient simulation (TRNSYS) and artificial neural networks (ANNs) to predict temperature and relative humidity inside a greenhouse across the calendar year, based on external atmospheric conditions. The TRNSYS model meticulously simulates the greenhouse’s thermal load, incorporating real-world data to ensure a high level of accuracy in describing the facility’s dynamic behavior. Our ANN model, composed of three layers, underwent optimization to identify the ideal number of neurons, learning rates, and epochs, settling on a model configuration that minimized prediction errors. The evaluation metrics, including root mean square error (RMSE) and mean absolute error (MAE), demonstrated the model’s effectiveness, with an RMSE of 0.3166 °C for temperature and 5.9% for relative humidity, and MAE values of 0.1002° and 3.4%, respectively. These findings underscore the model’s potential as a powerful tool for greenhouse climate control, offering substantial benefits in terms of energy efficiency, resource optimization, and overall sustainability in agriculture. By leveraging detailed dynamic simulations and advanced neural network algorithms, this study contributes significantly to the field of precision agriculture, presenting a novel approach to managing greenhouse environments in the face of changing climatic conditions.

Experimental and simulated evaluation of inverse model for shallow underground thermal storage

This study employs an inverse grey-box (IGB) modeling approach, which combines measured data and the physics of systems to predict the performance of shallow underground thermal energy storage (UTES) with top and side insulation. A simplified IGB model of the shallow UTES was developed using thermal network analysis. Experimental studies were conducted for shallow vertical and horizontal UTES configurations. Detailed models representing the field experiments were developed using the TRNSYS simulation tool and calibrated with the measured data from the experimental setup. The 4 Resistance 2 Capacitance (4R2C) IGB model was trained and tested in MATLAB using field experimental data and the data from the calibrated TRNSYS model. In comparing experimental data with the TRNSYS model for UTES, the prediction of outlet water temperature showed good agreement, with root mean square error (RMSE) and coefficient of variation of RMSE (CVRMSE) values of 0.94 °C and 3.16 % for vertical, and 0.99 °C and 2.97 % for horizontal configurations. The IGB model also aligned well with the experimental data, showing CVRMSE of 7.91 % and 3.17 % for vertical and horizontal systems, respectively. Sensitivity analysis revealed that model performance improves with longer training durations and closer testing times to training periods. However, a convergence point of 20 weeks of training data was achieved for making long-term performance predictions.

Techno-economic feasibility of integrating hybrid battery-hydrogen energy storage system into an academic building

Green hydrogen production and storage are vital in mitigating carbon emissions and sustainable transition. However, the high investment cost and management requirements are the bottleneck of utilizing hybrid hydrogen-based systems in microgrids. Given the necessity of cost-effective and optimal design of these systems, the present study examines techno-economic feasibility of integrating hybrid hydrogen-based systems into an outdoor test facility. With this perspective, several solar-driven hybrid scenarios are introduced at two energy storage levels, namely the battery and hydrogen energy storage systems, including the high-pressure gaseous hydrogen and metal hydride storage tanks. Dynamic simulations are carried out to address subtle interactions in components of the hybrid system by establishing a TRNSYS model coupled to a Fortran code simulating the metal hydride storage system. The OpenStudio-EnergyPlus plugin is used to simulate the building load, validate against experimental data, according to the measured data and monitored operating conditions. Aimed at enabling efficient integration of energy storage systems, a techno-enviro-economic optimization algorithm is developed to simultaneously minimize the levelized cost of the electricity and maximize the CO2 mitigation in each proposed hybrid scenario. The results indicate that integrating the gaseous hydrogen and metal hydride storages into the photovoltaic-alone scenario enhances 22.6% and 14.4% of the annual renewable factor. Accordingly, the inclusion of battery system to these hybrid scenarios gives a 30.4% and 20.3 % boost to the renewable factor value, respectively. Although the inclusion of battery energy storage into the hybrid systems increases the renewable factor, the results imply that it reduces the hydrogen production rate via electrolysis. The optimized values of the levelized cost of electricity and CO2 emission for different scenarios vary in the range of 0.376–0.789 $/kWh and 6.57–9.75 ton, respectively. The multi-criteria optimizations improve the levelized cost of electricity and CO2 emission by up to 46.2% and 11.3%, with respect to their preliminary design.

Solar driven liquid desiccant dehumidification system: Measurements and annual system simulations

Liquid desiccant air conditioning (LDAC) systems are used for dehumidification of air to low dew point temperatures. In the presented study a TRNSYS model of a LDAC unit is developed and validated with laboratory measurements. This model is coupled with a solar thermal system that provides heating water for the regeneration process. With this model dynamic annual system simulations can be carried out to simulate the dehumidification of a building. The solar fraction is evaluated for various infiltration rates of the building and solar collector areas with an internally cooled as well as an adiabatic absorption process.The simulation results reveal that high solar fractions of 70% to 81% can be achieved when dimensioning the solar thermal system to cover the regeneration heat demand on a good summer day. This is due to the good correlation of solar irradiance and dehumidification load. Without internal cooling of the absorption process (adiabatic conditions), the solar fraction is reduced by about 10percent points for the same size and operating conditions.

A simulation study on the heating characteristics of residential buildings using intermittent heating in Hot-Summer/Cold-Winter areas of China

Radiant air conditioning system is an important heating method with better thermal comfort, less noise and greater energy-saving potential. However, different intermittent heating modes may significantly impact both the heating efficiency and indoor thermal comfort, which has been neglected in existing studies. Therefore, to obtain optimal intermittent heating modes for achieving higher energy efficiency and better indoor thermal comfort for the residential buildings in Hot Summer and Cold Winter areas, a TRNSYS model of the radiant air conditioning system was developed and validated. The indoor thermal comfort and energy consumption characteristics during the coldest day and entire heating season were simulated and analyzed based on four different intermittent heating modes. The results demonstrated that the supply water temperature of the air source heat pump unit and the radiant terminals stabilized at the set temperature in about 1 h during the start-up stage, and the indoor air temperature stabilized at 24.0 °C after 7.5 h during the shutdown stage. The proportion of time that meets first-level thermal comfort under the four intermittent heating modes was above 90.1% and even higher at over 96.1% when considering the sleeping period. Compared to the continuous heating mode, the four intermittent heating modes saved 22.3%, 25.8%, 40.4% and 48.4% of energy. Overall, the preferred intermittent heating mode for residential buildings with the radiant air conditioning system in Hot Summer and Cold Winter areas was identified as switching on from 7:00 to 15:00 and 19:00 to 3:00, while switching off from 15:00 to 19:00 and 3:00 to 7:00. This model not only considered the immediate benefits of improved indoor thermal comfort and energy efficiency, but also showed great advantages in developing sustainable construction.

Mechanical Vapor Compression Desalination Process: Approaches to Optimize Compressor’s Consumption for Brine Valorization

Abstract Valorization of residual brines is one of the proposed solutions for minimizing the environmental effects of desalination plants, reducing the volume of wastewater generated at the time it increases both the freshwater production and the final concentration of the residue. Nevertheless, it is an energy-demanding process: the higher the final concentration of the fluid, the higher its energy consumption. We can approach this challenge from two different perspectives, either focusing on the final amount of concentrated residue or focusing on the energy demand of the installation. In this work, the behaviour of the compressor and the variables that affect its operation in a mechanical vapor compression (MVC) desalination system are studied. Using an own develop TRNSYS model of a compressor and adjusting with a real MVC desalination plant, it is done by analysing the connections between the final volume of residual brine and its energy consumption, comparing them with the values available from the LIFE Desirows experimental facilities as well. Moreover, the paper also explores some of the environmental and economic benefits of residual brines valorization.

TRNSYS MODEL OF THE COMBI BOILER DOMESTIC HOT WATER CIRCUIT WITH A FOCUS ON THE PARAMETER DEFINITION OF THE PLATE HEAT EXCHANGER

Combi boilers used for both space and domestic hot water heating are one of the common household appliances. Modelling the domestic hot water circuit of a combi boiler for the preliminary evaluation of the laboratory testing is of crucial importance since it decreases the time, cost, and energy spent on the trials. There are various modelling approaches established by the authors of this paper. Domestic hot water circuit of the appliance is modelled previously making use of the Transient System Simulation Tool (TRNSYS 18) and a good agreement is achieved with the experimental and numerical data for the economic mode simulations. The drawback of the current TRNSYS model is the dependence on the experimental data for some of the parameter definitions of the components selected from the TRNSYS library, i.e. UA (multiplication of the overall heat transfer coefficient and the heat transfer area) input of the plate heat exchanger and heat retention effect of the heat cell block. In this paper, a constant value is assigned to the parameter definition of UA instead of a time dependent varied profile. Mean absolute errors covering the steady-state and transient operating regions for the domestic hot water inlet and outlet temperature difference in economic mode simulations stay nearly the same around 0,46°C, 0,82°C, and 0,53°C for 5 l/min, 7 l/min, and 8,7 l/min, respectively, under constant and variable UA approaches. Comfort operating scheme model is established with a couple of experimental data as of the principal application of the constant UA approach. Mean absolute error of the overall domestic hot water inlet and outlet temperature difference profile decreases to 0,5°C in the comfort mode simulation.

Techno-economic assessment of a biomass gasification-based polygeneration system for greenhouses

Decentralized biorefineries are an attractive solution to reduce the carbon footprint of agricultural greenhouses, by converting the abundant local residual biomass into value-added products such as biofuels. While the thermodynamic performance of many biomass system configurations has been investigated in the literature, techno-economic assessments are needed to validate the potential of such facilities. This approach is applied to a small-scale polygeneration system for the use-case of a southern Quebec greenhouse. The polygeneration system can produce heat, electricity, methanol, hydrogen, and a CO2-rich stream. A TRNSYS model is used to simulate the heat demand of a 20 000 m2 greenhouse. The work presented here compares the polygeneration system with a conventional solution based on biomass combustion. Nine configurations between 1120 and 5600 kW of thermal output power are investigated for both system types. Twenty-seven market scenarios are generated from the combination of three pricing scenarios for electricity, methanol, and hydrogen: pessimistic, baseline, and optimistic. Fixed capital investment (FCI), operation expenses (OPEX), and NPV are presented. In the most pessimistic market scenario, the best polygeneration system would have an NPV of −8.2 M CAD. In the baseline and optimistic scenarios, the same polygeneration system would have an NPV of 17.6 M CAD and 40.2 M CAD, respectively. By comparison, the best combustion-based solution would have the highest NPV at −5.0 M CAD. Those results highlight that small decentralized polygeneration systems are promising. However, their profitability is heavily dependent on future energy market developments.

Thermal performance and energy cost of Korean multispan greenhouse energy-saving screens

Protected agricultural system such as a greenhouse cultivation is increasingly replacing traditional farming systems. Nonetheless, high energy demand in greenhouse farming requires innovative technologies through the use of climate screens to ensure sustainable production. Thus, this study developed a novel methodology for examining the energy retention capacity and economic effectiveness of greenhouse climate screen materials using their thermophysical, radiometric and aerodynamic properties in TRNSYS software. The TRNSYS model was developed to determine the energy consumption, which was validated using a multi-span Venlo-type experimental greenhouse (Yeoju, South Korea). Further analyses on energy saving capacity of different screens and the equivalent energy costs were performed. The results from this research showed that among the fifteen investigated screens, the ensemble screen (M3) saved 34.09 kWh.m−2 of annual energy, equivalent to 60 % of the heating energy demand, and energy cost of 4490.26 Korean won. m−2. Further, the results revealed that the climate screens with multi-layer, thermoreflective, low longwave transmissivity, impermeable and aluminized strips or surface characteristics and features have a considerable impact on reducing greenhouse energy use and desirable for high energy-saving. This research has demonstrated that the techniques and methods utilised can investigate all the types of covering and thermal screens used in greenhouse.

Demand response strategy study of a radiant roof cooling system based on the thermal inertia of the building envelope

There is an imbalance between supply and demand in the power system. Implementing demand response control strategies for air-conditioning systems is beneficial to optimize the allocation of power resources. Here, we use two single strategies and a combination strategy for the radiant roof cooling system: passive energy storage, global temperature reset, and the passive energy storage-global temperature reset combination strategy to implement demand response control, all of which achieve peak load reduction or shifting by changing the indoor controlled parameters. Based on the thermal inertia of the building envelope, we utilize a TRNSYS model to analyze the performance of three demand response strategies of radiant roof cooling systems in terms of thermal comfort, energy consumption, operating costs, and peak load shifting rates. The findings reveal that implementing demand response strategies can reduce the operating energy consumption of radiant roof cooling systems and facilitate peak load shifting. Among them, the combined response strategy shows the best peak load transfer effect, with a transfer rate of 19.84% and a better operating economy. Meanwhile, we find that the outdoor temperature affects the implementation of demand response strategies for the radiant roof cooling system based on the thermal inertia of the building envelope. Practical application The study has significant application value in the following aspects: Implementing a demand response strategy for the radiant roof cooling system, based on the thermal inertia of the building envelope, can reduce operational energy consumption and achieve peak load shifting. This approach effectively addresses the issue of supply-demand imbalance in the power system. The application of the work could facilitate improved operational energy efficiency, contributing to emissions reduction goals and optimizing the use of intermittent renewable energy systems in power grids.

Single and multi-objective optimization of PVT performance using response surface methodology with CuO nanofluid application

The nanofluid application in photovoltaic thermal (PVT) systems is widely known as an effective solution for improving output performance. However, studies exploring the optimum operation point of PVT systems with nanofluid application are scant in the current literature. The novelty of the study lies in exploring the optimum operating conditions of each PVT output using single-objective optimization and the overall performance optimization using multi-objective study. The conditions were explored with the application of copper oxide nanofluid as a coolant in PVT systems. The investigation was conducted using a numerical equation-based model developed in TRNSYS simulation environment. An experimental test was conducted to validate the outputs of numerical model. After validating the numerical model, TRNSYS model was investigated for 0.10%-0.50% volume concentration and 60–120 kg/h mass flow. The output data was then imported into Design-Expert software for performance optimization. Central composite design was selected as it is the most suitable fractional factorial design option in response surface methodology. In single-objective investigation, the optimization conditions for PVT outputs are identified as follows, the optimum electrical efficiency output was 14.64% at 90 kg/h fluid flow and 0.10% concentration, the thermal efficiency output was 34.94% at 120 kg/h fluid flow and 0.50% concentration, the overall energy efficiency output was 49.28% at 88 kg/h fluid flow and 0.10% concentration, the overall exergy efficiency output was 16.45% at 60 kg/h fluid flow and 0.50% concentration. The multi-objective study indicated that the collective performance of PVT outputs is optimum at 91 kg/h fluid flow and 0.10% concentration.

System optimization and mode modification of the solar assisted ground source heat pump system for primary schools in northern rural areas of China

With the increasing application of geothermal and solar energy in northern regions of China, it has become one of the main clean heating technologies for rural primary schools. However, the mismatch in equipment capacity has led to poor operating effect and economic efficiency of such systems. This paper puts forward experimental and analysis on a solar assisted ground source heat pump system in a primary school in Beijing's Daxing District. And then, to address the above issues, a TRNSYS model is established and verified to optimize the system strategy and form during 15 years period. What’ more, the main factors affecting solar collector selection are screened by sensitivity analysis. And through the step-by-step regression analysis, the collector selection correction model based on the coefficient Km is obtained. The results show that the temperature difference of the optimized collector control is 10 °C/1°C, and that of the supplementary heat is 20 °C/1°C. The applicable scenarios of the two system forms are different, and the energy efficiency of the system operation is increased by 23% and 23.4% respectively. In addition, the revised model ensures the balance of soil temperature for 15 years of operation under the condition of considering multiple elements, which provides a reference for the matching and selection of equipment for the same type of project in the future.

Techno-economic-environmental analysis of seasonal thermal energy storage with solar heating for residential heating in China

Seasonal thermal energy storage (STES) of solar heat is an option of interest for clean heat transition, as residential heating is often fossil fuel-based. This study 1) proposes an integrated optimization criterion to examine how local context influences the optimal configuration planning, techno-economic-environmental performance, and feasibility of STES application; 2) identifies the position of STES in comparison to other sustainable heating options considering the local context; and 3) provides a comprehensive and transparent showcase highlighting the importance of the local context in determining the feasibility of STES in the clean heating transition. The TRNSYS modeling tool is adopted to analyze the performance, and Pareto optimization is applied to treat the multi-objective optimization. The solar fractions and storage efficiencies of the four case studies range between 58-67% and 57–69%, respectively. STES has significant potential to reduce CO2 emissions (52–72%) compared to conventional heating systems. However, the heating cost of the STES system (5.4–8.7 €-ct/kWh) is more than twice that of the conventional heating system. The CO2 avoidance cost of the four case studies ranges between 114 and 368 €/t. Properly reducing the borehole number in cold climate zones and increasing the solar collector area in warm climate zones help improve the system performance.

Developing a TRNSYS model for radiant cooling floor with a pipe-embedded PCM layer and parametric study on system thermal performance

The design of the radiant cooling floor with a pipe-embedded PCM layer (RCF-PEPCML) lacks a relevant reference basis. Simulation is the best way to determine the optimal design of the system. The simulation research of PCM radiant terminals has been developed, but there is still a need to establish a convenient transient simulation method for RCF-PEPCML, in order to conduct various optimization studies on system design. In order to meet this simulation requirement, a two-dimensional heat transfer model for a pipe-embedded PCM layer (PEPCML) was established. The numerical model was written in FORTRAN language and integrated into TRNSYS to create a new module (TYPE207) for simulating a PEPCML. The accuracy of the new module was verified by experiments conducted in a scaled experiment room with radiant floor cooling. Then, using the newly-built module and TRNSYS, a case study was conducted to explore the effect of several key parameters on the thermal performance of the RCF-PEPCML. The influencing parameters considered include the PCM's phase change temperature, phase change latent heat, and the PCM layer thickness. The results of univariate sensitivity analysis show that these three parameters all greatly affect the thermal performance of RCF-PEPCML. The recommended optimal phase change temperature should meet this condition where the lower limit of the phase change temperature interval is higher than the water supply temperature by 0–1 °C. The optimal phase change latent heat and optimal PCM layer thickness depend on the specific design conditions of the cooling terminal. It is suggested to perform optimization design analysis for specific cases through simulation. The orthogonal test analysis of multiple parameters shows that the optimal design parameters combination for the case study is the combination of a phase change temperature of 20 °C, a phase change latent heat of 160 kJ/kg, and a PCM layer thickness of 15 mm. Among the three influencing factors, the phase change temperature should be given priority.

Model of the combi boiler appliance in TRNSYS for domestic hot water circuit: Experimental and numerical validations of economic mode simulations

Combi boiler type heating appliances are used nearly in every residential building for both space and domestic hot water (DHW) heating functions. There are challenging targets regarding both of these functions. Since there is a huge laboratory testing procedure behind each appliance design and the structural or operational changes on the regular designs, simulation models could be established for the initial evaluations of the appliance testing. Therefore, due to the estimations from the preliminary results of the simulations, the number of the laboratory tests could be decreased with cost, time, and energy savings. In this study, the main objective is modelling DHW heating circuit of a combi boiler appliance with the help of Transient System Simulation Tool (TRNSYS 18) to calculate DHW outlet temperature under various operating conditions. The TRNSYS model is validated experimentally and compared with the previous works of the authors. A good agreement is achieved in both transient and steady-state regions and the TRNSYS model is found superior when compared to the previously established one-dimensional model of the authors. DHW circuit model is validated only for economic (eco) working mode simulations in this study. Mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE) values are compared for the outcomes of the previously constructed one-dimensional model and currently established TRNSYS model with reference to the experimental data. TRNSYS model decreases all of these errors calculated according to the overall temperature profiles including the transient region for the central heating water at the heat cell inlet, central heating water at the heat cell outlet, and the inlet and outlet temperature difference of DHW at the experimentally investigated DHW flow rates of 5 l/min, 7 l/min, and 8.7 l/min.

Simulation and Field-Based Study of Thermal Performance of a Building - A Case Study

Concerns about building thermal performance and energy consumption are fast growing as they account for roughly 40% of worldwide annual energy use. Building construction in Nepal is controlled by the National Building Codes (NBC), which focus solely on structural considerations and ignore thermal behaviour. As a result, housing tends to be too much warm and too cold during summer and winter respectively due to the lack of passive heating and cooling mechanisms considered during the construction phase. The Thakle Integrated Settle (TIS), built by the Department of Urban Development and Building Construction (DUDBC) under the National Reconstruction Authority and supported by Oxfam Nepal, was the subject of this research. The building’s performance in the chosen location was analysed using a field and TRNSY simulation-based technique. Using meteorological data from Meteonorm software, the TRNSYS model was created to examine the performance in terms of internal air temperature and heating/cooling load of two buildings with different orientations, e.g., North-East (NE) and South-West (SW). According to simulation results, there is a heating demand that covers roughly 37% of the year, while cooling and comfort conditions were 32% and 31%, respectively. For NE and SW-facing buildings, heating demand was 4.10 MWh and 4.07 MWh, while cooling demand was 1.302 MWh and 1.309 MWh respectively.