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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]

Reducing carbon footprints and enhancing operational flexibility are crucial for the future development of coal-fired power plants (CFPPs). This necessitates the deployment of post-combustion carbon capture (PCC) and molten-salt heat storage (MSHS) systems. Given the various integration schemes and complex interactions, understanding the comprehensive performance of the integrated CFPP-PCC-MSHS system is important. This paper proposes an integration scheme for 1000MWe ultra-supercritical CFPP, solvent-based PCC and MSHS, achieving cascade energy utilization. A dynamic simulation model for the CFPP-PCC-MSHS system is developed to understand the dynamic couplings between subsystems. Comprehensive performance analyses are conducted to evaluate the thermodynamics, flexibility and safety of the integrated system under various operating conditions. Simulation results indicate that deploying MSHS reduces the thermal and exergy efficiencies of the CFPP-PCC system by 0.18 % and 0.19 %, respectively, but effectively expands the adjustable power load range by 6.08 % under the fixed 90 % CO 2 capture rate mode. Meanwhile, the integration of MSHS offers alternative pathways to improve the power ramping rate to 13.33 MW/min. The heat charging/discharging process of MSHS induces fluctuations in temperature and pressure within the turbine, potentially affecting plant operating safety. This paper provides useful insights for the design, retrofit and operation of new generation of CFPPs. • A dynamic model of the integrated CFPP-PCC-MSHS system is developed. • The integration of MSHS reduces thermal and exergy efficiencies by 0.18 % and 0.19 %. • MSHS enlarges power range of CFPP-PCC by 6.08 % under 90 % CO 2 capture condition. • Deploying MSHS offers effective pathway to improve the power ramping rate of CFPP. • Deploying MSHS induces pressure and temperature variations at each turbine stage. [ABSTRACT FROM AUTHOR]

This study implements a comprehensive dynamic simulation using a moving-boundary method to characterize an organic Rankine cycle under assumption-free operating conditions. The novelty of the model lies in its unique methodology for determining the state vector variables and initial conditions of the system, particularly in integrating sub-models, notably the model of liquid receiver. Consequently, the implemented dynamic model accurately forecasts the system's performance, focusing solely on the boundary conditions. A comprehensive dynamic model is constructed, encompassing a wide range of scenarios and facilitating the interchangeability of models as required. One notable advantage of the model is its systematic approach, which begins each simulation by determining the system's initial conditions before conducting the dynamic model in parametric and dynamic studies. The capability and accuracy of model is confirmed through comparison with experimental data under various steady-state and dynamic conditions, while adhering to the main rules of mass and energy conservation. The prediction accuracy of the model is evaluated by mean absolute percent error. According to the results, the maximum deviations of simulation results mostly are less than 11 %. • Using moving-boundary method to simulate an ORC under assumption-free conditions. • Using unique method for determining state vector variables and initial conditions. • Dynamic model precisely forecasts system performance, focusing on boundary conditions. • The maximum deviations between the simulation and experimental results are 11 %. • The simulation shows ORC's dynamic behavior when input conditions vary. [ABSTRACT FROM AUTHOR]

The railway sector's energy impact is increasing, and this trend is expected to persist over the next decade. Particularly, the energy consumption of Heating Ventilation, and Air Conditioning (HVAC) systems is significant among various services provided on board (30 % of total energy requirements) due to the rising attention to passengers' thermal comfort. In this framework, this research proposes an innovative method for enhancing indoor thermal comfort while also studying the associated energy consequences. It consists of an advanced passenger-centric-control framework for HVAC systems that prioritizes comfort, utilising optimized indoor air setpoints, which surpasses the rule-based control logic proposed by the existing standards. To analyse the proposed control framework, a novel mathematical model for the energy, economic, and environmental performance analyses of train HVAC systems, which can incorporate weather data associated with actual railway paths, is developed and validated. To prove the potential of the proposed method, a proof-of-concept analysis is conducted. In particular, for an existing railway coach operating in Italy, the standard and the innovative control logic are tested and compared. The results show an interesting thermal comfort hours increase (≃+1000 h) and energy savings (−27 % yearly), proving the benefits potentially achievable by adopting the proposed method. • Train cars' energy and thermal comfort assessment through dynamic simulation. • Investigation on railway carriages' indoor thermal comfort enhancement. • Development of an innovative passenger-centric HVAC system control framework. • Improved thermal comfort (+1000 h) and energy efficiency (−2.5MWh el) are achieved. [ABSTRACT FROM AUTHOR]

Heat–power decoupling is a key issue to be addressed for the combined heat and power (CHP) unit to enhance its operational flexibility, and utilizing heat storage in district heating systems represents a viable approach. The widespread adoption of heat pumps to boost heating network also increases the complexity of managing heat storage, and the quantitative impact of heat storage has significant implications during operation. To this end, dynamic models of heating networks and heat pumps were developed. A metric, the maximum maintenance time, was established to quantitatively assess heat storage utilization. Dynamic simulations and performance analyses were conducted on a 330 MW CHP unit. The results indicate that by employing heat storage, the feasible maximum and minimum output power of the heating system can be increased by 20 MW and decreased by 45.5 MW, respectively. With the integration of a heat pump, these values can further increase by 9 MW and decrease by 158 MW, respectively, significantly enhancing the operational flexibility of CHP unit. • Dynamic models of CHP unit, heating networks and heat pump were developed. • A new index to evaluate the heat storage capacity that can be used is proposed. • Dynamic simulation and performance analysis were conducted with a 330 MW CHP unit. • The integration of heat pump can increase heat storage capacity for peak shaving. • The feasible minimum output power of the CHP unit can be decreased by 158 MW. [ABSTRACT FROM AUTHOR]

In this study, various experimental tests were carried out with a 1 MW th circulating fluidized bed pilot plant at the Technical University of Darmstadt to investigate the combustion and co-combustion behaviour of different fuels under load change conditions in air and oxyfuel mode. The combustion tests were carried out with low-calorific lignite and hard coal as reference cases for co-combustion. In the co-combustion experimental tests, straw pellets, and refuse-derived fuels (high and low calorific) were used as co-fuels for coal. In addition, a comprehensive dynamic 1.5-D process simulation model was established for a 1 MW th circulating fluidized bed pilot plant. The model created with the "APROS" software precisely reproduces both the gas/solids and the water/steam side of the 1 MW th pilot plant. The dynamic process simulation model was first validated at various steady-state operation points and, in a second step, at various dynamic load changes. The numerical results, such as the pressure drop and temperature profiles along the fluidized bed riser as well as the flue gas concentrations at the cyclone outlet, were compared with the measurements and showed agreement during the long-term tests of the combustion and co-combustion processes. • A series of combustion and co-combustion tests were carried out in a 1 MW th CFB pilot plant. • The tests were carried out using different fuels under load cycling in air and in oxyfuel modes. • In all tests, stable reactor operation was achieved under load cycling in air and in oxyfuel modes. • A 1.5-D dynamic process simulation model was developed and validated with experimental tests. • The numerical results are in good agreement with the measurements obtained from the pilot plant. [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]

The progressive increase of renewable energy sources (RES) share during past decade strongly reflects on power system operating conditions. Romania is the South Eastern European country with the largest RES generating capacity. This paper proposes a novel method for assessing the impact on national power systems operation of integrating high shares of RES. Specifically, the method addresses first a variability analysis of RES production, based on historical records over 10 years for the Romanian power system. Wind energy is selected as the RES with the widest confidence interval, thus generating the largest power output fluctuations. Further, different simulation scenarios are defined in terms of variable wind energy share. The values obtained are integrated in a scaled simplified model, implemented in PSS/E. The impact of generating sets based on wind energy employment on voltage magnitude and transient time is assessed in fault conditions. Considering that the simulation scenarios defined comprise variable wind energy generation shares, this study emphasizes the impact of its dynamics on power systems. Simulation results highlight the negative influence of increasing wind energy share on the analyzed quantities. The outcomes of this research can suggest a particular analysis approach useful in studying power systems operation. • Momentary power recordings of a real power system underlie the research. • Different scenarios are defined varying load and wind energy share. • CDF is used to appraise the adequacy of the values selected for simulations. • Wind energy impact at different system loadings is analyzed subsequent faults. • Wind share increase negatively affects voltage evolution and transient time. [ABSTRACT FROM AUTHOR]

Efficient low consumption buildings require the building envelope to be scrupulously designed from an early stage. Passive solar technologies, such as the Trombe wall, can contribute to the reduction of the heating energy demand and, if properly operated, they can also impact the building summer behaviour. The use of such a solution has been limited, especially in warm climates, as severe problems of indoor overheating can occur even beyond the cooling period. Through the dynamic simulation software DesignBuilder, the authors investigated the energy performance of two different residential buildings equipped with a Trombe wall in different climatic contexts. The authors proposed the adoption of proper ventilation strategies to further reduce cooling needs. The validity and effectiveness of the proposed solutions was verified in warm climates where the Trombe reduced heating requirements by up to 71.7% and decreased the cooling energy demand by 36.1%. In a cold climate, heating savings were 18.2% with a cooling energy reduction of 42.4%. The study highlighted the fundamental importance of the definition of proper ventilation strategies based on climatic parameters to prevent drawbacks in intermediate seasons, with an evident limitation of the system performance. • Summer and winter dynamic performance of a Trombe wall was assessed in three localities. • Summer ventilation strategies of a Trombe wall have been investigated. • Considerable reductions of yearly energy requirements were found. [ABSTRACT FROM AUTHOR]

Among the various heating technologies that can be applied to urban areas district heating is recognized to allow significant reduction in primary energy consumption, provided that the system is properly designed and operated. Thermo-fluid dynamic simulation tools can be of extreme importance in order to achieve this objective. This paper aims at presenting a thermo fluid dynamic model for the detailed simulation of large district heating network and showing how it can be usefully applied to examine options for the reduction of primary energy consumption. The model is tested using experimental data and then applied for analyzing transient operations of the Turin district heating network, which is the largest network in Italy and one of the largest in Europe. A comparison between simulations and experimental results shows that the model is able to predict the temperature in the nodes of the network with good accuracy. The thermal power required to each plant is also calculated with a good level of accuracy. The model can be used for the simulation of operational strategies, thus representing a versatile and important tool for the implementation of advanced management such as the installation of local storage units or the variation of user request schedules. • A thermo-fluid dynamic model for the detailed simulation of large DHNs is proposed. • The model receives data from the substations as the input. • The transient simulation of the Turin DHN is compared with measurements. • The model can be applied to implement advanced management strategies. [ABSTRACT FROM AUTHOR]

Optimizing district heating (DH) systems in a holistic manner is often impeded by the computational complexities associated with network modeling. This study introduces a novel, efficient and theoretically accurate method for dynamic thermal modelling of DH pipes. The approach is to track water frontiers traveling along the pipe using discrete event simulation (DES) paradigm. As the DES method is based on variable time steps, the computational effort is significantly reduced compared to earlier methods. The proposed model can compute outlet water temperature, temperature profile along the pipe, and heat loss based on variable inlet temperature and flow rate. The DES model was validated by comparison with real measurements of a long DH pipe. Four variants of the model with different temperature profile assumptions and interpolation methods were compared. Numerical results show that the DES model can accurately predict outlet water temperature with a maximum discrepancy of 0.52 °C. The mean error of simulated outlet temperature was −0.01 ± 0.02 °C. Average computation time for 24-h simulation was 59 μs. Overall, this study shows that the DES method is appropriate for variable time step simulation for DH pipe, potentially, for network simulation. Our study may also inspire variable time step implementation in other energy applications. • New accurate method for dynamic thermal modelling of district heating pipe. • Lagrangian modelling approach with variable time steps. • Detailed calculation of temperature profile and heat loss. • Fast implementation using the Discrete Event Simulation paradigm. • Model is validated by comparison with real measurement data. [ABSTRACT FROM AUTHOR]

A novel operation mode of constant volume discharging process for advanced adiabatic compressed air energy storage (AA-CAES) is proposed, which achieves a constant output power by throttling and air supplementation. The dynamic model of the expansion process was developed based on the conservation of mass and energy of the open system. The reliability of the turbine and air storage tank models was verified. The results of the energy and exergy analysis of the expansion process show. • Propose a novel constant power operation mode of constant volume discharging process for AA-CAES. • Adopt a method of adjusting the inlet pressure of the turbine to change working state. • Analyze the first and second laws of thermodynamics for the dynamic process of discharging. • The proposed constant power operation mode has higher efficiency. [ABSTRACT FROM AUTHOR]

Waste heat recovery from buildings and/or industrial processes for generating different kinds of energy such as electricity, cooling, and heating is very effective for achieving higher efficiency of supply, reduced energy consumption, and lower carbon footprint. In this research, a novel waste heat-driven combined Kalina-Organic Rankine Cycle system for simultaneous supply of cooling, heating, and power is proposed, optimized, and investigated. For this, based on a parametric study, the system is analyzed from a 4E (energy, exergy, economic, environmental) perspective. Then, the cycle is optimized by using response surface methodology and taking exergy and economic parameters as the objectives. The simulations are conducted in TRNSYS, and the design of experiments technique is used for finding the best combination of the design variables. The possibility of using the proposed Cogeneration Cooling, Heating and Power System (CCHPS) for providing the energy demand of some buildings in Dubai is investigated. The results reveal exergy efficiencies of 54.16%, a total cost of 23458.07 $/years for the designed cycle. • A novel waste heat-driven combined Kalina-Organic Rankine Cycle system. • The system is analyzed from a 4E (energy, exergy, economic, environmental) perspective. • The cycle is optimized by using response surface methodology. • The results reveal exergy efficiencies of 54.16%, a total cost of 23458.07 $/years for the designed cycle. [ABSTRACT FROM AUTHOR]

An accurate and efficient model is the foundation for dynamic characteristics analysis and control design of nuclear reactors. Nevertheless, the widely-used mechanistic models of nuclear reactors inevitably have some deviations from the actual reactors due to inaccurate model parameters and model assumptions. This paper proposes a hybrid mechanistic and neural network modeling method for nuclear reactors to eliminate or minimizing these deviations. The high-efficiency point reactor kinetics model was adopted as the mechanistic reactor core model, and the simulation results obtained using the commercial program RELAP5 were taken as the reference operational data, based on which the reactivity feedback in the mechanistic model that is difficult to be accurately determined during reactor operations was calibrated using a genetic algorithm optimized BP neural network. Dynamic simulation results of a Generation III large pressured water reactor under three typical reactivity change transients show that the core power and outlet coolant temperature obtained with the hybrid model match much better with the reference results than those of the mechanistic model, demonstrating that the hybrid modeling method can improve the accuracy of the mechanistic reactor model effectively. This study can provide a valuable reference for accurate and efficient modeling of complex systems. • A hybrid mechanistic and neural network modeling method was developed for nuclear reactors. • A novel idea for exact core feedback reactivity prediction using neural network was proposed. • Genetic algorithm was adopted to optimize the neural network parameters. • Reactor mechanistic model accuracy can be greatly improved using the method. [ABSTRACT FROM AUTHOR]

Solar energy systems have been extensively studied for their potential to reduce greenhouse gas emissions and their economic feasibility in buildings. However, due to the high initial cost, the implementation of these systems has been limited. This study proposes an innovative energy system, incorporating Photovoltaic Thermal (PVT) technology without batteries and heaters, and ejector cooling for smart buildings that can interact with the power grid. The proposed system aims to offset the energy costs of buildings by selling excess electricity to the grid. Both thermodynamic and economic analyses were conducted using TRNSYS software, and optimization was applied to meet maximum exergy efficiency and minimum cost objectives. Results indicate that the maximum annual exergy efficiency of the system can reach 21.98%, while the minimum total production cost unit is $22.48/MWh. Operating conditions yield an annual exergy efficiency of 14.18%, with a total production cost unit of $34.01/MWh. Overall, findings demonstrate that this proposed system can efficiently provide electricity to the building while offering surplus energy for sale to the grid. • The dynamic smart simulation for the trigeneration energy system is designed. • This system is analyzed from the energy, exergy, and economic point of view. • The best condition is obtained by optimizing decision variables. • An ejector cooling system is used for the reduced consumption of electricity. • Battery and storage tanks are not used in this system to reduce costs. [ABSTRACT FROM AUTHOR]

Selective catalytic reduction (SCR) technology is widely applied for flue gas denitrification in coal-fired power plants. Given the high penetration of renewable power, coal-fired power plants should operate flexibly to support power grid peak regulation. However, the flexible operation of coal-fired power plants often causes transient overshoot of the NOx outlet concentration and NH 3 slip, and restricting the clean and reliable operation of coal-fired power plants is a difficult issue. In this study, a dynamic model of the coal-fired power plant is developed, and the characteristics of a denitrification system during load cycling transient processes were evaluated. Then, an improved control strategy for the denitrification system using cooperative control of NH 3 injection and flue gas temperature is proposed. Moreover, the control targets of NH 3 injection and flue gas temperature are analytically derived. The NOx outlet concentration exceeds the standard value by 14.22 and 6.80 mg m−3, respectively, during the loading down processes and loading up processes with the original control strategy. When the improved control strategy is adopted, the NOx outlet concentration can be controlled to be smaller than the standard value, and the NH 3 slip can be controlled well. • The influence of flue gas temperature on SCR reaction was mathematically derived. • A new co-control strategy of NH3 injection and temperature was proposed. • Transient overshoot of NOx outlet concentration can be avoided. • The N H 3 slip can be reduced significantly with improved control strategy. [ABSTRACT FROM AUTHOR]

The flexibility of the coal-fired boiler depends on the control system, which is designed according to its dynamic characteristics. In this paper, a detailed dynamic model of a supercritical coal-fired boiler is developed in Dymola, and the necessary control models are built. The model is validated against the design values under various conditions with a maximum error of 2.19%. The model is further validated by comparing dynamic simulation results with operating data. Then, the dynamic behavior of the boiler is analyzed under the single- and two-parameter disturbances. When the feedwater temperature, feedwater flow, and coal quantity are all disturbed by −5%, the maximum deviations of the live steam temperature are −21 °C, +32 °C, and −34 °C, respectively. Compared to the simultaneous change of feedwater and fuel, the maximum value of the live steam temperature is reduced by 21.56 °C when the coal quantity is changed 100 s before the feedwater flow. Besides, a first-order inertia compensation element is developed ahead of the feedwater flow command, which effectively improves the performance of the water-fuel ratio control. As the load-variation rate increases, the deviation in the transient process of the thermodynamic parameters increases, and the time required for stabilization lengthens. • A detailed dynamic model of a supercritical coal-fired boiler is developed. • The model is validated for dynamic performance using measured plant data. • The response time and maximum deviation of main parameters are evaluated. • Adding a first-order inertia element before feedwater improves water-fuel control. [ABSTRACT FROM AUTHOR]

Supercritical water gasification (SCWG) technology can convert biomass into hydrogen rich gas and biochar. Fluidized bed reactor is promising for the industrialization of this technology, and the reactor dynamic performance study is of great significance for its scaling up. However, current simulation studies mainly focus on steady-state analysis using Computational Fluid Dynamics (CFD) software, it is difficult to conduct dynamic study due to its high computational costs. To this end, a reactor network model (RNM) that accounts for the flow, heat transfer, and kinetic dynamics for fluidized bed reactor is firstly developed based on the partitioning theory, which can reduce the computation time of dynamic simulation from several days to seconds. Additionally, extensive open-loop simulations of the RNM are carried out to generate the dataset for the development of a recurrent neural network (RNN) model. Additionally, current studies mainly focus on open-loop simulation, closed loop optimization is absent. To this end, a framework for building a machine learning (ML) model and a ML-based nonlinear predictive control scheme is developed. Model predictive control (MPC) schemes based on the RNN model is used to optimize the SCWG process to achieve multiple objectives, such as maximizing hydrogen yield and carbon yield. The open loop simulation results demonstrate that H 2 yield decreases from 0.00022 to 0.0002 kg s−1 with temperature reducing from 700 to 600 °C. To increase H 2 yield to the setpoint, MPC increases temperature and mass flowrate to 708 °C and 417.57 kg h−1. Additionally, MPC increases carbon yield and minimizing CO 2 yield by decreasing temperature to 475 °C and increasing mass flowrate to 407.38 kg h−1. • Proposed the reactor network model (RNM) for SCW fluidized bed reactor (SCWFBR). • Proposed Machine-learning based Model Predictive Control (MPC) scheme for SCWFBR. • Investigated dynamic properties, optimization and control of SCWFBR. • C is maximized and CO 2 is minimized at 475 °C and mass flowrate of 407 kg/h. • H 2 reaches the set value, 1.85 kmol/h at 708 °C and mass flowrate of 417.57 kg/h. [ABSTRACT FROM AUTHOR]

A dynamic model of a compressed gas energy storage system is constructed in this paper to discover the system's non-equilibrium nature. Meanwhile, the dynamic characteristics of the CO 2 binary mixture (i.e., CO 2 /propane, CO 2 /propylene, CO 2 /R161, CO 2 /R32, and CO 2 /DME) based system are first studied through energy and exergy analyses. Performance indicators are considered, including round trip efficiency, exergy efficiency, energy density, discharge time, and average power output. The effects of tank volume and ambient temperature on the system performance are analyzed. According to the results, although the round trip efficiency of the CO 2 mixture system is reduced by about 0.68%–11.97% compared to pure CO 2 , the compressor performance and the system pressure stability are improved. When the tank volume increases from 10,000 m3 to 15,000 m3, the system round trip efficiency increases by 0.16%–0.33%. A further improvement of round trip efficiency for the CO 2 mixture is found compared to pure CO 2 at higher ambient temperature. This paper demonstrates the dynamic operational characteristics of the compressed gas energy storage system when using different CO 2 binary mixtures, providing a reference for optimizing related systems. Potential scenarios and applications for the CO 2 binary mixture are discussed for future research. • A dynamic model of Compressed CO 2 binary mixture Energy Storage is constructed. • The effects of different CO 2 binary mixtures on dynamic performance are compared. • The effects of storage pressure and ambient temperature on performance are analyzed. • The RTE of CO 2 mixture system is reduced by 0.68%–11.97% compared to pure CO 2. • A 1 K increase in ambient temperature results in a 5% increase in storage density. [ABSTRACT FROM AUTHOR]

This paper presents a new thermo-hydraulic model for district heating systems simulations, which aims at being a fast and accurate tool to simulate highly renewable networks characterized by fluctuating energy profiles. The main novel aspect of the tool lies in the heat transmission modelling over long pipes based on a Lagrangian numerical approach. In comparison to other existing models, this approach significantly reduces computational time and it increases results' accuracy. The elaborated method avoids numerical diffusion in the results and consequently allows proper prediction of temperature propagation, especially in case of fast changes of fluctuating profiles. The tool is built following a modular procedural programming approach in order to facilitate the simulation of multicomponent system. Thanks to its modular structure, every components of the system is built with the same structure that is differently declined according to each component's requirements. In this way, new additional elements' models easily fit the existing ones. The model is validated under real operating conditions with hourly monitoring data of an Italian district heating network. The results show good correspondence also in the most peripheral nodes of the network, where the largest deviations are normally encountered, thus making the model a reliable and fast simulation tool for district heating network design and operational control. • A model for fast and realistic simulation of district heating network is presented. • The heat-transmission pipe is modelled with the method of characteristics with a Lagrangian approach. • An entire big scale district heating model is validated with yearly monitoring data, proving the model usability. • Simulation results agree with temperatures at distant user's substations and peak demand at generation plant. [ABSTRACT FROM AUTHOR]

The transition of existing second-generation district heating networks (DHN) towards lower temperature levels for operation can lead to energy savings and to fewer constraints for the pipes and substations. However, retrofitting measures on the distribution network are often inevitable in order to still guarantee heat demand satisfaction. This paper presents a methodology to efficiently identify and alleviate existing limitations for temperature lowering in the design of a DHN distribution network. After having identified the most restrictive assets through existing methods, we apply a multi-objective optimization on a dynamical thermal hydraulic simulator for selecting the most efficient modifications on the DHN to attain our target. We apply the developed methodology on a test case representing real DHN operation, and featuring 60 consumers and 260 pipes. The maximum operating temperature is decreased significantly and various modifications for retrofitting are proposed as a set of optimal solutions, forming a Pareto front approximation. This work, through the combined use of a non-linear, dynamic simulator, and a multi-objective optimization framework, allows also to consider a variety of assets (exchangers, pumps, pipes ...) as retrofitting targets and, thus, potentially identifies interesting solutions beyond common practices. • Lowering the supply temperature in district heating network can require the modification of the network. • The modifications of pipes, substations or pumps can be optimum using multi-objective optimization. • A dynamic thermohydraulic simulation is needed to ensure the optimality of a solution. [ABSTRACT FROM AUTHOR]

In this paper a novel dynamic simulation model for enhancing the sustainability of transportation systems equipped with diesel co-generators is presented. In each simulation time step of the carried out energy performance analyses, the best operation/combination of generators as well as their optimal part load ratio are determined with the aim to achieve the minimum fuel consumption. Input to the model are: size of each installed diesel generator; number of engines; required power profile; route scheduling and hourly weather data. The developed simulation model is implemented in TRNSYS environment. Here, a new in-house TRNSYS type written in Fortran is also included. With the presented approach - especially helpful for cruise ship designers, manufacturers and owners - new design criteria and useful technical results can be obtained. To show the capability of the tool a novel case study is presented. It concerns on an existing cruise ship to be refurbished from the energy point of view. Here, four diesel generators are installed on-board. The ship energy system includes five electric chillers, two auxiliary boilers, two reverse osmosis and two multi-stage flash desalination devices (driven by the diesel generators waste heat recoveries). Simulation results show remarkable energy savings obtained through the proposed optimization approach. Specifically, a maximum primary energy saving of about 15 GWh/y is obtained compared to the initial reference scenario. It corresponds to a fuel consumption reduction of 2.5 kt/y (-1.6 M$/y) and to an avoided CO 2 emission of 8.0 kt/y. • Proposed model improves sustainability of ships through unit commitment approach. • Optimization of the generators operating sequence increases a ship's energy efficiency. • The model dynamically adapts waste heat recovery to different operating conditions. • A novel algorithm identifies the best running sequence for on-board generators. • Primary energy saving of 1.92% and fuel consumption reduction of 1.73% are obtained. [ABSTRACT FROM AUTHOR]

This paper presents a novel dynamic simulation model for the analysis of a hybrid turboexpander system coupled with innovative high-vacuum solar thermal collectors. The model is developed in MatLab and it is able to dynamically calculate the energy, exergy, environmental, and economic performances of the investigated system, by taking into account the hourly fluctuation of thermodynamic and economic parameters (e.g. electricity cost, natural gas temperature, and flow rates, etc.). In addition, a computer-based Design of Experiment (DoE) approach was implemented for achieving the optimal design of the proposed system. A suitable case study is presented in order to show the capabilities of the developed simulation tool. Conventional and non-conventional decompression systems located in the weather zone of Messina (South-Italy) are investigated with the aim of assessing the optimal system configuration. By means of the computer-based DoE analysis, the optimal values of several design parameters (such as the number of solar thermal collectors, the volume of the hot water storage tank, and the size of the water loop pump) are calculated. Numerical results show significant primary energy savings (1.36 TWh/year) and avoided carbon dioxide emissions (348 t CO2 /year). From the economic point of view, a feasible simple pay-back period of 4.51 years is achieved. The destroyed exergy of the system components are calculated, obtaining the highest value for the turbo-expander, equal to 12.0 TWh/year. • Dynamic modelling and simulation of natural gas turbo-expander system. • Energy, exergy and economic analysis of the turbo-expander system coupled to solar thermal collector field. • DoE analysis for the optimization of the solar field. • Analysis of a case study of pressure reduction station. • Confirmed system feasibility by achieved energy, economic and environmental results. [ABSTRACT FROM AUTHOR]

District Heating (DH) networks are getting closer to the concept of "Smart Grids" to deal with the contribution of new technologies and paradigms like Renewable Energy Sources, Distributed Generation and Storage, and Low-Temperature District Heating. This requires good anticipation of the system's dynamics with the objective of improving control. This work proposes a model based on the Finite Volumes method for anticipating the dynamics in DH systems. Its application to branched network topologies gives the delay between the change in the settings at the generation points and the time they are perceived by the different substation in the network, which is a prerequisite for system design, operation planning and optimal control. The model is tested in a 6 Node branched network with the main topology elements being represented (junctions, splits, etc.); real demand data is used at the consumption nodes. A comparison between the model developed by the authors and the existing Finite Volumes method is also presented for the proposed topology. These results shed light on the needs and opportunities in DH, mainly for ICT implementation, energy storage location and management, and enhanced control in the smart energy networks context. • New approach to model heat transport in dynamic District Heating networks. • The Electrical Analogy gives robustness to the Finite Volumes method. • The Modified method has better accuracy in variable systems. • Approach is able to evaluate the operation of DH networks in a dynamic environment. [ABSTRACT FROM AUTHOR]

Engineering efforts to handle contemporary energy supply challenges and mitigate pollutant emission lead towards more complicated systems. Power plants are supplementing with additional processing units, alternative production modes and higher level of automation. Wind and solar sources, biomass combustion, gasification, carbon capture and storage (CCS), and cogeneration have appeared as important players in the energy systems. The increasing complexity comprises a risk that the systems become less manageable and less stable than currently. Traditional steady-state engineering methods cannot fully address these challenges that are inherently dynamic in their nature. Dynamic process simulation appears as important tool to the systems design and optimisation tasks. A large variety of dynamic process modelling and simulation approaches has been presented recent years. This paper presents a brief review of methods and simulation packages that are generally applied for studying energy systems' transient behaviour. A CCS capable power plant is presented as an example of utilizing dynamic process simulation for virtual evaluation of a novel electricity production concept. The modelling was performed using two simulators Apros and Aspen Plus Dynamics, which were linked together for dynamic simulating the full chain of cryogenic oxygen distillation, oxy combustion, turbine islands and carbon dioxide purification and liquefaction operations. • Dynamic simulations for design and optimisation of contemporary energy systems have been reviewed. • A case study for evaluating oxy combustion CFB boiler cycle with carbon capturing is presented. • Co-simulation with two dynamic process simulation software: Apros and Aspen Plus Dynamics were shown. • Flexibility aspects of oxy combustion power plant are discussed. [ABSTRACT FROM AUTHOR]

Thermoeconomic analysis allows for a deep understanding of the cost formation process within an energy system, providing insights into the possible routes for improvement. Several thermoeconomic approaches are well-established for application in systems with steady operating conditions, such as power plants, while a limited number of applications to air-conditioning systems in buildings have been proposed, due to the difficulties in dealing with very irregular load profiles and unsteady plant operating conditions. This study investigates the potential of Thermoeconomics as a support for decision making in building energy systems, proving its capability to identify trade-offs between cost fractions related to capital investment and efficiency. The proposed approach to thermoeconomic analysis of dynamic systems introduces some methodological novelties, such as the use of a preliminary dynamic simulation to calculate "averaged energy flows" on an arbitrary time basis and the adoption of a flexible super-structure, capable to reflect the different operating conditions throughout the year. That is then applied to a school dwelling, supplied with space heating and cooling and a mechanical ventilation Air Handling Unit. The sources of irreversibility are evaluated and the main targets for improvement are identified, calculating the trends of exergetic, exergoeconomic and exergoenvironmental costs on a monthly basis. • An innovative dynamic thermoeconomic analysis is performed for an air-conditioning system. • Symbolic Thermoeconomics is applied for exergetic and exergoeconomic cost accounting. • A novel flexible "productive superstructure" is defined for the dynamic operating conditions. • A simple guide workflow is given for Symbolic Thermoeconomics dynamic application. • Application to a school dwelling allowed to calculate average costs on a monthly basis. [ABSTRACT FROM AUTHOR]

In this paper four different air conditioning systems designed for a building located in Naples, are investigated. The first plant is based on distributed energy conversion systems: twelve boilers and twelve chillers. In the second solution the space heating demand is satisfied by a centralised boiler while the cooling load is met by a centralised chiller. The third option consists of a trigeneration plant. The fourth configuration is composed by an electric heat pump satisfying space heating and cooling and a centralised boiler used for domestic needs. Dynamic simulations have been carried out to compare the energy and environmental performance of the centralised systems with those achieved by the distributed one. Besides, as further loads, for the third option, two electric vehicles charged by the cogenerated electricity surplus are compared to diesel cars. The results show that the best energy and environmental performance are achieved by the cogenerator-based system, with a primary energy demand of 120.6 MWh/y and equivalent dioxide carbon emissions of 25.2 t/y in the configuration without vehicles. This result is also confirmed with electric and diesel vehicles. The energy competitiveness of the plant with the electric heat pump is achieved only in a scenario with a high penetration of renewable energy sources. • Autonomous and centralised air conditioning systems are compared. • Dynamic simulations are performed to carry out energy and environmental analyses. • A multi-purpose block of flats is considered as users simulated. • Electric and diesel vehicles are introduced in the analysis. • A sensitivity analysis is carried out considering the renewable energy sources contribution. [ABSTRACT FROM AUTHOR]

Given the massive scientific progress on near zero-energy targets, occupant behavior has become a key variable affecting building energy performance. In this view, the paper builds upon previous contributions to analyze real occupancy of an office building with peer occupants monitored for 2 years. After assessing that peers do not behave the same and do not control equivalently the indoors, acknowledged occupancy models and field-collected data are compared through dynamic simulation on daily and annual bases. To this aim data-driven occupancy models are developed based on the collected data. Moreover, neural response tests are performed on selected occupants to study their emotional status. The estimation of annual energy need highlights the influence of building occupancy. In fact, the simulated building energy consumption can vary by up to 20% by only selecting the occupancy simulation scheme. Moreover, non-negligible discrepancies in terms of value gap and time schedule daily profiles are still found between predicted and measured variables when considering the data-driven models, since they do not take into account multi-physical and non-physical (personal) stimuli. The first results of neural experiment show the role of personal non-physical factors in the inconsistent reaction to thermal stimuli, as key driver for the associated behavior. • Occupant behavior long-term data-driven models are developed for office buildings. • Standard occupancy and data-driven models are compared via dynamic simulation. • Neural response tests are used to correlate occupants' emotions to environmental conditions. • Building final energy need significantly varies with varying occupancy model. • Understanding human-centered non-physical drivers leads to more reliable models. [ABSTRACT FROM AUTHOR]

A reliable preliminary forecast of heating energy demand of a building by using a detailed dynamic simulation software typically requires an in-depth knowledge of the thermal balance, several input data and a very skilled user. The authors will describe how to use Artificial Neural Networks to predict the demand for thermal energy linked to the winter climatization of non-residential buildings. To train the neural network it was necessary to develop an accurate energy database that represents the basis of the training of a specific Artificial Neural Networks. Data came from detailed dynamic simulations performed in the TRNSYS environment. The models were built according to the standards and laws of building energy requirements in seven different European countries, for 3 cities in each country and with 13 different shape factors, obtaining 2184 detailed dynamic simulations of non-residential buildings designed with high energy performances. The authors identified the best ANN topology developing a tool for determining, both quickly and simply, the heating energy demand of a non-residential building, knowing only 12 well-known thermo-physical parameters and without any computational cost or knowledge of the thermal balance. The reliability of this approach is demonstrated by the low standard deviation less than 5 kWh/(m2·year). Image 1 • Alternative method to solve the building energy balance without any computational cost. • Development of an ANN to assess of the energy performance of non residential building. • Several dynamic models in different location with different shape factor were built TRNSYS. • Implementation and creation of an organised energy database set. [ABSTRACT FROM AUTHOR]

Based on a quasi 3-D steady model inside and a 2-D unsteady model outside of the borehole of ground heat exchanger(GHE), the relationship between the heat exchange rate per depth of borehole and main parameters (center-to-center distance of two branch pipes, radius and depth of the borehole) has been analyzed. The rational values of those design parameters with considering the heat exchange rate per depth of borehole are obtained. The dynamic simulations of underground temperature field (UTF) of single-pipe and pipe-group of U-tube GHE have been conducted by ANSYS. The change rules of UTF are obtained when ground source heat pump(GSHP) has experienced a complete cooling and heating cycle during one year. The simulation results of a single-pipe show that the action radius of borehole is 1.9 m, i.e., it is reasonable that the borehole center-to-center distance is 3.8 m. The simulation results of pipe-group indicate that temperature of the soil center encircled by four boreholes at the beginning of heating in winter is higher than the initial temperature of soil, but it is in opposite for cooling in summer, which is beneficial to the efficient operation of GSHP. This work can provide guidance for the rational design and operation of GSHP. • Relation of heat exchange rate per depth of borehole(HERPDB) with design parameters. • Rational values of design parameters with considering HERPDB. • Dynamic simulation of underground temperature field (UTF) of a single U-tube GHE. • Dynamic simulation of UTF of pipe-group of U-tube GHE round one year. • Efficient operation of GSHP with borehole center-to-center distance of 3.8 m [ABSTRACT FROM AUTHOR]

Abstract We investigate different operating conditions effects, including cathode relative humidity, anode stoichiometry and inlet pressure, on PEMFC with anode recirculation by conducting dynamic simulations. The performance improvement caused by the self-humidification effect is about 6.5% with dry cathode inlet, and it is very slight with fully humidified cathode inlet. Nitrogen fraction in the anode is low in the first 20 min under a low cathode relative humidity. A 0.3–0.6 cathode relative humidity might be suitable for the simulated cases. Generally, the fuel cell benefits from increasing anode stoichiometry by enhancing the self-humidification effect, decreasing the performance decline rate and ameliorating hydrogen distribution along the channel. Increasing anode inlet pressure and cathode inlet pressure play the mitigated and exacerbated role on voltage decline, respectively. However, increasing cathode inlet pressure can significantly improve output performance especially under a low cathode relative humidity. We suggest an appropriate low cathode relative humidity, increasing anode stoichiometry, and increasing anode and cathode inlet pressure by similar amount for PEMFC with anode recirculation. Highlights • Modeling of operating condition effect on anode recirculation PEMFC is presented. • An appropriate low cathode humidity is proposed for low nitrogen crossover rate. • High anode stoichiometry can improve fuel distribution and mitigate voltage decline. • Increasing anode and cathode inlet pressure by similar amount is recommended. [ABSTRACT FROM AUTHOR]

Abstract Integration of a latent heat energy storage into a solar heating system has become a well-known engineering practice that can bridge the mismatch between the heat demand of the served building and heat supply from the solar heating system. However, control schemes, energy performance analysis, characterization and optimization of such a system under the Tibet climatic/altitude conditions still remain a challenge. This research aims to investigate a PCM-integrated solar heating system applicable to Tibet which is unique in terms of the altitude, solar radiation, atmospheric pressure and water boiling temperature etc. The whole process involves (1) identification of the unique features of Tibet climate and altitude and relevant requirements to the solar system; (2) design of a PCM-integrated solar heating system based on a selected building in Lhasa and planning the potential control strategies appropriate to such a system; (3) analysis of the system's energy performance under different operational schemes; and (4) recommendation of the most appropriate system operational scheme and design strategy. A dynamic simulation model was established and applied to study the energy performance of such a system, in which the solar energy usage rate is defined as the performance evaluation index. It is found that the operational scheme 'A' has the best energy saving effect, followed by operational schemes B and C. The system presents a more favorite energy performance between 9:00 h–18:00 h, compared to other time slots in a typical winter day. Change in operational schemes creates a significant impact on the energy saving effect of the system. The results help wide and fast deployment of the PCM-integrated solar heating system and enable the determination of the best performing operational scheme and associated performance data appropriate to Tibet or similar regions in the world, thus making a significant contribution to the saving of fossil fuel energy consumption and reduction of the carbon emission on the regional and global scales. Highlights • Energy performance and operational schemes of a Tibet-focus SHS-PCM was investigated. • Operational scheme A is the best and C is the worst in terms of energy saving rate. • Daytime heating achieved a higher energy efficiency compared to the full day heating. • Energy saving rates for three schemes are 64%, 50% and 46% for the full day heating. • Energy saving rates for three schemes are 92%, 79% and 24% for daytime heating. [ABSTRACT FROM AUTHOR]

Abstract The present investigation is a continuation of a previous study conducted by the authors that presented a dynamic-simulation model of an Ericsson engine equipped with a gas-to-gas heat exchanger. This model is here used to investigate the effect of compressor and expander valve timing variation. The investigation begins with an un-optimized case and examines various improvements in terms of valve timings. This results to an optimized case that improves power and thermal efficiency. The optimized case serves as reference to study the effects of variations in the valve timings of the compressor and expander. The inlet valve closing timing of the expander (IVC e), which determines the intake duration of the expander, necessitates the readjustment of some of the other valve timings, since it significantly affects the pressure levels in all devices. The IVC e variation led to the potential of using a single heater with multiple compressor-expander pairs that are sequentially and periodically coupled to the heater. This increases the specific power output compared to using several compressor-heater-expander triplets, since it reduces the total volume of the engine. The number of compressor-expander pairs that can be coupled to a single heater is largely determined by the IVC e timing. Highlights • Valve timing effects are analyzed in terms of flow conditions and performance. • Expander inlet valve closing greatly affects pressure levels and performance. • Multiple compressor-expander pairs coupled to a single heater increase specific power. • The number of compressor-expander pairs depends on expander inlet valve closing. [ABSTRACT FROM AUTHOR]

Abstract This work aims at presenting the current works concerning the polygeneration systems simulation, by specially focusing on the potential integration of different technologies into a single system. Polygeneration allows one to produce energy vectors (power, heating and cooling) as wells as other useful products (hydrogen, syngas, biodiesel, fertilizers, drinking water etc.) by converting one or multiple energy sources. Polygeneration system can be fuelled by renewable sources (geothermal, solar, biomass, wind, hydro), as well as fossil fuels (natural gas, coal, hydrogen, etc.). In this paper innovative energy technologies, such as fuel cells and conventional ones are taken into account, by also focusing on the control strategies implemented for the proper management of polygeneration systems in general. Works regarding energy, economic and exergy analyses and system optimizations are also illustrated. Highlights • Current literature studies on polygeneration systems simulation. • The review includes conversion technologies fuelled by fossil and/or renewable energy. • A classification of methodology, outputs, control and optimization. • Contribution of polygeneration to the development of distribute generation systems. [ABSTRACT FROM AUTHOR]

Abstract This study is aimed at development of a theoretical model by combining modified non-ideal adiabatic model and dynamic analyses in order to predict the dynamic behavior of a 1-kW class beta-type Stirling engine with rhombic drive mechanism during starting. All friction losses caused by piston rings, bearings, and seals are taken into consideration. The total torque can be expressed in a closed-form relation by including the effects of the inertia force, the gravity force, the pressure force and the friction forces. The transient variations of instantaneous angular velocity under different operating conditions are simulated. The variations of the engine speed, the shaft power, and the mechanical efficiency of the engine under time-varying output torque are also described. The results also indicate that engine has a minimum and a maximum operating speed, and a minimum initial speed for starting. A prototype engine is built and tested for validation of the present model. Experiments on the transient behavior of the prototype engine during starting and under time-varying operating conditions are conducted. The numerical predictions by the present model closely agree with the experiments. And the maximum power generated by the engine is 1358 W at 1313 rpm in the test. Highlights • Thermodynamic and dynamic are combined for analyzing the Stirling engine. • A closed-form relation for the difference kind of torque sources is proposed. • A 1-kW prototype engine is built and tested for verifying the theoretical model. [ABSTRACT FROM AUTHOR]

This study synthesized a novel Cu@4 A zeolite nano-catalyst, which exhibited excellent catalytic pyrolysis performance on oil shale. The catalytic pyrolysis behaviors of oil shale were investigated, results show the initial pyrolysis temperature of organics decreased from 410 °C to 360 °C after catalytic treatment, and the activation energy declined from 190.73 to 147.95 kJ/mol. The oil and gas yields increased by 7.61% and 19.69% after catalysis treatment by Cu@4 A, respectively; the yields of H 2 and ethylene catalyzed by Cu@4 A zeolite climbed to 15% and 21%. Cu@4 A shows a prominent selectivity on light alkanes and alkenes compared with metal catalysts. The configurations of hydrocarbons in nano-pore were investigated by Molecular Dynamics simulations, the first density peak of C 3 H 6 declined by 68.3% after catalyzed by Cu@4 A at a temperature of 573 K. The interaction energy of hydrocarbon would decrease when the system temperature increases. Finally, the catalytic mechanism was elucidated, kerogen would decompose into macromolecule aromatic hydrocarbons via the β-cleavage of carbenium ions over the acidic sites of the prepared catalyst, then followed by the dehydrocyclization, oligomerization, and aromatization. [Display omitted] • Cu@4 A zeolite nano-catalyst for oil shale in-situ conversion was synthesized. • The prepared catalyst exhibits favorable catalytic performance toward oil shale. • The adsorption configurations and catalysis mechanisms were explored by MD simulation and experiments. [ABSTRACT FROM AUTHOR]

Energy savings and emission reductions in the construction industry are an important mean of achieving China's goals of carbon peaking and carbon neutrality. Management of debris and waste produced during construction is particularly important to achieve the construction industry's carbon emission reduction goals. This study constructs an (SD) model of the management of C&DW carbon emissions under different sorting modes to explore the relationship among factors affecting carbon emissions produced during C&DW management and to investigate the carbon emission reduction effects of different policies. The SD model simulates the effects of different carbon emission reduction policies and proposes optimization suggestions for the simulation results, which show that: (1) When the subsidy is set at 25CNY/t, there is a significant increase in the propensity of contractors to choose the resource sorting mode and a significant decrease in total carbon emissions of C&DW treatment. (2) When using a carbon tax as a policy tool to regulate the choice of C&DW sorting mode, there is a significant increase in the tendency of contractors to choose the resource-based sorting mode. The findings of the study can provide a basis for the government to introduce relevant C&DW management and emission reduction policies. [Display omitted] • A SD model of the management of C&DW carbon emissions is constructed. • Stronger penalties for illegal dumping prompt contractors to recycle more C&DW. • It is better for government to use tax and fee reduction policies to manage carbon emissions reductions. • The research results further improve the theory of C&DW resource utilization. [ABSTRACT FROM AUTHOR]