Simulation Models Of Systems Research Articles

Power increase potential of coal-fired power plant assisted by the heat release of the thermal energy storage system: Restrictions and thermodynamic performance

The integration of a thermal energy storage (TES) system is an effective way to improve the load cycling rate of coal-fired power plants (CFPPs). To evaluate the power increase potential and thermodynamic performance of CFPP supplied by heat release of the molten salt TES system, eight discharging modes for CFPP integrated with the TES system including steam injection, heater bypass, and additional turbine schemes were comparatively evaluated. The system simulation models of the integrated systems were developed and the thermodynamic performance of the proposed system were evaluated. Results show that the mode SI-HPT (high-pressure turbine steam injection) has the largest output power increase of 25.00 % under the benchmark condition of 75%THA, but the mode HB-LPH (low-pressure heater bypass) shows a very low output power increase of 2.08 %. Moreover, the power generation efficiency is changed by the external heat source through a change in the average heat absorption temperature of the Rankine cycle and the internal irreversibility of the steam/water cycle. Under the typical benchmark discharging condition of 75%THA, the power generation efficiency of the turbine in mode SI-LPT (low-pressure turbine steam injection) can be reduced from 47.41 % to 44.15 %, but it can be increased from 47.41 % to 48.86 % in mode SI-HPT. When the temperature ranges of the TES system are above 600 °C and below 450 °C, the modes SI-HPT and SI-LPT obtain the optimal comprehensive performance, respectively. This study can provide the scientific guidance for retrofit for CFPP to achieve efficient and flexible design.

Laminar burning characteristics of ammonia and hydrogen blends at elevated initial pressures up to 2.5 MPa

Ammonia is a highly promising alternative fuel, and blending it with hydrogen can mitigate its poor combustion performance. However, the combustion mechanism of ammonia-hydrogen mixtures requires further validation through measurements of laminar burning velocity, particularly under high-pressure conditions relevant to practical combustors. Experimental data at high initial pressures (>1.0 MPa) are notably scarce. In this study, experiments were conducted using an outwardly propagating spherical flame in a high-pressure, high-temperature, constant-volume combustion chamber to determine the laminar burning velocities of ammonia-hydrogen blends at elevated initial pressures. The effects of different equivalence ratios (0.6 ∼ 1.4), volumetric hydrogen ratios (0.1 ∼ 0.6), and initial pressures (0.1 ∼ 2.5 MPa) were evaluated. Chemical kinetics of ammonia and hydrogen combustion was investigated at high pressures. The experimental results were compared with the simulation results under a wide range of conditions using several existing mechanisms to evaluate their applicability. The results show that the laminar burning velocity increases first and then decreases as the equivalence ratio (ϕ) increases and reaches a maximum value around ϕ of 1.1. The laminar burning velocity increases non-linearly with the volumetric hydrogen ratio, with more pronounced acceleration at higher hydrogen ratios. In contrast, the laminar burning velocity decreases non-linearly with the increasing initial pressure, and this reduction becomes progressively slower as the initial pressure rises. The predictive performance of the mechanisms by Okafor et al. and Gotama et al. is relatively satisfactory under certain conditions, but further optimization based on experimental data is necessary. Additionally, reaction pathway analysis of ammonia-hydrogen combustion indicates that introducing hydrogen increases the concentration of active radicals such as OH, O, and H, thereby enhancing ammonia combustion. Sensitivity analysis of the laminar burning velocity identified the critical elementary reactions across varying pressures, providing strong support for optimizing ammonia-hydrogen chemical kinetics models and developing simulation models for practical combustion systems.

Enhancing safety feedback to the design of small, unmanned aircraft by joint assessment of impact area and human fatality.

Advantages of commercial UAS-based services come with the disadvantage of posing third party risk (TPR) to overflown population on the ground. Especially challenging is that the imposed level of ground TPR tends to increase linearly with the density of potential customers of UAS services. This challenge asks for the development of complementary directions in reducing ground TPR. The first direction is to reduce the rate of a UAS crash to the ground. The second direction is to reduce overflying in more densely populated areas by developing risk-aware UAS path planning strategies. The third direction is to develop UAS designs that reduce the product in case of a crashing UAS, where is the size of the crash impact area on the ground, and is the probability of fatality for a person in the crash impact area. Because small UAS accident and incident data are scarce, each of these three developments is in need of predictive models regarding their contribution to ground TPR. Such models have been well developed for UAS crash event rate and risk-aware UAS path planning. The objective of this article is to develop an improved model and assessment method for the product In literature, the model development and assessment of the latter two terms is accomplished along separate routes. The objective of this article is to develop an integrated approach. The first step is the development of an integrated model for the product . The second step is to show that this integrated model can be assessed by conducting dynamical simulations of Finite Element (FE) or Multi-Body System (MBS) models of collision between a UAS and a human body. Application of this novel method is illustrated and compared to existing methods for a DJI Phantom III UAS crashing to the ground.

A holistic simulation model of solid-set sprinkler irrigation systems for precision irrigation

A holistic simulation model of solid-set sprinkler irrigation systems for precision irrigation

Analysis of energy performance and load matching characteristics of various building integrated photovoltaic (BIPV) systems in office building

Building Integrated Photovoltaic (BIPV) is a key technology for achieving zero-energy buildings by generating electricity and reducing energy consumption. Although many studies have analyzed the impact of BIPV on building energy efficiency, there is a lack of comprehensive comparative analysis of various BIPV systems. This study compared the impact of various BIPV systems on office building energy performance and provided optimal solutions for different climate zones. Simulation models for PV rooftop, PV window, and PV shading systems were developed and validated in EnergyPlus. The energy performance of BIPV systems in different Chinese climates was evaluated using these models. The results show that the PV window and PV shading have the most power generation capability in Beijing, and the PV rooftop has the most power generation capability in Kunming. Energy savings in Kunming are the highest with PV rooftop, PV windows, and PV shading at 111.78 %, 39.36 %, and 44.43 %, respectively. Finally, the study calculated the self-sufficiency rate (SSR) and self-consumption rate (SCR), and their ratio, along with the load matching ratio, were used to assess loading matching. Optimal BIPV schemes were identified for each climate zone, revealing that the PV rooftop combined with the PV shading system achieved the best load matching in Kunming, Guangzhou, Changsha, Beijing, and Harbin, with ratios of 82.00 %, 69.38 %, 70.88 %, 74.78 % and 67.27 %, respectively. These results provide a valuable reference for implementing the BIPV system to achieve zero energy consumption in office buildings under different climatic conditions in China.

Trajectories of socio-ecological systems: Does social capital matter? A case study in the tropical Andes

Between natural and social systems there are two-way interactions, which determine the path of change in the Socio-Ecological System. For example, the type of land use decisions that society makes could lead to the deterioration of the biophysical system and its ecological functioning, causing effects on social well-being. Conceptual and simulation models of socio-ecological systems allow an understanding of such interactions and the development of trajectories. In this manuscript we explore the link between three lines of research that overlap but have been studied separately (i) Governance, (ii) Socio-ecological systems, and (iii) social capital. This paper analyzes the dynamics of social capital and its influence on governance and Land Use and Land Cover Changes in a basin of the Colombian Andes. To this end, we develop a Systems Dynamics model (SD). This research contributes to the (i) understanding of how the institutions, their policies, the actors, and the interactions generated between them in a territory influence the management of natural resources, which is indispensable to supporting the decision-making process; and (ii) operationalization of the social capital elements on the SES model through an integrated analysis with consideration of feedback mechanisms between natural and social system. With this model, a scenario evaluation is developed to analyze the effect of different approaches of the social capital organization on land cover in the basin case study.

Models of data processing and logical access segregation considering the heterogeneity of entities in information systems

The subject of the research is the process of logical access segregation to data in information systems. The aim of the article is to improve the accuracy and reliability of modeling processes for data processing and logical access segregation considering the heterogeneity of entities in information systems. The tasks to be solved include: conducting a comparative analysis of modern data access distribution models, integrating simpler role-based models, synthesizing hierarchical role-based models, developing enforced typing models based on trust relationships, and presenting the main provisions of the security policy integration process. The methods used are: systems analysis, component design, logical and simulation modeling in the form of role-based access segregation models. The results obtained include: development of data processing models and logical access segregation in information systems that take into account the heterogeneity of entities and the multi-level structure of information systems. The models differ from known ones by considering the heterogeneity of entities and the multi-level structure of information systems. This has increased scalability by up to 35% due to a modular approach to defining security policies. Additionally, the developed model demonstrates 25% higher implementation practicality as it easily integrates with existing access control systems and adapts to various platforms and environments. The proposed models are effective for large information systems and distributed environments due to their modularity and ability to adapt to different operational conditions. This ensures reliable access control in systems with numerous subjects and objects. The implementation of multi-level RBAC models has improved the accuracy and reliability of results.

Moving control surfaces in a geometry-resolved CFD model of an airborne wind energy system

Properly understanding the unsteady interaction of the wind with the aircraft is critical to develop reliable airborne wind energy (AWE) systems. High-fidelity simulation tools are needed to accurately predict these interactions, providing insights into the design and operation of efficient and safe AWE systems. In this work, we present a computational fluid dynamics (CFD) framework of an airborne wind system which resolves all lifting surfaces and includes moving control surfaces. This work considers a reference multi-megawatt ground-gen pumping system. To simulate complex fluid flow problems, with large rigid-body motion and deflecting control surfaces using CFD, we opt for the Chimera/overset technique. The goal of this contribution is to demonstrate the effect of the control surfaces in the CFD framework. This work is a major milestone in the ongoing development of high-fidelity aero-servo-elastic simulation models for airborne wind energy systems.

The long term price elastic demand of hydrogen – A multi-model analysis for Germany

Hydrogen and its derivatives are important components to achieve climate policy goals, especially in terms of greenhouse gas neutrality. There is an ongoing controversial debate about the applications in which hydrogen and its derivatives should be used and to what extent. Typically, the estimation of hydrogen demand relies on scenario-based analyses with varying underlying assumptions and targets. This study establishes a new framework consisting of existing energy system simulation and optimisation models in order to assess the long-term price-elastic demand of hydrogen. The aim of this work is to shift towards an analysis of the hydrogen demand that is primarily driven by its price. This is done for the case of Germany because of the expected high hydrogen demand for the years 2025–2045. 15 wholesale price pathways were established, with final prices in 2045 between 56 €/MWh and 182 €/MWh. The results suggest that – if climate targets are to be achieved - even with high hydrogen prices (252 €/MWh in 2030 and 182 €/MWh in 2045) a significant hydrogen demand in the industry sector and the energy conversion sector is expected to emerge (318 TWh). Furthermore, the energy conversion sector has a large share of price sensitive hydrogen demand and therefore its demand strongly increases with lower prices. The road transportation sector will only play a small role in terms of hydrogen demand, if prices are low. In the decentralised heating for buildings no relevant demand will be seen over the considered price ranges, whereas the centralised supply of heat via heat grids increases as prices fall.

Yam Production-Related Agro-climatological Risks and Yam Yield Modeling in Côte d’Ivoire: A Review

In this paper, we present a review of the agro-climatological-related risk of yam production and models developed for yam yield prediction in Côte d’Ivoire. Four official national platforms (Ministry of Agriculture and Rural Development (MINADER), National Center for Agricultural Research (CNRA), National Agency for Rural Development Support (ANADER), Airport, Aeronautical and Meteorological Exploitation and Development Company (SODEXAM)) and six scientific search engines were investigated in this study including Theses.fr, African Journal Online, Science Direct, Google Scholar, WorldCat and Semantic Scholar. Using the boolean parameters “AND”, “OR” and “()” to facilitate and direct our search, we were able to define four key phrases comprising the topic words that were used in the search. Exclusion and inclusion criteria for the selection of documents were also defined in advance, as well as the criteria for reviewing and extracting information from selected documents. The results showed that no work in the field of agro-climatological risks related to yam production and yam yield modeling in Côte d’Ivoire was available on these online research platforms at the time of this literature review. However, other studies similar to the scope of this review on yam exist in several West African countries, particularly Ghana, Benin and Nigeria, and also in the Caribbean. These studies use simulation models such as the Approach for Land Use Sustainability (SALUS) model, the Environmental Policy Integrated Climate (EPIC) model and the Cropping Systems Simulation (CROPSYST) model for growth, yield modeling and the influence of climatic parameters on yam. In addition to these models, artificial intelligence through machine learning models was also seen in this review as an excellent tool for yield prediction for several crops including yams.

A Comprehensive Analysis of Sensitivity in Simulation Models for Enhanced System Understanding and Optimisation

This article delves into sensitivity analysis within simulation models of real systems, focusing on the impact of variability in independent input factors (x) on dependent system outputs (y). It discusses linear and nonlinear regression to analyse and represent relationships between input factors and system responses. This study encompasses three sensitivity analysis areas: factor screening, local sensitivity analysis, and global sensitivity analysis, highlighting their roles in understanding the significance of factors in simulation models. The practical application of sensitivity analysis becomes clear through a case study in a manufacturing system. The case study utilises the Simio simulation system to investigate the impact of input factors on production lead time and work in process (WIP). The analysis uses regression to quantify the impact of seven factors, showcasing the most significant ones with tornado charts and emphasising the application of sensitivity analysis to optimise system responses.

FRF-based model updating of liquid-filled pipeline system considering tolerance intervals of test errors in the antiresonant frequencies

The frequency response function (FRF)-based model updating technique is an effective method to calibrate system parameters of the dynamic simulation model of pipeline systems. However, the existing FRF-based model updating methods is difficult to solve the problem of the test errors in the antiresonant frequencies, which significantly affects the accuracy of the updated results. Hence, this paper proposes a new FRF-based model updating method of the liquid-filled pipeline considering the tolerance intervals of test errors in the antiresonant frequencies. In this method, the effect of test errors on FRFs is quantified by employing the interval method, and then the tolerance intervals of test errors in the antiresonant frequencies can be identified from the interval FRFs. The obtained tolerance intervals are integrated into the objective function of the FRF-based model updating through the penalty function method, and the optimal system parameters can be obtained by using a global optimization algorithm. Compared with the existing FRF-based model updating methods, the proposed method can not only effectively reduce the effect of test errors in the measured FRFs on the updated results but also alleviate the ill-condition of model updating calculations, so that the accuracy and convergence of model updating calculations are improved simultaneously. Numerical and experimental validations of the proposed method are carried out by using an L-shaped water-filled pipeline system. The performances of the proposed method are compared with the typical FRF-based model updating method. The results demonstrate that the proposed method can obtain the updated results with higher accuracy and reliability than the typical method.

Research on Fast Frequency Response Control Strategy of Hydrogen Production Systems

With the large-scale integration of intermittent renewable energy generation presented by wind and photovoltaic power, the security and stability of power system operations have been challenged. Therefore, this article proposes a control strategy of a hydrogen production system based on renewable energy power generation to enable the fast frequency response of a grid. Firstly, based on the idea of virtual synchronous control, a fast frequency response control transformation strategy for the grid-connected interface of hydrogen production systems for renewable energy power generation is proposed to provide active power support when the grid frequency is disturbed. Secondly, based on the influence of VSG’s inertia and damping coefficient on the dynamic characteristics of the system, a VSG adaptive control model based on particle swarm optimization is designed. Finally, based on the Matlab/Simulink platform, a grid-connected simulation model of hydrogen production systems for renewable energy power generation is established. The results show that the interface-transformed electrolytic hydrogen production device can actively respond to the frequency disturbances of the power system and participate in primary frequency control, providing active support for the frequency stability of the power system under high-percentage renewable energy generation integration. Moreover, the system with parameter optimization has better fast frequency response control characteristics.

Chaotic Communication Systems with Signal Modulation Based on Controlled Symmetry of Semi-Implicit Finite-Difference Models

The article is devoted to investigation coherent communication system model with a new method of signal modulation based on variable symmetry of finite-difference schemes with subsequent experimental analysis of the effectiveness of different modulation techniques. The aim of the study is to investigate a computer model of chaotic communication system with signal modulation based on variable symmetry of semi-implicit finite-difference schemes. Novelty: elements of scientific novelty have finite-difference models of receivers/transmitters, allowing to realize a new method of modulation of chaotic signals. Result: obtaining a simulation model of coherent chaotic communication systems with tools for covertness and noise immunity analyses. Practical relevance: The simulation model of chaotic communication system is a necessary tool for analyzing the performance of the system before its physical implementation.

Developing a Dynamic Smart Grid Model

The aim of the research was to create a computer simulation model of the future smart grid systems, suitable to examine their operation and optimal control. The model is able to simulate events in arbitrary system cases and the answers of the system. The flexibility of the simulation is foreseen by the modular structure of the software. The generation and consumption data are based on real measured values. Different size and number of smart grids were examined by using this model. The actual result of the research was that the system’s behavior, as simulated by the model, was similar to the everyday operation of a real grid. Furthermore, the model is a tool to investigate the trends of future network development (regarding the change of smart grid criteria). There is a need to work out new application behaviors, procedures, and operational routines regarding the research areas represented by certain modules. The computer simulation model is already ready to use in the education, and as it is extensible, it is suitable to follow the changes of smart systems in the future.

Performance monitoring and redesign of power system stabilizers based on system identification techniques

To maintain stable power system operation, damping control systems are used in conventional power plants, known as Power System Stabilizers (PSS). However, to derive suitable controller parameters, the current methods require dynamic models that are difficult to maintain and update, and in some cases, might not be available. This makes it challenging for grid operators to maintain system stability when the system is under stringent operating conditions or undergoes the loss of major transmission corridors, which would require a new stabilizer design to provide adequate damping.Leveraging the availability of real-time measurements and “probing” technologies, this paper provides a complementary approach that does not require power system simulation models, but is based on system identification techniques that allow to derive simple and accurate models based on data collected on the system. The proposed method allows to monitor the performance of damping controllers and even to perform redesign based on the models derived with system identification. The resulting redesign could be used to update PSS parameters and improve damping without the need of removing existing damping control systems from service.

Modeling and Analysis of Bio-Inspired, Reconfigurable, Piezo-Driven Vibration Isolator for Spacecraft.

The positioning accuracy of spacecraft in orbit is easily affected by low-frequency micro-vibrations of the environment and internal disturbances caused by the payload. Inspired by the neck structure of birds, this study devised a piezo-driven active vibration isolation unit with high stiffness. First, a dynamic model and two-sensor feedback control method for the isolation unit were developed, and the isolation mechanism and anti-disturbance characteristics were analyzed. Further, the stability of the closed-loop was verified. Simulation models of serial and parallel systems based on the proposed vibration isolation unit were implemented to demonstrate its feasibility. The results indicate that the proposed isolation units can provide excellent low-frequency vibration isolation performance and inertial stability and that they can effectively resist the internal disturbance of the payload. Moreover, its performance can be further improved via serial or parallel reconfiguration that facilitates its adaptation to the varied isolation requirements of spacecraft.

A Predictive Out-of-Step Identification Method Based on Wide-Area Velocity-Acceleration Trajectory

Online identification of the transient instability is essential in power system analysis, as it facilitates the grid operator to decide and coordinate system failure correction control actions. The rapid technological development of phasor measurement units (PMUs) provides an opportunity for online transient out-of-step identification in real-time. This paper analyzes the characteristics of angular velocity-acceleration trajectories in detail, and then proposes a predictive transient out-of-step identification method among coherent groups of generators based on the velocity-acceleration trajectory sampled by PMUs. To prove that the method can distinguish the transient out-of-step event following disturbance reliably, a mathematical proof of the criterion extended to multi-machine system is made, and the influences of the exciter and emergency control are taken into consideration to a certain extent. Finally, the effectiveness and predictability of the proposed method are demonstrated on a 39-bus New England test system and two large-scale power system simulation models of China by numerical studies.

Estimating the Long-Term Thermal Comfort Elasticities of Diverse Households

District energy systems simulation models are developed to investigate whether the demand-supply energy balance can be maintained despite the energy transition. To adapt these models to the future energy system, models of residential energy flexibility are required. We hypothesize that a quantification of households’ comfort elasticities is needed to model residential energy flexibility more accurately. Therefore, this study aims to identify diverse households’ long-term thermal comfort elasticities. Eight longitudinal mixed methods case studies with an explanatory sequential design were conducted in seven Belgian dwellings. Data were collected before and during the recent energy crisis. They include sensor measurements, a questionnaire, and follow-up interviews. All households show elasticities. Some differ the average set point temperature, the average heated volume to a limited extent, or the temperature of no more heating. Differences between households could be explained by differing household and dwelling characteristics.

Study of Error Flow for Hydraulic System Simulation Models for Construction Machinery Based on the State-Space Approach

This study presents an error flow research method for simulation models of hydraulic systems in construction machinery based on the state-space approach, aiming to ensure the reliable application of digital twin models. Initially, a comprehensive analysis of errors in the simulation modeling of hydraulic systems in construction machinery was conducted, highlighting simulation model parameters as the primary error sources. Subsequently, a set of metrics for assessing the accuracy of simulation models was developed. Following this, an error flow analysis method for simulation models of hydraulic systems in construction machinery was explored based on the state space approach, delving into the sources, transmission, and accumulation of errors in the simulation modeling of valve-controlled cylinder systems. The research results unequivocally indicate that the spring stiffness, viscous damping coefficient, and hydraulic cylinder external leakage coefficient are critical parameters affecting the accuracy of valve-controlled cylinder system simulation models. Furthermore, it was observed that the simulation model of the control valve has a significantly greater impact on the errors in the valve-controlled cylinder system simulation model than the hydraulic cylinder model. In conclusion, the reliability of the error flow model was confirmed through simulation experiments, revealing a maximum relative error of only 3.73% between the error flow model and the results of the simulation experiments.