Plant Simulation Research Articles

АЛГОРИТМ ОПРЕДЕЛЕНИЯ ПАРАМЕТРОВ РЕГУЛЯТОРА, УДОВЛЕТВОРЯЮЩИХ ТРЕБОВАНИЯМ ПЕРЕХОДНОГО ПРОЦЕССА В ПОНИЖАЮЩЕМ ПРЕОБРАЗОВАТЕЛЕ ПОСТОЯННОГО НАПРЯЖЕНИЯ

The relevance Any modern simulator of an integral part of the spacecraft power supply system (SC PSS) is an energy-converting complex and is a continuous- discrete, non-stationary system with a variable structure. In order to fully simulate all modes of solar and storage batteries, as well as all types of electrical load, simulators must be developed consisting of several interconnected subsystems that form the overall structure of the simulator. During the tests, depending on the current mode of operation, one of the necessary (not in demand) subsystems at a given time is connected (disconnected), i.e. simulators are systems with a variable structure. Taking into account the power of the PSS of the spacecraft, simulators of the components of the PSS should have no less than the rated power, and therefore they must be created on the basis of power converters of electricity, since the latter have the best efficiency of possible energy-converting electrical systems. In addition, modern power conversion systems are impossible without the use of electronic computing tools — lower-level controllers and computers, on the basis of operating systems of which a fullfledged control software package is deployed. Thus, a modern simulator of the PSS component is a continuous-discrete impulse system. Taking into account the requirements for reliability and the period of active operation imposed on modern solar power plant simulators, it should be borne in mind that over long periods of operation, the parameters of electronic components degrade, on the basis of which power converters are built. Thus, the simulators of the PSS components of the spacecraft are non-stationary systems with long periods of active operation. Thus, at present, it is relevant to consider approaches to determining continuous linear models of power converters of electrical energy in order to synthesize the controllers of their control systems, which form the basis for constructing any simulator of an integral part of the PSS of a spacecraft. Aim of research To form a multilevel computer model of a DC converter and determine the values of the coefficients of the voltage and current PID controllers that provide optimal switching between its operating modes. Research methods Method of multilevel component chains, method of coordinate descent. Results In the format of the method of multilevel component circuits, a multilevel model is formed that provides the determination of the values of the parameters of the coefficients of the voltage and current PID controllers, at which the optimal switching between the modes of its operation is observed in the DC buck converter.

Exergy Analysis of Organic Rankine Cycles with Zeotropic Working Fluids

Waste heat recovery is one of the possible solutions to improve the efficiency of internal combustion engines. Instead of wasting the exhaust stream of an energy conversion system into the environment, its residual energy content can be usefully recovered, for example in Organic Rankine Cycles (ORC). This technology has been largely consolidated in stationary power plants but not yet for mobile applications, such as road transport, due to the limitations in the layout and to the constraints on the size and weight of the ORC system. An ORC system installed on the exhaust line of a bus powered by a natural gas spark ignition engine has been investigated. The thermal power available at engine exhaust has been evaluated by measuring gas temperature and mass flow rate during real driving operation. The waste thermal power has been considered as heat input for the ORC plant simulation. A detailed heat exchanger model has been developed because it is a crucial component for the ORC performance. The exergy analysis of the ORC was performed comparing different working fluids: R601, R1233zd(E) and two zeotropic blends of the two organic pure fluids. The model allowed the evaluation of the ORC produced energy over the driving cycle and the potential benefit on the engine efficiency.

Analysis of Traffic Noise Pollution Using Siemens Tecnomatix Plant Simulation

This paper considers a simulation-based tool for the prediction of roadside noise pollution. A special feature of the tool is that its core is a standard manufacturing simulation software – Tecnomatix Plant Simulation by Siemens. The tool uses standard elementary object classes of Plant Simulation such as path, vehicle, method etc., and provides a powerful and highly parameterisable environment for analysing the noise pollution by traffic flows. It possesses a high flexibility of model programming and is open for extensions and adjustments to new calculation methods. The infrastructure modeling facilities are essentially independent of the noise computation algorithms and thus can be used with various tool-internal or external numerical calculation components. As a result of earlier computational studies, a set of functional interdependencies of flow parameters and model settings have been obtained, and methods for calculating noise indicators have been adapted for their implementation in embedded languages of simulation tools. As a result of the programming-experimental study, a "Traffic Noise Tool" (TNT) software module has been developed. TNT allows to analyse the impact of traffic flow characteristics (traffic intensity, traffic flow by vehicle categories, and traffic mode in each track etc.) and of road infrastructure (number and carrying capacity of the cracks, additional distance between opposite directions, availability of noise protection devices, etc.) on the noise pollution of the roadside environment. During the simulation&calculation process, the noise characteristics of the individual vehicles are recorded and displayed by diagrams, and so is the equivalent overall noise level at a given monitoring point. The results of this study can be used in the practice.

Process system integration

Process engineering today is concerned with the understanding and development of systematic procedures for design and optimal operation and control of the chemical process systems. This work motivated by the need to provide a more flexible than existing approaches framework for changes in chemical process engineering in particular, and for predicting the behavior of process systems in general. Integrated method of the process systems development make possible seeking out the most adequate model for simulation of real process design and optimization, that leads to improving current and development a new processes. The study state plant simulation model and dynamic simulation model make significant tools for observation behavior of the process. Comparative study of different processes can established more concurrent process alternatives.

Simulation and Initial Experiment of a Twist-Tilt Quadcopter for Fully Actuated Motion

Although conventional quadcopters are well developed and are used in many applications, they are limited to 4 degree-of-freedom motion. For instance, the underactuated quadcopters cannot hover with inclined roll or pitch angles. To achieve fully actuated 6 degree-of-freedom motion, this paper presents a design, construction, and initial experimental results of an overactuated twist-and-tilt quadcopter configuration proposed in the group's previous work. The copter is comprised of four rotors, where each rotor's twist and tilt angles are independently adjustable over one full rotation by servo actuators. The copter weighs 5.78kg and is designed to carry an additional 5kg payload. A comprehensive multi-body virtual plant simulation model was also created with identified parameters from the rotor-arm drive dynamics to verify the control, which is designed based on a lumped single rigid body model. Also, an experimental rig was constructed to facilitate flight testing in a small physical space with safety to both the copter and environment. The initial experimental results for 6 degree-of-freedom motion is then presented.

Design of Pico-Hydro Power Plant with Monitoring System Based on Internet of Things

Currently the electrification ratio in Banyumas Regency is around 79%. This means, of the 1.7 million residents of Banyumas Regency, only around 21% have not enjoyed PLN electricity. Those whose homes have not yet had electricity are on average residents who are on the slopes of the mountain slopes, and some residents in several groves in remote areas in Banyumas Regency which are very far from the PLN electricity network. This problem can be overcome by providing electrical energy by utilizing renewable alternative energy, one of which is micro hydro or pico hydro power plants on an individual or residential scale. Therefore, this research designed a simulation of a pico hydro power plant using a Pelton turbine which is expected to be able to provide benefits to the general public, this tool is equipped with remote monitoring using Google Firebase based on the Internet of Things which can be monitored via the Android application for monitoring Voltage, current and power use the INA219 sensor which has been programmed on Arduino Uno and Node MCU ESP8266. This tool uses a 12-24 Volt DC generator, produces DC electricity which is stored in a 12 Volt 5 Ah battery which is then converted using an inverter to become AC electricity. In this test using a 5 Watt AC lamp load, the battery voltage which was initially 12.6 Volts was reduced to 9.9 Volts, the lamp load was able to light up for 1 hour. In measuring the voltage and current, the generator produces an average voltage of 15.9 Volts and a current of 50.2 mA.

Verification of intelligent scheduling based on deep reinforcement learning for distributed workshops via discrete event simulation

Production scheduling, which directly influences the completion time and throughput of workshops, has received extensive research. However, due to the high cost of real-world production verification, most literature did not verify the optimized scheduling scheme in real-world workshops. This paper studied the verification of scheduling schemes and environments, using a discrete event simulation (DES) platform. The aim of this study is to provide an efficient way to verify the correctness of scheduling environments established by programming languages and scheduling results obtained by intelligent algorithms. The system architecture of scheduling verification based on DES is established. The modelling approach via DES is proposed by designing parametric workshop generation, flexible production control, and real-time data processing. The popular distributed permutation flowshop scheduling problem is selected as a case study, where the optimal scheduling scheme obtained by a deep reinforcement learning algorithm is fed into the production simulation model in Plant Simulation software. The experiment results show that the proposed scheduling verification approach can validate the scheduling scheme and environment effectively. The utilization and Gantt charts clearly show the performance of scheduling schemes. This work can help to verify the scheduling schemes and programmed scheduling environment efficiently without costly real-world validation.

On-site simulator-based initiating event detection and identification in NPPs

Installing safety components to prevent a severe accident from developing from an initiating event is essential. Although various approaches have been presented to detect and identify initiating events, their development relies on the data simulated by computer codes like the Modular Accident Analysis Program. This study focuses on developing approaches to detect and identify initiating events using the data generated by a nuclear power plant (NPP) on-site simulator. By relying on historical data to construct an empirical model that can predict normal operation sensing readings, an abnormal event that leads to excessive discrepancies between the acquired and predicted readings can be detected. Several single- and multiple-sensor feature extraction methods have been presented to find low-dimensional representations for initiating events to facilitate accurate event identification. The results from detailed experiments containing data of 13 event categories with 185 events generated by the Maanshan NPP plant simulator demonstrated the feasibility of developing on-site simulator-based schemes for detecting and identifying initiating events.

Reconstruction Layout Optimization of Multivariety and Small Batch Workshop in Aerospace Industry.

To cope with the problems of frequent mold changes, long production cycles and serious logistics crossings in workshop of aerospace enterprise. First, a manufacturing cell layout planning method based on the feature bit code domain method and K-Means++ is proposed to realize the accurate division of manufacturing cells. Then, a multiobjective optimization method of dynamic reconstruction layout based on improved fruit fly optimization algorithm (IFOA) is proposed to solve the reconstruction layout optimization of the production workshop problem with the optimization objectives of logistics cost, reconstruction cost, loss cost, and cell integrated area. Finally, plant simulation software is applied to simulate the workshop layout before and after optimization. The simulation results show that the logistics cost of the workshop cell layout after optimization is reduced by 8.7%, the utilization rate of the workshop area is improved by 5.2%, and the value-added rate of products is increased by 6.6%, which verifies the effectiveness and feasibility of the proposed model and method.

A Three Stage Optimal Scheduling Algorithm for AGV Route Planning Considering Collision Avoidance under Speed Control Strategy

With the trend of terminal automation and the requirement for port operation efficiency to be greatly improved, it is very necessary to optimize the traveling route of automatic guided vehicles (AGV) with reference to the connection of loading and unloading equipment. As a complex multi-equipment system, it is inevitable that AGV will collide when traveling due to various accidents in actual operation, which will lead to AGV locking and reduce the efficiency of terminal operation. Considering the locking problem of AGV, we propose a three-stage integrated scheduling algorithm for AGV route planning. Through joint optimization with quay cranes (QC) and yard blocks, a road network model is established in the front area of the container port to optimize the path of AGV in the road network, and a speed control strategy is proposed to solve the problem of AGV collision avoidance. In the first stage, we establish the AGV optimal route model with the goal of minimizing the AGV path according to the AGV road network situation. In the second stage, on the basis of the determination of AGV route planning, and when the container task is known, the AGV task assignment model is established with the goal of minimizing the maximum completion time, and the model is solved by genetic algorithm (GA). In the third stage, on the basis of AGV task assignment and route determination, the AGV route and AGV task assignment scheme are input into the simulation model by establishing the AGV collision avoidance control model for speed control, and establishing the AGV route network simulation model for automated terminals considering collision avoidance in plant simulation software. The maximum completion time obtained from the simulation model is compared with the completion time obtained from the genetic algorithm. The proposed three-stage joint scheduling algorithm can improve the loading and unloading efficiency of the port, reduce the AGV locking situation, and has a certain contribution to the formulation of the actual operation planning of the port.

If self-shading is so bad, why is there so much? Short shoots reconcile costs and benefits.

If trees minimize self-shading, new foliage in shaded parts of the crown should remain minimal. However, many species have abundant foliage on short shoots inside their crown. In this paper, we test the hypothesis that short shoots allow trees to densify their foliage in self-shaded parts of the crown thanks to reduced costs. Using 30 woody species in Mediterranean and tropical biomes, we estimated the contribution of short shoots to total plant foliage, calculated their costs relative to long shoots including wood cost and used 3D plant simulations calibrated with field measurements to quantify their light interception, self-shading and yield. In species with short shoots, leaves on short shoots account for the majority of leaf area. The reduced cost of short stems enables the production of leaf area with 36% less biomass. Simulations show that although short shoots are more self-shaded, they benefit the plant because they cost less. Lastly, the morphological properties of short shoots have major implications for whole plant architecture. Taken together, our results question the validity of only assessing leaf costs to understand leaf economics and call for more integrated observations at the crown scale to understand light capture strategies in woody plants.

A User-Friendly Dynamic Reactor Simulator Built in Microsoft Excel

Computer plant simulation is being used in all aspects of engineering, through many simulation software packages. However, almost all of them require licenses that must be purchased by engineering colleges intending to use simulation in their teaching. As public educational institutions everywhere are facing a scarcity of economic resources, they can resort to a freeware steady-state plant simulator, however, there is no availability of reliable, free dynamic plant simulators. In addition, published experiences on developing dynamic simulators use programming languages requiring paid licenses (e.g. Matlab) and thus have limited relevancy to schools struggling to cut expenses. This article first uses a set of typical college objectives to discuss the advantages of building their own dynamic simulators, and then shows the development of a user-friendly dynamic simulator of a batch reactor constructed entirely within Microsoft Excel, which, in contrast to the programming languages used in related reports, is already widely used by universities around the world.

Application of Freely Moving AGVs in a Discrete Event Simulation Environment: A First Model

The use of automated guided vehicles (AGVs) in manufacturing systems has become particularly widespread in the latter period, thanks to the intensification of automation and to the adoption of the Industry 4.0 principle. Modern AGVs can also have greater autonomy then before, thanks to the advancement of the related technologies which further improve their applicability in numerous complex settings. In the Industry 4.0 principle, the use of predictive simulations in relation to manufacturing logistics systems also plays an important role, which applies to the modelling of the operation of AGVs as well. In light of these developments, the current paper introduces an initial model with the aim to demonstrate a possible approach for modelling the operation of freely moving AGVs in a discrete event simulation environment. The model is made with Plant Simulation, a widely applied discrete event simulation software. The presented approach opens the door for multiple future research avenues and could also serve as a basis for a further developed general model with wider utilization possibilities.

Modal Identification of Low-Frequency Oscillations in Power Systems Based on Improved Variational Modal Decomposition and Sparse Time-Domain Method

Power systems have an increasing demand for operational condition monitoring and safety control aspects. Low-frequency oscillation mode identification is one of the keys to maintain the safe and stable operation of power systems. To address the problems of low accuracy and poor anti-interference of the current low-frequency oscillation mode identification method for power systems, a low-frequency oscillation mode feature identification method combining the adaptive variational modal decomposition and sparse time-domain method is proposed. Firstly, the grey wolf optimization algorithm (GWO) is used to find the optimal number of eigenmodes and penalty factor parameters of the variational modal decomposition (VMD). And the improved method (GWVMD) is used to decompose the measured signal with low-frequency oscillations and then reconstruct the signal to achieve a noise reduction. Next, the processed signal is used as a new input for the identification of the oscillation modes and their parameters using the sparse time-domain method (STD). Finally, the effectiveness of the method is verified by the actual low-frequency oscillation signal identification in the Hengshan power plant and numerical signal simulation experiments. The results show that the proposed method outperforms the conventional methods such as Prony, ITD, and HHT in terms of modal discrimination. Meanwhile, the overall reduction in the frequency error is 34, 44, and 21%, and the overall reduction in the damping error is 37, 41, and 18%, compared with the recently proposed methods such as the EFEMD-HT, RDT-ERA, and TLS-ESPRIT. The effectiveness of the methods in suppressing the modal confusion and noise immunity is demonstrated.

Optimisation of the Logistics System in an Electric Motor Assembly Flowshop by Integrating the Taguchi Approach and Discrete Event Simulation

An electric motor assembly flowshop (EMAF) is a type of classical mixed-product assembly line that uses automatic guided vehicle (AGV) systems for material handling. To optimise the logistics system configuration and alleviate the impact of the AGV parameters on the efficiency of the EMAF, a modelling and optimisation method based on discrete event simulation (DES) combined with Taguchi orthogonal experimental design was proposed. A DES model of the entire production process for the EMAF was constructed using the Tecnomatix Plant Simulation software package. After optimisation of the principal layout in the DES model, the number of assembly stations was decreased from 13 to 9, and the balance ratio was increased from 65.08% to 84.65%. In addition, the combination of the Taguchi method with the DES model was further developed to achieve the optimal parameter combination of the AGVs in order to allow the AGVs to operate more efficiently under various states. The final overall theoretical throughput was increased from 134 to 295 units within the seven-hour observation period.

Technological Assessment on Steam Reforming Process of Crude Glycerol to Produce Hydrogen in an Integrated Waste Cooking-Oil-Based Biodiesel Production Scenario

The current scenario of society is to produce fuel from renewable energy resources. The purpose of this research work is to develop an integrated approach for glycerol valorization and biodiesel production. Employing a range of methodologies widely used in the industry, technical analysis and assessments of the process’s applicability in real-world situations are also made. The integrated process plant is simulated using Aspen Plus®. Several different sensitivity analyses are carried out to describe the process that improves efficiency and are designed to maximize hydrogen recovery from the reforming section. The integrated process results are compared with several existing standalone biodiesel production processes. Additionally, the results are verified with the theoretical studies on glycerol valorization. The outcomes of the process plant simulation reveal coherent results with the current industrial standards for the two processes. The results show that the amount of glycerol produced (stream 7) is 60.72 kmol/h in mass flow rate, this translates to 7272.74 kg/h. The hydrogen produced is 488.76 kmol/h and, in mass flow rate, this translates to 985.3 kg/h. The total yield of hydrogen produced is around 13%. The biodiesel yield is at 92.5%. It shows a realistic recovery that would be attained if the process is implemented, contrary to theoretical studies.

Simulation and Laboratory Model of Small Hydropower Plant

Abstract This paper is dedicated to the description of all our research done so far in the field of simulation of small hydropower plants as well as in creating a functional laboratory model based on the proposed simulation models. Comparing to the common structures, we propose some different approaches in modelling parts of the small hydropower plants, e.g. fuzzy model of the hydraulic turbine efficiency. Moreover, this simulation model is created directly for the small hydropower plants, thus it simplifies parts, that are commonly used in other scientific papers and simulate the phenomenon connected to the big scale hydropower plants structure and physical description. As a necessary step in the process of creation of universal laboratory model of a small hydropower plant that should be used for design and tuning purposes of new approaches of controlling such systems, we discuss the research and development phase that led to the final construction of the depicted laboratory model.

Proposal for an aggregated solar PV power plant simulation model for grid code compliance

• Evaluation of the most recent Spanish grid code requirements. • A new tool to speed up the commissioning of new solar PV power plants is presented. • The accuracy of the aggregated PV power plant dynamic model proposed is demonstrated. • The aggregated model is shown to be ten times faster than the detailed equivalent. • The aggregated solar PV power plant simulation model approved by the Spanish TSO. Renewable energy and, in particular, solar PV power, will play a crucial role in achieving net-zero emissions scenarios over the coming decades. Increasing the share of renewables in countries’ energy mixes is therefore a major challenge that must be urgently addressed. Within this context, the present work proposes an innovative tool that may accelerate the commissioning process of new solar PV power plants, in the form of an aggregated simulation model to assess a power plant's responses under the technical requirements established in the Spanish grid code. Our analyses, based on the comparison of the proposed model with a detailed model -both representing the same installation, show, from a quantitative and qualitative viewpoint, the accuracy and usefulness of the dynamic simulation model proposed. The aggregated model is shown to be ten times faster than the detailed equivalent, while the errors encountered in the simulation responses of both models are below 0.1% in all cases. It must also be noted that the present paper has allowed for the introduction, in the most recent version of the Spanish grid code and following approval of the Spanish Transmission System Operator (TSO), Red Eléctrica de España (REE), of this new and advantageous PV power plant model. Finally, it is worth mentioning that this study could form the basis for encouraging other countries to also adopt this model in their grid codes as a new tool to help integrate PV power into power grids.

ANALISA PENGGUNAAN ENERGI ANGIN SEBAGAI PEMBANGKIT LISTRIK ALTERNATIF DI KOTA PALU

Currently, the energy we use is still using fossil energy. In the future, the need for energy will increase because every year there is a large population growth. If you still use fossil energy and don’t find new energy alternatives, then Indonesia will experience a severe energy crisis and certain places will experience blackouts. One of the efforts so that the wind energy crisis can be minimized is to utilize natural energy that has the potensial to generate energy such as the Wind Power Plant. In this study, planning and simulation of Wind Power Plant were carried out to help reduce the use of fossil energy and help the needs of the community in the Talise Beach area. From the results of the study that the average output of wind turbine production is 1,180/hour winh a maximum production of wind turbines per day of 5,665 kW and the construction system cost (NPC) of Rp. 91,340,660,000. Electrical energy that can be generated from wind turbines by utilizing an area of about 42,021.67 m2 is 10,332,498 kWh/year with a total unfulfilled power of 1,416 kW/year. Lack of power or unmet load can be overcome by the existence of a grid/network.

Research on Using the Tecnomatix Plant Simulation for Simulation and Visualization of Traffic Processes at the Traffic Node

Simulation software Tecnomatix Plant Simulation was originally created for a modelling and subsequent simulation of production and logistics processes. Its variability, however, opens its use also in other areas such as transport in urban agglomerations. Based on that, research was implemented to verify the program’s application in urban transport, specifically to visualize and simulate traffic processes at the traffic node. The paper describes a methodology which made it possible to create a simulation program for traffic light intersections, and presents examples of the simulation model application. The proposed methodology will enable the application of Tecnomatix Plant Simulation to create a complex simulation model of the logistics process. It will mainly enable to simulate the field of production logistics and city logistics within one simulation model.