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R744/R152a mixture has broader application prospects. However, its thermodynamic and safety characteristics need to be fully considered. This paper presents the flammability characteristics and reaction mechanism of R744/R152a mixture by experimental and ReaxFF MD. Firstly, the flammable zones of the mixture with different ratios were tested on a high-precision experimental setup. Using a high-speed camera and an infrared thermographic record flame evolution characteristics and relative flame temperature of the mixture both lean and rich limits. The flammable zones of R152a are 0.386–0.685 (Φ) at y = 0. R744 was able to narrow the flammability zones of R152a. As the inert gas increases, the lean and rich limits merge, is 0.542 (Φ). Based on experimental studies, the inhibitory effect of R744 on the oxidation mechanism of R152a was investigated from the atomic level using ReaxFF MD. The results showed that the R744 increased the activation energy of the system from 52.08 kcal/mol to 55.73 kcal/mol, 52.18 kcal/mol, 57.04 kcal/mol, 52.93 kcal/mol, 52.98 kcal/mol, respectively. Reaction pathways and the rates of elementary reaction are significantly suppressed. The simplified mechanism of the oxidation can reveal the macroscopic phenomenon that R744 inhibits flame propagation. The results of this study provide safety guidance for R744/R152a applications. • Experiments method explore the flammability zones of R744/R152a. • The flame propagation suppression of R152a by R744 was analyzed. • The mechanism of R744 inhibition of R152a was investigated by Reaxff MD. • R744 has an inhibition effect on the rate constant of the elementary reaction. [ABSTRACT FROM AUTHOR]

The rapid simulation of pipelines significantly facilitates tasks such as pipeline operation scheduling and optimization, while neural networks can offer an efficient alternative modeling approach. Based on the Fourier Neural Operator (FNO), this study proposes a rapid and comprehensive model for computing the transient natural gas pipeline processes. To further enhance the performance of the model, a novel loss function is proposed that integrates the Benedict-Webb-Rubin-Starling (BWRS) equation as a physical constraint. After being trained on finite-dimensional data, the proposed model demonstrates high accuracy, good grid invariance, and significant computational acceleration. Compared with data from existing studies and simulation results of the renowned natural gas pipeline simulation software TGNET, the relative error of the proposed model remains below 2.5 %. The trained model can also predict outcomes beyond the original training data with a root mean squared error value of 2.542 × 10−3, demonstrating good grid invariance. Moreover, compared to the traditional numerical algorithm, the model exhibits a significantly high acceleration ratio, typically achieving an order of magnitude of 102 and occasionally up to 103. In conclusion, the proposed model can serve as a solver for transient natural gas pipeline simulation processes, efficiently providing accurate simulation results. • A comprehensive computational model for efficiently computing transient pipeline simulation processes is proposed. • The Benedict-Webb-Rubin-Starling (BWRS) equation of state is embedded into the loss function as a physical constraint. • The proposed model exhibits strong grid invariance. • The proposed model achieves a significant speedup compared with traditional numerical methods. [ABSTRACT FROM AUTHOR]

Residential buildings account for 84 % of Italy's built environment, playing a pivotal role in the EU's aim to cut GHG emissions by 55 % through enhanced energy efficiency and climate adaptation. This necessitates comprehensive energy retrofit initiatives, especially in sectors like social housing, which has been relatively overlooked in terms of energy efficiency strategies. This study focuses on a multi-story building from the 1980s in Rome, implementing an innovative energy system proposed by the RESHeat European project. This system, aimed at standardizing energy retrofits for late 20th-century social housing, leverages the underexplored potential of water-source heat pump (WSHP) systems. The novelty of this research extends to its examination of multi-family housing, a sector that has seen less attention compared to public spaces and smaller residential buildings. Through experimental validation and annual dynamic simulations using TRNSYS and Simulink, the research compares the existing heating system with a proposed upgrade that includes a WSHP and Photovoltaic-Thermal (PVT) panels. This upgrade demonstrated a significant efficiency improvement, achieving an annual COP of 6.1 for the WSHP and a 36 % Primary Energy Savings (PES) from the PVT panels, showcasing the effectiveness of these technologies in enhancing the energy profile of multi-family residential buildings. [Display omitted] • A multi-energy system for a 1980s social housing in mild climate is presented. • A dynamic model based on a water-source HP and cooled PV panels was set. • Experimental validation of building and plant components were conducted. • Combining heat pump and PVT panels a seasonal COP of 5.4 can be achieved in heating. • Solar fraction of 0.98 ensured by PVT contributes to a Primary Energy Saving of 36 %. [ABSTRACT FROM AUTHOR]

Dynamic simulation is a powerful tool for accurately evaluating the thermal demands of buildings and assessing the impact of energy refurbishment actions on their final consumption. Conversely, semi-stationary models are widely adopted in commercial applications for its simplified approach, which reduce calculation times, resulting in standardized results showing a certain deviation with respect to the real energy This paper presents the energy and economic comparison between the dynamic simulation and semi-stationary approaches for the calculation of primary energy demand of residential buildings. The semi-stationary method, used by the legislation to calculate the buildings energy label, is based on an energy performance parameter, not representative of the real energy demand. Conversely, an approach based on dynamic simulation provides a more reliable estimation of the primary energy demand. The main novelty of this paper is to numerically prove that the energy and economic savings calculated by means of software based on the current legislation may be overestimated. In this work, the dynamic simulation of the building-plant system is performed by TRaNsient SYstem Simulation (TRNSYS) program. Each building apartment is divided in thermal zones, where the internal heat gains are defined in detail. The semi-stationary simulation of the building-plant system is performed according to the Italian standard UNI TS 11300. The models allow one to evaluate the yearly primary energy demand, along with the energy bill and CO 2 emissions. A specific case study is developed for a residential building located in Naples (Italy). The models are used to calculate the building energy demand for several scenarios, considering different thermal transmittances of the building elements. The results show that the semi-stationary method overestimates of primary energy saving, equal to 64.7 %, with respect to the one calculated with the dynamic approach, equal to 43.2 %. • Semi-stationary and dynamic simulations were compared for residential buildings. • Critical evaluation of energy and economic savings due to the building refurbishment. • Primary energy savings of 65 % and 43 % by semi-stationary and dynamic simulation. • Dynamic simulation is needed within the legal frame of energy efficient buildings. [ABSTRACT FROM AUTHOR]

In this study, two processes of predictive model combining dynamic simulation and regression model were presented. First, (1) the demand forecasting process defined in this study is a method of predicting energy consumption based on the simulated energy consumption of a target building, and (2) the energy saving process is a method of setting an energy reduction target based on the predicted energy consumption and providing energy saving measures to achieve the target. Specifically, there are two functions based on the regression models which are predicting actual energy consumption by inputting the energy consumption simulation data, and inversely inputting the actual energy consumption and deriving the corresponding simulation conditions. As a result of predicting building energy consumption through the demand forecasting process, the performance in the heating season showed CV-RMSE was 14.622%, and in the cooling season CV-RMSE was 5.877%. In addition, in the case study using the energy saving process, it was possible to derive the heating and cooling set temperature for 5% energy saving as an energy saving method by using weather forecast data. • Demand forecasting and energy saving of buildings. • Regression model-based process between simulation-based predictions and actual energy consumption. • Two processes combining TRNSYS and DNN model to ensure building energy management efficiency. [ABSTRACT FROM AUTHOR]

Generalized predictive control (GPC), which has excellent control performance and robustness, is only applicable to the control object that can be expressed in the transfer function and is difficult to be directly applied to the hydraulic turbine regulation system (HTRS) that contain extremely complex nonlinearity. Therefore, considering the practical application of GPC in a hydropower station containing the Francis turbine, the double models, real-time feedback linearization module, and a nonlinear characteristic compensator are designed, and a generalized predictive control strategy combining these modules (GPC-DM-RFLM-NCC) is proposed. Firstly, the salp swarm algorithm (SSA) is improved based on the chaotic mapping and Levy flight, an accurate nonlinear hydraulic turbine model is constructed based on the backpropagation neural network (BPNN) and improved SSA (ISSA), and an HTRS simulation platform with nonlinear characteristics is built by combining modules such as water diversion system, servo system, and generator. Then, the irrationality of the commonly used linear hydraulic turbine models in HTRS dynamic process simulation is verified through quantitative calculation. Furthermore, by combining the real-time feedback linearization method and ISSA-based nonlinear characteristic compensator, the GPC-DM-RFLM-NCC is proposed. Finally, the HTRS simulation platform, which consists of GPC, double models, real-time feedback linearization module, and nonlinear characteristic compensator, is built, and the applicability, reliability, and excellent robustness of the proposed GPC-DM-RFLM-NCC are verified by the real data of a hydropower station. • The salp swarm algorithm is optimized based on the chaotic mapping and Levy flight. • A refined model of the hydraulic turbine regulation system containing the precise hydro-turbine model is established. • The irrationality of the popular linear hydraulic turbine model is revealed through quantitative calculation. • A generalized predictive control strategy is proposed considering the nonlinearity of the hydraulic turbine. • Model mismatch caused by feedback linearization is estimated and corrected. [ABSTRACT FROM AUTHOR]

Dynamic simulation of regional integrated energy systems (RIES) is beneficial for improving stability and safety of RIES. However, it is hard to implement a dynamic simulation due to the RIES's complexity caused by the coupled multiple energy sources, especially considering coupling components failure. To address this issue, a novel fault-driven co-simulation strategy for coupled heat-gas-electric system under different states is developed in this study. This strategy includes two steps: (1) the RIES is firstly decomposed into different modules and construct corresponding sub-models; and then (2) the solution sequence of these sub-models is determined according to the system states. Additionally, the strategy also considers the transmission delay of gas and heat. Two typical components failures (combined heat and power unit failure and gas-fired generator unit failure) at a typical industrial park's RIES are selected to validate the dynamic simulation strategy. And results indicate that such strategy can obtain accurate dynamic behavior of RIES after coupling components failures occurs, such as the flow fluctuation of the gas pipeline that lasts for 179 s and the temperature reduction process of the heat node that lasts for more than 35000 s. Therefore, this study is instructive for further development of RIES technology. • A novel dynamic simulation strategy for the RIES is developed. • The RIES considering coupling components failures is studied. • The effects of coupling component failures on subsystems of RIES is analyzed thoroughly. • The transmission delays of both gas and heat are taken into account in simulation of RIES. [ABSTRACT FROM AUTHOR]

The new generation of the district heating system (DHS) has attracted much attention due to its high efficiency. A precise and fast dynamic simulation is the foundation of the optimization and control strategy of a DHS. As a type of heterogeneous system, the DHS has internal components with multiple time scales, which limits accuracy of simulations. However, current studies have either chosen pseudo-dynamic models or have not considered the effect of the internal time scale on the simulation. To solve above problems, a dynamic multi-rate simulation method based on the individual-based model (IBM) is proposed in this paper. According to IBM, a complex system is decoupled into individuals, who interact with each other to form the whole system from bottom-up. During the process of modeling, equations of individuals indicating their dynamic behaviors are all converted into a system of ordinary differential equations (ODEs). And then the ODEs are solved from system level using multi-rate simulation methods. The case study illustrates that the proposed method takes 36.59 s for the 72 h long-term simulation of the DHS containing three components commonly involved and a district heating network, which provides good decision-making information for the optimal control of the system. • Individual-based multi-rate dynamic analysis method for heterogeneous systems. • Abstraction-based programming framework for IBM dynamic simulation. • Short-term simulation verification of a real DHN and long-term dynamic behavior analysis of a virtual DHS. • Compared with the forward Euler method, the proposed method is accurate and fast. [ABSTRACT FROM AUTHOR]

Replacing the baseload providers on the energy market with decarbonized renewable solutions increases frequency dynamics on the grid. In order to handle the concomitant risks and chances linked with this change of paradigm between energy producers and consumers, complex dynamic models are required to optimize energy management strategies. Industrial transcritical carbon dioxide (CO 2) heat pumps, such as the one developed by MAN Energy Solutions Schweiz AG (MAN ES), offer a proven solution for the decarbonization of the district heating sector. Furthermore, they are associated with pathways to increase the usage of this solution for sector coupling applications. This work presents a detailed Modelica model of the high-temperature CO 2 heat pump, focusing on the thermodynamic states of the refrigerant during load variations of the system. In a consecutive step, the model is validated against testbed data of a heat pump from MAN ES with over 35 MW heat supply and a lift from 40 to 100 K. The model results match the testbed data with an accuracy of over 95 % and demonstrate a full coverage of the performance map minimum to maximum speed, providing water-side supply temperatures of 50–109 °C. Realistic dynamics in fast load balancing operation are demonstrated where power consumption was varied by 80 % compared to maximum power within 30 s. Models of this kind are essential for an accurate prediction how decarbonized energy networks react by linking electricity and heat supply together. These predictions are ultimately useful to upgrade or optimize complex control strategies. • A large-scale, transcritical CO 2 heat pump is modeled in Modelica. • The model is successfully validated with measurements from a 35 MW testbed setup. • Motor speed and control valve dynamics variated separately as well as combinations are validated. • Fast dynamics of electrical power consumption (up to 7 MW in 30s) are demonstrated. • The model is qualified for implementation in real plant operation and control. [ABSTRACT FROM AUTHOR]

In this paper, a fully coupled model for a backward bent duct buoy oscillating water column (BBDB-OWC) wave energy converter (WEC) is established, with the consideration of strong transient nonlinear interactions among ocean waves, BBDB hull motion, mooring system, internal water column oscillation, aerodynamics, turbine rotation and the damping effect of the generator. The model is validated by comparison with experimental results, and then used to investigate the transient characteristics and periodic average performance of the WEC under regular wave conditions. The differences in transient hydrodynamic characteristics and air pressure-flow rate relationship between the fully coupled model and the orifice model are compared. The transient characteristics of an impulse turbine under reciprocating and transient airflows are studied. And the effect of wave period, wave height and load torque coefficient on the average performance of the WEC is investigated. • A fully coupled wave-to-electricity model for a BBDB-OWC WEC is established. • Hydrodynamics between the fully coupled model and orifice model are compared. • Transient performance of impulse turbine using fully coupled model is investigated. • Effect of wave conditions and load coefficient on BBDB performance is studied. [ABSTRACT FROM AUTHOR]

Barocaloric refrigeration technology is a promising candidate for next-generation refrigeration technologies attributed to its eco-friendliness, high efficiency, and mechanical stability. To date, research in this field has predominantly focused on the exploration of solid-state refrigerants. However, the development of barocaloric systems is currently hindered by a lack of both prototype models and a comprehensive theoretical foundation. Addressing this gap, this study innovatively introduces the first model of a barocaloric refrigeration system, characterized by efficient hydrostatic pressure transitions and rapid heat and cold extraction. The employed refrigerant, neopentyl glycol, is notable for its low cost and significant barocaloric effect. Through the development of a one-dimensional dynamic numerical model for the system, this study investigates the system's temperature variability and operational efficiency under varying design parameters and operating conditions. Simulations suggest that the system could achieve a maximum COP of 13.1 and a refrigeration capacity of 106.4 W at a temperature span of 10 K. Additionally, the system is capable of reaching a maximum temperature span of 18 K under no-load conditions. This research not only underscores the theoretical viability of barocaloric refrigeration, but also provide crucial theoretical support and guidance for the design and construction of the first-generation barocaloric refrigeration prototype. • A first-generation barocaloric refrigeration prototype was innovatively proposed. • A one-dimensional dynamic model for barocaloric refrigeration is established. • The system achieves a notable COP of 13.1 and refrigeration capacity of 106.4 W. • The system can achieve an impressive maximum temperature span of 18 K. [ABSTRACT FROM AUTHOR]

District Heating Networks are seen as a popular solution for the decarbonation of space and domestic hot water heating by the use of renewables or waste heat. Their design and operation can be enhanced both environmentally and economically through the use of dedicated simulation tools. This work presents a new multicomponent Python-based software library including an efficient steady-state model for the hydraulic simulation and a Lagrange-based dynamic model for the thermal part. The model is verified on real data from a meshed DHN with a granularity of 15 min. For the considered period of 6 days, the model estimated the return temperatures of two heat plants with a mean error of 0.08 K and 0.43 K and standard deviations of 0.56 K and 0.71 K respectively. On the hydraulic part, after applying a fixed correction factor, the error on the pressure differences was estimated in 3 peripheral locations of the network. In the worst case, the relative error distribution had a mean of 0.38% and a standard deviation of 8.74%. Finally, the implemented hydraulic solver achieved a speed improvement over the standard loop method of 17.5%. • A flexible and open-source dynamic simulation framework based on a multicomponent approach is presented. • Reliability is tested on 15-minute metered data from a meshed network. • The implemented hydraulic simulation method is on average 17.5% faster than the loop method. • The RMSE on the return temperatures of heat plants was 0.83 K in the worst case. [ABSTRACT FROM AUTHOR]

Pumped thermal energy storage (PTES) technology offers numerous advantages as a novel form of physical energy storage. However, there needs to be a more dynamic analysis of PTES systems. This paper proposes a dynamic simulation model of the PTES system using a multi-physics domain modeling method to investigate the dynamic response of key system parameters during the system's start-up and variable operating conditions. Additionally, the impact of equipment parameters on system characteristics was analyzed. Furthermore, a comparative analysis was conducted to assess the variation in system characteristics when considering the different working medium properties. The results show that the system cavity volume should be selected as 5 m3, and the initial pressure of the system during the charge/discharge period should be selected as 2.1 MPa and 3.8 MPa, respectively. The system runs to the design operating conditions during the start-up process in about 1400 s. In the process of variable operation conditions, the power load in the charge/discharge period can be increased or reduced from the rated value by gas filling or venting, and the system characteristics change accordingly. The simulation model and research findings will offer theoretical insights for optimizing the design of the PTES system. • A dynamic simulation physical model of the PTES system was proposed. • The dynamic changes in system characteristics were analyzed. • The TES tank's thermal inertia and heat management of the PTES system were analyzed. • The effects of main equipment parameters on system characteristics were analyzed. • System characteristics were compared when using different gas properties. [ABSTRACT FROM AUTHOR]

Compared with the conventional turbofan engine, the adaptive cycle engine (ACE) has more extensive flight envelope and the more types and number of adjustable components. While the performance of each mission profile is improved adaptively, the controller design of profile switching process will face strong flight condition disturbance and internal uncertainty. The traditional control system's single loop controller and discrete switching method of control parameters are to some extent difficult to meet the adaptive and robustness requirements of ACE. Thus, this paper proposed a multi-variable decoupling anti-disturbance controller for ACE based on the results of flight envelope partitioning with similar distances, embedded a state-dependent switching law. By analyzing the impact of inlet disturbances, internal actuator actuation, and random degradation of component performance on different switching laws, the adjust time and overshoot of the controller with state-dependent switching law proposed in this paper are reduced by an average of about 11.91 % and about 9.98 %, and the average thrust linearity and robustness has increased by about 0.096 % and 20.02 %. Finally, the reliability and feasibility of the control system were verified based on a hydraulic driven semi-physical experimental platform, providing reference for more complex and dynamic engine operation control in the future. • Consider external and internal disturbances during the ACE mission profile switching. • A multivariable ADRC controller with state-dependent switching law for ACE is proposed. • The controller robustness was analyzed through stochastic perturbation simulation. • The system reliability was verified based on RVABI semi-physical experimental platform. [ABSTRACT FROM AUTHOR]

Dynamic simulation of thermal systems is crucial for their optimal control but facing the challenge of balancing calculation accuracy and efficiency, where numerically high-efficient and accurate heat exchanger (HX) modeling is a key. Herein, we propose a frequency domain model for HXs' dynamic simulation in the to meet this challenge. The governing equations of HXs are first converted to frequency domain through Fourier transform, and the analytical solution of the converted equations yields the frequency domain HX model in the form of transfer matrix that connects the inlet temperature variations and outlet temperature responses. Furthermore, integrating transfer matrices of HXs into the system's transfer matrix enables a high-efficiency thermal system simulation. Numerical cases of a single HX, a HX network, a district heating network, and a thermodynamic cycle are used to validate the developed method and demonstrate its efficacy by comparing it against finite difference/volume method. Results show that the proposed method could reduce the calculation time by 2–3 orders of magnitude, and the maximum deviation of node temperature is around 1 K. The proposed method can be a powerful tool for the analysis of thermal systems and potentially integrated energy systems. • Propose a dynamic frequency domain model for heat exchangers with Fourier transform. • Analytical solution of the dynamic model gives the outlet temperatures directly. • The proposed HX model can be directly integrated in thermal system simulation. • Calculation time is reduced by 2–3 orders of magnitude with the same accuracy. [ABSTRACT FROM AUTHOR]