Supplied with electricity and natural gas, local energy systems (LESs) with gas-fired generations increase the operational flexibility of urban energy supply. However, the increasing usage of these LESs may lead to adverse impacts on the urban energy system supply via power and/or gas distribution networks. Dynamic interactions between the LESs, electricity, and gas networks subject to different disturbances need to be investigated due to the complexity of the problem. To address this issue, this paper first presents the topology and operating mode of the LESs as well as the relationship with power and gas networks. Second, an extended microturbine model is developed to reflect the nonlinear dynamic propagation of disturbances between the two networks. A general model of the interconnected LESs is developed to analyze the mutual impacts between gas and electricity networks under different modes. Finally, an iterative method is proposed to simulate the mechanism of disturbance propagati... [more]

This paper presents a characteristic analysis and experimental verification for predicting the electromagnetic losses in high-speed permanent magnet synchronous motors. To predict the operating characteristics (such as speed and input current), dynamic modeling is conducted that combines models for the space vector pulse width modulation (SVPWM) inverter and high-speed permanent magnet synchronous motor (HPMSM). By applying the predicted harmonic currents to the electromagnetic analysis, DC and AC copper losses of the stator winding, and eddy current loss of the rotor sleeve and rotor permanent magnet, are comprehensively analyzed using the finite element (FE) method. In particular, by analyzing the magnetic field behavior of magnetic flux density according to harmonics, a core loss analysis technique was presented. The validity of the hybrid analysis, which combines the stator copper loss and rotor eddy current loss derived from the FE analysis and the proposed core loss analysis, was... [more]

With a proliferation of diverse types of renewable distributed generation (DG) into the distribution network, an equivalent model of an active distribution network (ADN) is extremely important, since the detailed modeling of the whole ADN is much more complex and time consuming. However, different studies developed different model structures of ADNs, which are difficult to be applied in a power system simulation. At the same time, the DG’s low voltage ride through the (LVRT) control was not considered in the existing ADN model, which may lead to a large modelling error. In this paper, a general equivalent model is developed for the ADN with a significant amount of DGs, based on a two-step modelling method. Step one, motivated by the dynamic similarities between the doubly-fed induction generator (DFIG)-based wind turbines, direct drive permanent magnet synchronous generator (DDPMSG)-based wind turbines, and photovoltaic (PV) generation, a general model structure of a renewable DG is in... [more]

In recent years, numerous projects for floating PV systems have been developed. These plants of various sizes have mainly been installed on enclosed lakes or basins characterised by the absence of external forcing related to waves and currents. However, offshore installation would allow the development of such plants in areas where land is not available, such as islands. This paper analyses the state of the art of floating PV, describes the design of a floating PV platform and the development of a numerical model to evaluate the system performance in an offshore environment. The case study of the island of Lampedusa is then analyzed: starting from a single floating foundation with its mooring system, a floating PV system is designed to meet the island’s electricity needs. In order to provide the competitiveness of the system, a techno-economic analysis is carried out, evaluating the main cost items of Capex, Opex and LCOE. Although the LCOE obtained is significantly higher than a tradi... [more]

The development of dynamic models for control purposes is characterised by the challenge of finding a compromise between the minimum necessary information about the system dynamics contained in the model and a model with a low level of complexity such that the model-based control system design becomes comfortable. To achieve this balance, a modified dynamic model for the drivetrain of a wind turbine is proposed in this contribution. The main idea is to introduce the tip-speed ratio as a state variable so that an interval observer can be designed in such a way that its estimates can be used in the torque control during the partial load operation as well as for the estimation of the effective wind speed. During the runtime, the observer’s matrix gain is recalculated to adapt the behaviour to the current operational state, which changes all the time with the wind speed. Besides the theoretical formulation, a numerical example of a 20 MW reference wind turbine illustrates the utility of th... [more]

In recent years, the integration of battery energy storage systems (BESSs) with multilevel modular converters (MMCs) has received interest in power system applications. In this work, this configuration is called a MMC-based BESS. The batteries are connected directly to the MMCs on submodules (SMs), called the single-stage approach. Several control strategies have been proposed to guarantee the proper operation of a MMC-based BESS. This system is complex due to the control strategy. Another challenge is in obtaining the controller gains for a MMC-based BESS converter. In this sense, there is a gap in the methodology used to calculate the controller gains. Thus, this work aimed to tune the analytical expressions of a MMC-based BESS by considering the single-stage approach. The methodology is validated through detailed simulation models of 10.9 MVA/5.76 MWh connected to a 13.8 kV power system. Finally, to validate the dynamics of the controllers, the simulation results in the PLECS softwa... [more]

A misusage of machine learning (ML) strategies is usually observed in the process systems engineering literature. This issue is even more evident when dynamic identification is performed. The root of this problem is the gradient explode and vanishing issue related to the recurrent neural networks training. However, after the advent of deep learning, these issues were mitigated. Furthermore, the problem of data structuration is often overlooked during the machine learning model identification in this field. In this scenario, this work proposes a guideline for identifying ML models for the different applications in process systems engineering, which are usually for simulation or prediction purposes. While using the proposed guideline, the work also identifies a virtual analyzer for a pressure swing adsorption unit. In these types of adsorption separations, it is usual that the measurement of the main properties is not done online. Therefore, the virtual analyzer is another contribution o... [more]

In this paper, a novel second-order active disturbance rejection control (2-ADRC) algorithm is proposed to optimize the control of the air supply subsystem for Proton Exchange Membrane Fuel Cell (PEMFC). To improve the optimal control effect of the air supply subsystem for PEMFC, the modeling theory of the air supply subsystem considering dynamic characteristics of the PEMFC system is first studied, and the dynamic Simulink model of the PEMFC system is established and verified. Then, the optimal oxygen excess ratio (OER) parameters under different load currents are obtained, and the optimal OER parameters are also used as the OER control reference for the designed algorithms. In addition, a 2-ADRC algorithm is designed and proposed to make the actual OER parameters close to the optimal OER in real time. Furthermore, compared with PID and MPC algorithms, the 2-ADRC algorithm can comprehensively consider the two parameters of mass flow and pressure ratio to make the compressor work in th... [more]

In industrial smelters, sulfuric acid is manufactured using the elemental sulfur in a series of three-unit operations: elemental sulfur oxidation, sulfur dioxide catalytic conversion, and sulfur trioxide absorption. The sulfur oxidation, which is the basic step in this process, is generally performed under a sulfur combustion furnace that ensures the production of the process gas stream, which will be the main supply stream to the other unit operations. In this paper, a dynamic model is developed based on the fundamental mass and energy balance, including the sulfur oxidation and the dynamic flow behavior aspects within the furnace. The obtained model is simulated in the Matlab/Simulink environment and data from an industrial plant were used to validate the model. The simulation results and the plant measurement comparison showed an accuracy of 96%, with a mean absolute error of 16.12 °C and a root mean square error of 23.27 °C. Afterwards, the effect of different operating conditions... [more]

This is the source code for the STORE (STochasic Omentum REsponse) model. The model is used to simulate how naive T-cells in the omentum will prime and multiply during the expansion period (8 days) after a T-cell vaccination in a mouse.

This is the matlab source code used in the following paper:

Christian DA, Adams TA II, Smith TA, Shallberg LA, Theisen DJ, Phan AT, Abraha M, Perry J, Ruthel G, Clark JT, Murphy KM, Kedl, RM, Hunter CA. cDC1 coordinate innate and adaptive responses in the omentum required for T cell priming and memory. Science Immunology 7, eabq7432 (2022).

This is fixed legacy code used for the paper for scientific auditing and reproduction purposes. See paper for documentation.

In our previous work, a mathematical, agent-based dynamic model was developed which simulates the response of the mammalian omentum to a T cell vaccine injection during the expansion phase. The model tracks how each individual naïve T cell interacts with antigen presenting cells, and subsequently primes and divides over an 8-day period following vaccine injection. The model works from first principles; individual phenomena based on experimental observation and theory are incorporated into the model, and the collection of many such phenomena together create a nuanced model of the system as a whole. In this work, we show that the model works well in other relevant tissues, such as the spleen.

The present work aims to provide insights into the dynamic operation of a coupled reformer/combustion unit that can utilize a variety of saturated hydrocarbons (HCs) with 1−4 C atoms towards H2 production (along with CO2). Within this concept, a preselected HC-based feedstock enters a steam reforming reactor for the production of H2 via a series of catalytic reactions, whereas a sequential postprocessing unit (water gas shift reactor) is then utilized to increase H2 purity and minimize CO. The core unit of the overall system is the combustor that is coupled with the reformer reactor and continuously provides heat (a) for sustaining the prevailing endothermic reforming reactions and (b) for the process feed streams. The dynamic model as it is initially developed, consists of ordinary differential equations that capture the main physicochemical phenomena taking place at each subsystem (energy and mass balances) and is compared against available thermodynamic data (temperature and concent... [more]

Desalination has become one of the obvious solutions for the global water crisis due to affording high-quality water from seawater and brackish water resources. As a result, there are continuing efforts being made to improve desalination technologies, especially the one producing high-quantity freshwater, i.e., thermal desalination. This improvement must be accomplished via enhancement of process design through optimization which is implicitly dependent on providing a generic process model. Due to the scarcity of a comprehensive review paper for modeling multi-effect distillation (MED) process, this topic is becoming more important. Therefore, this paper intends to capture the evolution of modeling the forward feed MED (most common type) and shed a light on its branches of steady-state and dynamic modeling. The maturity of the models developed for MED will be thoroughly reviewed to clarify the general efforts made highlighting the advantages and disadvantages. Depending on the outputs... [more]

The main objective of any bioenvironmental controller is to create favourable bioenvironmental conditions around the living-system. In industrial incubation practice of chicken embryo, it is sometimes difficult to fill large incubators with uniform eggs, which leads to suboptimal results. The ideal incubation solution is a machine that is capable of coping with all sorts of variabilities in eggs. This can be realised in practice by creating different zones of different environmental conditions within the same machine. In the present study, a two-levels controller was designed and implemented to combine both convective and radiative heating to incubate eggs. On the higher level, three model-predictive-control (MPC) constrained controllers were developed to regulate the power applied to nine IR-radiators divided into three zones based on continuous feedback of the eggshell temperatures in each zone. On the lower level, a PID controller was used to maintain the air temperature within an e... [more]

Pyrimidine-nucleoside phosphorylases (Py-NPases) have a significant potential to contribute to the economic and ecological production of modified nucleosides. These can be produced via pentose-1-phosphates, an interesting but mostly labile and expensive precursor. Thus far, no dynamic model exists for the production process of pentose-1-phosphates, which involves the equilibrium state of the Py-NPase catalyzed reversible reaction. Previously developed enzymological models are based on the understanding of the structural principles of the enzyme and focus on the description of initial rates only. The model generation is further complicated, as Py-NPases accept two substrates which they convert to two products. To create a well-balanced model from accurate experimental data, we utilized an improved high-throughput spectroscopic assay to monitor reactions over the whole time course until equilibrium was reached. We examined the conversion of deoxythymidine and phosphate to deoxyribose-1-p... [more]

When modeling low capacity energy systems, such as a small size (5⁻150 kWel) organic Rankine cycle unit, the governing dynamics are mainly concentrated in the heat exchangers. As a consequence, the accuracy and simulation speed of the higher level system model mainly depend on the heat exchanger model formulation. In particular, the modeling of thermo-flow systems characterized by evaporation or condensation requires heat exchanger models capable of handling phase transitions. To this aim, the finite volume (FV) and the moving boundary (MB) approaches are the most widely used. The two models are developed and included in the open-source ThermoCycle Modelica library. In this contribution, a comparison between the two approaches is presented. An integrity and accuracy test is designed to evaluate the performance of the FV and MB models during transient conditions. In order to analyze how the two modeling approaches perform when integrated at a system level, two organic Rankine cycle (ORC... [more]

Liver resection is an important clinical intervention to treat liver disease. Following liver resection, patients exhibit a wide range of outcomes including normal recovery, suppressed recovery, or liver failure, depending on the regenerative capacity of the remnant liver. The objective of this work is to study the distinct patient outcomes post hepatectomy and determine the processes that are accountable for liver failure. Our model based approach shows that cell death is one of the important processes but not the sole controlling process responsible for liver failure. Additionally, our simulations showed wide variation in the timescale of liver failure that is consistent with the clinically observed timescales of post hepatectomy liver failure scenarios. Liver failure can take place either instantaneously or after a certain delay. We analyzed a virtual patient cohort and concluded that remnant liver fraction is a key regulator of the timescale of liver failure, with higher remnant li... [more]

In this study, a dynamic and two-dimensional model for a steam methane reforming process integrated with nuclear heat production is developed. The model is based on first principles and considers the conservation of mass, momentum and energy within the system. The model is multi-scale, considering both bulk gas effects as well as spatial differences within the catalyst particles. Very few model parameters need to be fit based on the design specifications reported in the literature. The resulting model fits the reported design conditions of two separate pilot-scale studies (ranging from 0.4 to 10 MW heat transfer duty). A sensitivity analysis indicated that disturbances in the helium feed conditions significantly affect the system, but the overall system performance only changes slightly even for the large changes in the value of the most uncertain parameters.

In this study, a dynamic and two-dimensional model for a steam methane reforming process integrated with nuclear heat production was developed. The model is based on first principals and considers the conservation of mass, momentum and energy within the system. Very few model parameter needed to be fit based on the experimental data reported in the literature. Using the fitted model and existing data, an industrial scale design for the integrated steam reforming and nuclear heat process is proposed. The system performance was analyzed by studying the dynamic behaviour of the key variables of the system. It has been shown that the methane conversion in the SMR tubes are generally lower than conventional reforming processes due to the low temperature of the gas flows in the shell side. Several options were investigated to increase the conversion of the methane in the SMR tubes, we found that combining steam reforming with dry reforming processes together can provide significant improveme... [more]

Synthetic ammonia produced from fossil fuels is essential for agriculture. However, the emissions-intensive nature of the Haber⁻Bosch process, as well as a depleting supply of these fossil fuels have motivated the production of ammonia using renewable sources of energy. Small-scale, distributed processes may better enable the use of renewables, but also result in a loss of economies of scale, so the high capital cost of the Haber⁻Bosch process may inhibit this paradigm shift. A process that operates at lower pressure and uses absorption rather than condensation to remove ammonia from unreacted nitrogen and hydrogen has been proposed as an alternative. In this work, a dynamic model of this absorbent-enhanced process is proposed and implemented in gPROMS ModelBuilder. This dynamic model is used to determine optimal designs of this process that minimize the 20-year net present cost at small scales of 100 kg/h to 10,000 kg/h when powered by wind energy. The capital cost of this process sca... [more]

This work focuses on designing the optimum raceway pond by considering the effects of sunlight availability, temperature fluctuations, and harvest time on algae growth, and introduces a dynamic programing model to do so. Culture properties such as biomass productivity, growth rate, and concentration, and physical properties, such as average velocity, pond temperature, and rate of evaporation, were estimated daily depending on the dynamic behavior of solar zenith angle, diurnal pattern of solar irradiance, and temperature fluctuations at the location. Case studies consider two algae species (Phaeodactylum. tricornutum and Isochrysis. galbana) and four locations (Tulsa, USA; Hyderabad, India; Cape Town, South Africa; and Rio de Janeiro, Brazil). They investigate the influences of the type of algae strain and geographical location on algae biomass production costs. From our case studies, the combination of I. galbana species grown in Hyderabad, India, with a raceway pond geometry of 30 cm... [more]

In this study, a dynamic and two-dimensional model for a steam methane reforming process integrated with nuclear heat production is developed. The model is based on first principles and considers the conservation of mass, momentum and energy within the system. The model is multi-scale, considering both bulk gas effects as well as spatial differences within the catalyst particles. Very few model parameters need to be fit based on the design specifications reported in the literature. The resulting model fits the reported design conditions of two separate pilot-scale studies (ranging from 0.4 to 10 MW heat transfer duty). A sensitivity analysis indicated that disturbances in the helium feed conditions significantly affect the system, but the overall system performance only changes slightly even for the large changes in the value of the most uncertain parameters.

In the previous study, a dynamic and two-dimensional model for a steam methane reforming process integrated with nuclear heat production was developed. It was shown that the integrated high temperature gas-cooled reactor (HTGR)/steam methane reforming (SMR) is an efficient process for applications such as hydrogen production. In this study, it is demonstrated that combining nuclear heat with the mix of steam and dry reforming process can be a promising option to achieve certain desired H2/CO ratios for Fischer-Tropsch or other downstream energy conversion processes. The model developed in the previous study is extended to the combined steam and dry reforming process. The resulting model was validated using reported experimental data at non-equilibrium and equilibrium conditions. The dynamic and steady state performance of the integrated mixed reforming of methane and nuclear heat system was studied and it was found that in addition to desired H2/CO ratios, higher methane conversion and... [more]