Search Results (20)

In the age of widespread renewable energy integration, coal-fired power plants are transitioning from a primary baseload role to a more flexible peak-shaving capacity. Under frequent load changes, the thermal efficiency will significantly decrease. In order to achieve efficient dynamic operation, this study proposes a comprehensive mechanical model of a 300 MW drum-type boiler. Based on the Modelica/DYMOLA platform, the multi-domain equations describing energy and mass balance are programmed and solved. A comprehensive evaluation of the energy transformation within the boiler’s heat exchange components was performed. Utilizing the principles of exergy analysis, this study investigates how fluctuating operational conditions impact the energy dynamics and exergy losses in the drum and heating surfaces. Steady-state simulation reveals that the evaporator and superheater units account for 81.3% of total exergy destruction. Dynamic process analysis shows that the thermal inertia induced by the drum wall results in a significant delay in heat transfer quantity, with a dynamic period of up to 5000 s. The water wall exhibits the highest total dynamic exergy destruction at 9.5 GJ, with a destruction rate of 7.9–8.5 times higher than other components. Full article

To accommodate the integration of renewable energy, coal-fired power plants must take on the task of peak regulation, making the low-load operation of boilers increasingly routine. Under low-load conditions, the phase transition point (PTP) of the working fluid fluctuates, leading to potential flow instability, which can compromise boiler safety. In this paper, a one-dimensional coupled dynamic model of the combustion and hydrodynamics of a supercritical boiler is developed on the Modelica/Dymola 2022 platform. The spatial distribution of key thermal parameters in the furnace and the PTP position in the water-cooled wall (WCW) are analyzed in a 660 MW supercritical boiler when parameters on the combustion side change under full-load and low-load conditions. The dynamic response characteristics of the temperature, mass flow rate, and the PTP position are investigated. The results show that the over-fire air (OFA) ratio significantly influences the flue gas temperature distribution. A lower OFA ratio increases the flue gas temperature in the burner zone but reduces it at the furnace exit. The lower OFA ratio leads to a higher fluid temperature and shortens the length of the evaporation section. The temperature difference in the WCW outlet fluid between the 20% and 60% OFA ratios is 11.7 °C under BMCR conditions and 7.4 °C under 50% THA conditions. Under the BMCR and 50% THA conditions, a 5% increase in the coal caloric value raises the flue gas outlet temperature by 32.7 °C and 35.4 °C and the fluid outlet temperature by 6.5 °C and 9.9 °C, respectively. An increase in the coal calorific value reduces the length of the evaporation section. The changes in the length of the evaporation section are −2.95 m, 2.95 m, −2.62 m, and 0.54 m when the coal feeding rate, feedwater flow rate, feedwater temperature, and air supply rate are increased by 5%, respectively. Full article

The rail vehicle industry wants to produce vehicles with higher speeds, to maintain and increase its market share. However, when the speed of the vehicle increases, it may have an undesirable effect on ride comfort, in terms of ride dynamics. Recent developments towards lighter and faster vehicles make the problem of ride comfort at higher speeds increasingly important. Focusing on the behavior of flexible rather than rigid body behavior should not be neglected when designing long and light car bodies. There are several approaches to incorporate body flexibility in multibody simulations and they have some superiorities and weaknesses. In this study, an efficient and accurate vertical dynamic model for the ride comfort analysis is developed and implemented in a commercial object-oriented modeling (OOM) software Dymola (2015 FD01) which uses the open-source code Modelica. This model includes car body flexibility with the assembling of a rigid body approach. The developed model is compared to a three-dimensional vehicle model in the commercial Vampire software (Pro V5.50) at different velocities. For the vertical ride comfort analysis, the ISO 2631-1 standard was used for both the developed model and the three-dimensional model. The results are presented as acceleration history and $a^{wrms}$—weighted r.m.s (root mean square) of accelerations—as required by the standard. The developed model has shown its feasibility in terms of its efficiency and accuracy for the vertical ride comfort analysis. The accuracy of the model is evidenced by the fact that the car body vibration level at high speeds shows minor differences compared to the results of the Vampire, which is a validated commercial software in the area of rail vehicle dynamics. The approach involving the assembly of rigid bodies is applied for the first time for high-speed trains in dynamical modelling, with flexible car bodies for ride comfort analysis. Furthermore, it can be used for parametrical studies focusing on ride comfort, thereby offering a quite beneficial framework for addressing the challenges of ride comfort analysis in high-speed rail vehicles. Improvements for and analyses of other aspects are also possible, since the optimization and other useful libraries are readily available in Dymola/Modelica. Full article

Mathematical optimization is a widespread method in order to improve, for instance, the efficiency of energy systems. A simulation approach based on partial differential equations can typically not be formulated as an optimization problem, thus requiring interfacing to an external optimization environment. This is, among others, also true for the programming language Modelica. Because of high computation time, such coupled approaches are often limited to small-scale optimization problems. Since simulation models tend to get more complex, simulation time and, in turn, associated optimization time rise significantly. To enable proper sampling of the search space, individual optimization runs need to be solved in acceptable times. This paper addresses the search for a proper optimization approach and tool to couple with Modelica/Dymola. The optimization is carried out on an exemplary power plant model from the ClaRa-Library using an evolutionary algorithm (SPEA2-based) with Ansys optiSlang. To verify and evaluate the results, a comparison with the standard Dymola optimization library is performed. Both parallelization and indirect optimization with surrogate models achieved a significant runtime reduction by a factor of up to 5.4. The use of meta models is particularly advantageous for repetitive optimization runs of the same optimization problem but may lead to deviations due to the calculated approximations. Full article

The exploitation of solar irradiation is a critical weapon for facing the energy crisis and critical environmental problems. One of the most emerging solar technologies is the use of solar towers (or central receiver systems) coupled with high-performance thermodynamic cycles. In this direction, the present investigation examines a solar tower coupled to a closed-loop Brayton cycle which operates with supercritical CO₂ (sCO₂) as the working medium. The system also includes a storage system with two molten salt tanks for enabling proper thermal storage. The sCO₂ is an efficient fluid that presents significant advancements, mainly reduced compression work when it is compressed close to the critical point region. The novelty of the present work is based on the detailed dynamic investigation of the studied configuration for the year period using adjustable time step and its sizing for achieving a continuous operation, something that makes possible the establishment of this renewable technology as a reliable one. The analysis is conducted with a developed model in the Modelica programming language by also using the Dymola solver. According to the simulation results, the yearly solar thermal efficiency is 50.7%, the yearly thermodynamic cycle efficiency is 42.9% and the yearly total system efficiency is 18.0%. Full article

The objective of this study is to demonstrate and validate the Dynamic Energy Transport and Integration Laboratory (DETAIL) preliminary scaling analysis using Modelica language system-code Dymola. The DETAIL preliminary scaling analysis includes a multisystem integral scaling package between thermal-storage and hydrogen-electrolysis systems. To construct the system of scaled equations, dynamical system scaling (DSS) was applied to all governing laws and closure relations associated with the selected integral system. The existing Dymola thermal-energy distribution system (TEDS) facility and high-temperature steam electrolysis (HTSE) facility models in the Idaho National Laboratory HYBRID repository were used to simulate a test case and a corresponding scaled case for integrated system HYBRID demonstration and validation. The DSS projected data based on the test-case simulations and determined scaling ratios were generated and compared with scaled case simulations. The preliminary scaling analysis performance was evaluated, and scaling distortions were investigated based on data magnitude, sequence, and similarity. The results indicated a necessity to change the normalization method for thermal storage generating optimal operating conditions of 261 kW power and mass flow rate of 6.42 kg/s and the possibility of reselecting governing laws for hydrogen electrolysis to improve scaling predictive properties. To enhance system-scaling similarity for TEDS and HTSE, the requirement for scaling validation via physical-facility demonstration was identified. Full article

The integration of photovoltaic panels and heat pumps in domestic environments is a topic that has been studied extensively. Due to their electrical nature and the presence of elements that add thermal inertia to the system (water tanks and the building itself), the functioning of compression heat pumps can be manipulated to try to fulfill a certain objective. In this paper, following a rule-based control concept that has been identified in commercial solutions and whose objective is to improve the self-consumption of the system by actively modulating the heat pump compressor, a parametric analysis is presented. By making use of a lab-tested model, the performance of the implemented control algorithm is analyzed. The main objective of this analysis is to identify and quantify the effects of the main parameters in the performance of the system, namely the climate (conditioning both heating and cooling demands), the photovoltaic installation size, the thermal insulation of the building and the control activation criteria. A total of 168 yearly simulations have been carried out. The results show that the average improvement in self-consumption is around 13%, while the cost is reduced by 2.5%. On the other hand, the heat from the heat pump and the power consumed increase by 3.7% and 5.2%, respectively. Finally, a linear equation to estimate the performance of the controller is proposed. Full article

The performance of the innovative configurations of the “efficient” thermal networks is a key topic in scientific research, focusing on distribution temperatures and integration with high-efficiency plants and renewable sources. As it already happens for the electricity prosumers, a thermal prosumer may feed the district heating network through a bidirectional exchange substation with the excess of the locally produced thermal energy (e.g., by means of solar thermal plant) or with the waste heat recovered in the industrial processes. The Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA) and the Alma Mater Studiorum University of Bologna (UNIBO) designed a bidirectional substation prototype, based on a return-to-supply configuration, and tested steady-state and dynamic conditions to evaluate performances and optimization measures. In this paper, the Modelica language and Dymola software were used to run a multi-domain simulation and model-based design of the substation, starting from a new heat exchanger model featuring variable efficiency, based on the thermal resistance scaling method. Control systems and components were customized from models in standard libraries in order to reproduce the substation behavior under defined operating settings, and the model was validated on the abovementioned experimental tests. Numerical results in terms of exchanged powers, temperatures and flow rates were systematically compared to experimental data, demonstrating a sufficient agreement. In particular, the absolute mean deviation—in terms of temperature—between experimental and numerical data assessed over the entire tests remains contained in +/−1 °C. As further step of the analysis, an optimized model could be included as a component in a district heating network for further investigations on the prosumers’ effects on an existing traditional grid (e.g., in case of deep renovation of urban areas connected to district heating and/or creation of micro energy communities). Full article

Establishing interoperability is an essential aspect of the often-pursued shift towards Model-Based Systems Engineering (MBSE) in, for example, aircraft development. If models are to be the primary information carriers during development, the applied methods to enable interaction between engineering domains need to be modular, reusable, and scalable. Given the long life cycles and often large and heterogeneous development organizations in the aircraft industry, a piece to the overall solution could be to rely on open standards and tools. In this paper, the standards Functional Mock-up Interface (FMI) and System Structure and Parameterization (SSP) are exploited to exchange data between the disciplines of systems simulation and geometry modeling. A method to export data from the 3D Computer Aided Design (CAD) Software (SW) CATIA in the SSP format is developed and presented. Analogously, FMI support of the Modeling & Simulation (M&S) tools OMSimulator, OpenModelica, and Dymola is utilized along with the SSP support of OMSimulator. The developed technology is put into context by means of integration with the M&S methodology for aircraft vehicle system development deployed at Saab Aeronautics. Finally, the established interoperability is demonstrated on two different industrially relevant application examples addressing varying aspects of complexity. A primary goal of the research is to prototype and demonstrate functionality, enabled by the SSP and FMI standards, that could improve on MBSE methodology implemented in industry and academia. Full article

Research activity in the field of combined cooling heating power (or trigeneration) systems with high renewable energy source (RES) contributions has increased rapidly over the last few years, in line with the European Union legislation about energy communities. However, technical challenges arise regarding the synergetic, sustainable and optimal integration of RES in local energy systems. In the present study, the operation of a trigeneration system located in the student residences of Democritus University of Thrace in Greece is examined. The system involves a combination of highly promising renewable and storage technologies, including solar thermal energy and biomass for heat generation, hot water tanks for thermal energy storage, absorption refrigeration for cooling, along with Organic Rankine Cycle and photovoltaic systems for electricity generation. System modeling and simulation have been implemented in Dymola environment with the use of Modelica equation-based modeling language. The accuracy of the model response has been validated against available measurements. Specific design and control measures have been proposed, simulated in a transient fashion and evaluated in terms of (i) RES generation, (ii) solar fraction and (iii) temporal flexibility. The measures examined, including the placement of a Li-ion battery, resulted in an increase of 24.6% in the heating demand solar contribution and of 7.9% in the renewable energy generated for the electricity demand, over the examined periods. Full article

The European and national regulations in the decarbonisation path towards 2050 promote district heating in achieving the goals of efficiency, energy sustainability, use of renewables, and reduction of fossil fuel use. Improved management and optimisation, use of RES, and waste heat/cold sources decrease the overall demand for primary energy, a condition that is further supported by building renovations and new construction of under (almost) zero energy buildings, with a foreseeable decrease in the temperature of domestic heating systems. Models for the simulation of efficient thermal networks were implemented and described in this paper, together with results from a real case study in Italy, i.e., University Campus of Parma. Activities include the creation and validation of calculation codes and specific models in the Modelica language (Dymola software), aimed at investigating stationary regimes and dynamic behaviour as well. An indirect heat exchange substation was coupled with a resistive-capacitive model, which describes the building behaviour and the thermal exchanges by the use of thermos-physical parameters. To optimise indoor comfort conditions and minimise consumption, dynamic simulations were carried out for different operating sets: modulating the supply temperature in the plant depending on external conditions (Scenario 4) decreases the supplied thermal energy (−2.34%) and heat losses (−8.91%), even if a lower temperature level results in higher electricity consumption for pumping (+12.96%), the total energy consumption is reduced by 1.41%. A simulation of the entire heating season was performed for the optimised scenario, combining benefits from turning off the supply in the case of no thermal demand (Scenario 3) and from the modulation of the supply temperature (Scenario 4), resulting in lower energy consumption (the thermal energy supplied by the power plant −3.54%, pumping +7.76%), operating costs (−2.40), and emissions (−3.02%). The energy balance ex-ante and ex-post deep renovation in a single user was then assessed, showing how lowering the network operating temperature at 55 °C decreases the supplied thermal energy (−22.38%) and heat losses (−22.11%) with a slightly higher pumping consumption (+3.28%), while maintaining good comfort conditions. These promising results are useful for evaluating the application of low-temperature operations to the existing district heating networks, especially for large interventions of building renovation, and confirm their potential contribution to the energy efficiency targets. Full article

In the present paper, the numerical modeling of an innovative latent thermal energy storage unit, suitable for direct integration into the condenser or evaporator of a heat pump is presented. The Modelica language, in the Dymola environment, and TIL libraries were used for the development of a modular model, which is easily re-usable and adaptable to different configurations. Validation of the model was carried out using experimental data under different operating modes and it was subsequently used for the optimization of a design for charging and discharge. In particular, since the storage unit is made up of parallel channels for the heat transfer fluid, refrigerant, and phase change material, their number and distribution were changed to evaluate the effect on heat transfer performance. Full article

Thermal energy storage (TES), which features an innovative technology, can enhance energy efficiency in the building sector and reduce CO₂ emissions. Due to their high heat storage capacity, phase change materials (PCMs) have impressed many researchers. This paper investigates the energy performance of an individual house integrating a solar Trombe wall containing PCM with respect to heating demand and thermal comfort applications. The thermal energy performance of the design house was simulated using Dymola/Modelica, the thermal building simulation tool, whereby the optimization of objective functions as regards heating demand and thermal comfort was executed using GenOpt, the generic optimization software. Optimization of the solar Trombe wall focuses on the feasibility to find the optimal PCM parameters when running GenOpt, which consist of latent heat, melting temperature, PCM thickness and thermal conductivity, in order to minimize both the annual energy consumption for heating and the number of hours of thermal discomfort. The parametric study was first conducted for each PCM parameter so as to not only observe its effect on the identified energy performance, but also ensure the absence of errors in simulation runs before performing the optimization. The ‘Coordinate Search’ Generalized Pattern Search (GPS) algorithm was applied to minimize the objective function, whereas the ‘Weighted Sum Approach’ was used to solve the multi-objective function problem. Results showed that the higher the latent heat, the lower the heating demand and the greater the thermal comfort. The results of these parametric studies show that for the effect of the parameter on heating, demand is quite limited (1–2 kWh·m${}^{-2}$·year${}^{-1}$) whereas the effect on thermal comfort is more significant. The optimal PCM melting temperature is higher for warmer climates; it is also higher for the studied case applying the optimization method to minimize the objective function by assigning the number of hours of thermal discomfort (from 32.8 ${}^{\circ }\mathrm{C}$ to 35.9 ${}^{\circ }\mathrm{C}$, depending on weather) than it is when applying the optimization method to reduce the objective function by assigning heating demand (from 31.5 ${}^{\circ }\mathrm{C}$ to 32.9 ${}^{\circ }\mathrm{C}$, again depending on weather). Full article

The heating, ventilation and air conditioning (HVAC) system negatively affects the electric vehicle (EV) driving range, especially under cold ambient conditions. Modern HVAC systems based on the vapour-compression cycle can be rearranged to operate in the heat pump mode to improve the overall system efficiency compared to conventional electrical/resistive heaters. Since such an HVAC system is typically equipped with multiple actuators (compressor, pumps, fans, valves), with the majority of them being controlled in open loop, an optimisation-based control input allocation is necessary to achieve the highest efficiency. This paper presents a genetic algorithm optimisation-based HVAC control input allocation method, which utilises a multi-physical HVAC system model implemented in Dymola/Modelica. The considered control inputs include the cabin inlet air temperature reference, blower and radiator fan air mass flows and secondary coolant loop pumps’ speeds. The optimal allocation is subject to specified, target cabin air temperatures and heating power. Additional constraints include actuator hardware limits and safety functions, such as maintaining the superheat temperature at its reference level. The optimisation objective is to maximise the system efficiency defined by the coefficient of performance (COP). The optimised allocation maps are fitted by proper mathematical functions to facilitate the control strategy implementation and calibration. The overall control strategy consists of superimposed cabin air temperature controller that commands heating power, control input allocation functions, and low-level controllers that ensure cabin inlet air and superheat temperature regulation. The control system performance is verified through Dymola simulations for the heat pump mode in a heat-up scenario. Control input allocation map optimisation results are presented for air-conditioning (A/C) mode, as well. Full article

As the heating demands of buildings drop considerably, the use of solar walls makes increasing sense. One of the obstacles to the development of such walls is their need for on-site implementation by specialized companies. On the other hand, a storage wall is generally composed of heavy materials with high inertia, which prevents prefabrication of the solar component. To avoid this problem and allow for solar walls to be prefabricated in the factory, a novel approach to replacing this heavy wall with a lighter storage wall incorporating phase change materials (PCM) has been proposed. This paper aims to demonstrate the impact of PCM on the thermal energy performance once they have been integrated into the storage wall of the composite Trombe wall. Addressed herein will be the heat transfer exchange inside a house located in the northern part of France, where a composite Trombe wall has been fitted without PCM. Three configurations will be investigated—(1) the model house without the solar Trombe wall, defined as the reference configuration; (2) the model house integrating the concrete solar Trombe wall; and (3) the model house integrating the PCM solar Trombe wall. Two setpoint temperatures will be introduced—(a) a constant setpoint of 20 °C, and (b) a variable setpoint of 19 °C (14 h from 7:00 a.m. to 9:00 p.m.) and 16 °C (10 h from 9:00 p.m. to 7:00 a.m.). Furthermore, three different climate conditions will be adopted to run simulations—Paris-Orly, Lyon, and Nice. Dymola/Modelica, a dynamic thermal simulation tool, will be utilized to simulate the thermal performance of these defined configurations. The results obtained, regarding a solar Trombe wall installation that applies two distinct storage walls exposed to the weather of Paris, showed similar minimizations of the one-year energy heating demand inside the bedroom, equal to roughly 20% (i.e., 20.45% of concrete storage wall and 19.90% of PCM storage wall) compared to the reference configuration (i.e., the house with no solar Trombe wall). Based on the imposed setpoint temperature by means of night and day reductions, the resulting heating energy demand in the bedroom, through application of the two storage walls (concrete and PCM) and three different climatic regions could be minimized by 20.34% in Paris, 20.20% in Lyon, and 68.10% in Nice (for the concrete storage wall) vs. the reference configuration; and by 18.79% in Paris, 19.56% in Lyon, and 55.15% in Nice (for the PCM storage wall) vs. the reference configuration. Full article