System Operation Process Research Articles

Joint risk-based maintenance strategy and integrated monitoring approach for manufacturing system operational process considering workpiece quality

The fluctuation of various parameters in the production process increases the risk of generating unqualified products and suffering from systematic failures and downtimes, and the preventive maintenance and control of potentially faulty machines in manufacturing systems should consider the continuous increase of operational risk. Therefore, to proactive control the manufacturing system operational risk, a joint model of risk-based maintenance (RBM) and integrated monitoring is proposed. The proposed model formulates an appropriate maintenance strategy and appropriate control charts for monitoring the manufacturing process, guaranteeing the stable operation of the manufacturing system. First, considering the co-effect of the production equipment state and workpiece quality, a novel connotation of the manufacturing system mechanism’s operational risk is proposed, and the RBM framework is constructed. Second, considering the manufacturing system operational state, an integrated maintenance decision-making model based on different risk scenarios is established using a dynamic monitoring scheme based on EWMA control charts. Third, a particle swarm optimisation algorithm is adopted to optimise the proposed model to obtain the optimal maintenance strategy for production equipment and monitoring parameter for workpiece quality. Finally, the effectiveness of the proposed approach is illustrated with a case study on a subway current receiver production line.

Control-oriented dynamic modeling and GPC for single-tower double-circulation wet flue gas desulfurization system

In China, the current situation of large-scale grid integration of renewable energy generation and the government's introduction of capacity-based electricity pricing policies have compelled coal-fired power plants to gradually enhance their load adjustment capabilities and expand their load adjustment ranges. Simultaneously, the national environmental requirements for these plants have become increasingly stringent. However, the economic control of wet flue gas desulfurization (WFGD) systems is still far from meeting practical requirements. In this paper, starting from practical engineering applications and utilizing historical operational data, considering the actual system operation process, the impact of the absorption tower variable-frequency slurry circulation pump on the concentration of sulfur dioxide (SO2) in flue gas under different slurry pH values is investigated. This led to the establishment of a dynamic model for a single-tower double-circulation wet flue gas desulfurization (SD-WFGD) system. Recognizing the significant delay and inertia characteristics of pH value control in the SO2 absorption tank, a desulfurization system pH value desulfurization capacity-based optimization control scheme for the SD-WFGD system is proposed, termed as the Direct Sulfur Control (DSC) strategy. Based on the established dynamic model, a SD-WFGD system series control system is developed using a step generalized predictive control algorithm (GPC) combined with the DSC strategy. Validation results indicate that, compared to SGPC control schemes and traditional PID control schemes, this approach reduces fluctuations in slurry supply and outlet SO2 concentration, significantly enhancing the control performance of the SD-WFGD system. This ensures the safe, stable, economical, and flexible operation of the desulfurization system against the backdrop of flexible operation in coal-fired power plants.

Uncertain parameters adjustable two-stage robust optimization of a rural housing integrated energy system considering biomass on-site utilization

Rural areas will be an important component to achieve carbon neutrality. However, there are currently issues such as an unreasonable energy consumption structure and low efficiency in renewable energy utilization. It is urgent to propose an energy optimization solution to address these problems. Therefore, considering the advantages of renewable energy in rural areas and the diversified and decentralized energy consumption patterns of rural households, a rural housing integrated energy system (RHIES) is proposed, which includes photovoltaics and a biomass utilization chain through self-production and local consumption. Subsequently, considering the economic and low-carbon aspects of the system's operational process, an uncertain parameters adjustable two-stage robust optimization model (UPATSRO) is developed to achieve a balance between robustness and economic efficiency during the scheduling optimization process. The results of case study indicate that the proposed RHIES reduces costs and carbon emissions by 28.15% and 93.83%, respectively, compared to conventional approaches. The biomass utilization mode satisfies 52.31% of the gas load and 39.71% of the thermal load for households. Additionally, it is shown that the proposed UPATSRO optimization model can achieve a flexible adjustment of scheduling schemes during the scheduling optimization process.

Influencing Factor Identification and Simulation for Urban Metro System Operation Processes—A Resilience Enhancement Perspective

Influencing Factor Identification and Simulation for Urban Metro System Operation Processes—A Resilience Enhancement Perspective

Terminology, structure and model of the electrical systems operation process

The content of operation as one of the most important stages of the life cycle of a technical system is revealed. The structure of the process of technical operation of electrical engineering systems is considered. The essence of the individual stages of operation is revealed, their functional purpose is given. It is shown that some fundamental concepts related to operation do not have an unambiguous interpretation. The well-known definitions of these concepts are considered and a one-digit formulation of each of them, which corresponds to the current standards, is given. Special attention is paid to the disclosure of the content of the concept of state and consideration of various types of technical states of the system. The definition of the “condition” category, the formulation of which differs from the known definitions and allows more fully and accurately solving the problems of diagnosing the studied electrical systems, is given. An important feature of this definition is that it fixes the continuous variability of the state of any system in a function of time. At the same time, stable technical conditions that differ significantly from each other and correspond to the current version of the standard are distinguished. Such states are serviceable, faulty, operable, inoperable, partially inoperable, marginal. Functional conditions that are determined by the operating modes of the system are considered. The current definitions of the most important properties and events, among which a special place is occupied by reliability, survivability, safety, failure, damage, defect, are given. For the selected technical states, a model in the form of an oriented graph is synthesized. It is shown that the actual process of an electrical system operation has two features. The first one is that the probability of transition from one state to another does not depend on the type of state the system is in at the moment. The second feature is that the time spent in each technical condition can be either deterministic or random. The conclusion about the possibility of modeling the process of changing the technical states of the system by semi- Markov models with a discrete set of states is made. A mathematical model in the form of Kolmogorov differential equations, which makes it possible to estimate the probabilities of the system being in a particular state, has been compiled.

Joint optimization of multi-stage component reassignment and preventive maintenance for balanced systems considering imperfect maintenance

In this paper, a balanced system consisting of several multi-state components is considered to work during multiple sequential stages. The system is balanced when the largest state difference among all components is no greater than a predetermined value. The system fails when it loses balance or when at least one component is completely failed. Components on different positions are functionally exchangeable, while their degradation characteristics vary with distinct loads and external environments. To keep system balance in the long term and improve its reliability, a joint policy of component reassignment and preventive maintenance is proposed considering imperfect maintenance. The positions of components can be exchanged, and they can be maintained to any better states or be left in the present states. At the beginning of each stage, operators need to decide whether and how to reassign and maintain the components to minimize the total expected cost. A Markov decision process is constructed to model the system operation process and to obtain the optimal joint strategies. Two heuristic policies are presented to compare with the proposed policy. A numerical example based on a three-wheel mobile robot is investigated to illustrate the proposed model and validate the effectiveness of the algorithm.

Developing a unit testing framework for control system software implementation of a degassing vacuum pumping station

Research objective is to develop a test automation system for the process algorithm software implementation of the degassing vacuum pumping station control system operation at a coal mine. Relevance. The vacuum pumping station is an essential component of a mine degassing system. Degassing system operation depends on its correct functioning. A programmable logic controller with appropriate software is a key component of the vacuum pumping station automation system. Correct software implementation of the system operation process algorithm is of primary importance. To verify the compliance of the implementation with the requirements, manual testing is commonly used according to a pre-compiled test-plan, which is formed based on the requirements imposed on the system. Manual testing has a number of disadvantages. It is a long process where human errors are likely to occur, and the use of a test bench and/or an assembled control system sample is inevitable. Requirements for the algorithm can be changed in the course of program development, debugging, and initiation, which greatly complicates the testing process. Results. To solve the problem of process algorithm software implementation testing automation, the process control algorithm should be isolated from the software components responsible for the hardware. Access to the process control algorithm should be provided through standard interfaces (for example, OPC UA). Additional process equipment (valves, etc.) used in the automation system should be implemented in the form of emulators with an opportunity to assign their modes of operation. By creating an additional software layer of interaction with a process algorithm and emulator in a programming language with advanced test tools (for example, Python), it is possible to implement test scenarios from a test plan in this language. It will allow testing in automatic mode rather than manually. Conclusions. The proposed approach to process algorithm software implementation testing automation will greatly simplify software development for this type of automation and control systems

The Design of Web Based Information System for 'Bintang Multi Sparepart Store'

The advancements in information technology have provided many conveniences in the process of recording and reporting. Bintang Multi Sparepart Store is a business that sells automotive supplies. Its business process is divided into product sales, product stock fulfilment, and sales report creation. Based on the ongoing business process, sales recordings are done manually with a book, which increases the risk of errors due to spills and dirt on the book, tears, and human error. This results in inaccurate sales report calculations. Information about product availability also often has errors due to inaccurate information. In view of the problems that are occurring, this study designed an integrated information system that can collect, store, and process data to produce accurate information by applying the System Development Life Cycle (SDLC) principles, programming language PHP and MySQL for database storage, and through unit testing, integration testing, system testing, and acceptance testing. The designed information system is operating well, and the entire process in the information system meets the user's needs in terms of functionality and usability. The implementation of the proposed information system allows the owner to monitor all business processes, including transaction data and product data. The proposed information system is also capable of storing, summarizing, and presenting the entire sales transaction data in real time. In addition, the designed information system can process calculation on transaction data to be presented in the form of an accurate sales report, and there is a manual to make the information system operation process easier.

A two-phase power flow algorithm of traction power supply system based on traction substation-network decoupling

Power flow analysis of traction power supply system (TPSS) is an effective approach to assess supply capacity and power quality, serving the whole process of system design, operation and optimization. The coupling effect between adjacent power supply arms poses challenges for the accurate and efficient solution, especially with the penetration of power converters and energy equipment. This paper proposes a two-phase power flow decoupling algorithm. TPSS is divided into traction substation and two decoupled power supply arms by introducing current ratio coefficients and unit matrices. Specifically, the equivalent voltage source model of traction substation and the modified chain network model of arms are solved by using forward–backward sweep method and LU decomposition method, respectively. Then the TPSS power flow can be obtained by alternative iteration of two solving phases. Simulations verify the proposed algorithm exhibits great compatibility at various operation modes. Additionally, the power supply capacity is mapped to the algorithm convergence. Compared to conventional methods, the algorithm achieves superior performance on accuracy and efficiency.

Harmonizing the use of optimization and feedback in process operations and control

This paper addresses how to combine the two main engineering design tools, optimization and feedback, to obtain high performance process control or process operation systems. We discuss the historical development of process control, where feedback dominated the early practical designs, and optimization was then incorporated much later through technologies like model predictive control. In chemical production scheduling, on the other hand, optimization had a strong early influence on the problem formulation, and feedback has only recently made an appearance. The recent developments in both process control and scheduling are illustrated with specific examples emerging from this series of FOCAPO/CPC meetings. The paper next presents recent theoretical developments in nominal and stochastic model predictive control. The closed-loop properties that arise from these different open-loop optimal control problems are then compared. The paper closes with some discussion of when the improvements of the closed-loop properties are worth the added complexity of the stochastic optimal control problem.

Topology Analysis of Full-Controlled Hybrid Switching Network in Fusion Device

Switching network unit (SNU) of fusion device excites the plasma and finally establishes the plasma current. The full-controlled hybrid scheme is the research trend and hotspot of SNU in a nuclear fusion device. Based on the analysis of the SNU schemes in the current fusion devices, two kinds of full-controlled hybrid circuits are compared and analyzed. Through the principle analysis, theoretical calculation, and model simulation under 50 kA, the system operation process and the influence of arc voltage and other related parameters on the operation process are studied and discussed. Finally, the main characteristics and applicable conditions of the two circuits are described. At the same time, the aspects needing attention in circuit design are explained. The research shows that the basic circuit is suitable for high-current circuits, and the multistage commutation circuit is suitable for high-voltage circuits. The above study can provide a useful reference for the design of full-controlled hybrid SNU.

The dynamic performance of a compact LN2 depressurization cryocooling system

Liquid nitrogen (LN2) has been widely used as a cooling medium. A compact LN2 depressurization cryocooling system can be used as a portable cooling unit to satisfy flexible cooling requirements. A prototype of this cryocooling system which was mainly composed of a LN2 tank, a LN2 pump, a heat exchanger and a vacuum pump was built and tested. In the test, the lowest cooling temperature could reach below 65 K, and the average temperature of 0.95 m3 LN2 dropped from 73.5 K to 68.1 K after 6814 s of running. The average refrigeration power reached 1326 W at 65 K. Meanwhile, the system operation process was simulated through theoretical analysis and modeling. Simulation results were nearly consistent with experimental results and the dynamic operating characteristics were well captured. For the experimental apparatus, the LN2 supplement and shutdown of the liquid-ring pump affect the system cooling performance, and modeling results show that the cooling efficiency decreases with the LN2 volume flow rate V̇LN2 increasing whenV̇LN2 > 0.9 m3/h.

Design and Conception of Will Notarization System Based on Ethereum

It is crucial to use blockchain to notarization system. Although a notarized will has the highest legal effect, the notarization process is cumbersome, the notary agency has heavy responsibilities and high costs, which has become a drawback of notarized wills, and which makes many people give up notarized wills. This research will design a will notarization system based on blockchain technology to solve the problem of difficult will notarization. Through demand analysis and scenario analysis, this paper builds the overall architecture of the will notarization system based on blockchain technology and the Ethereum platform. The architecture consists of three parts: the client used by the user, the server provided by the notary office, and the blockchain module. Based on the Truffle framework provided by Ethereum, it will involve multiple links such as HTML front-end development, JavaScript development, solidity smart contract development, Ethereum interface call, network construction, etc., to design the entire system deployment and operation process.

Comparative study on peak power prediction methods during start-up and power-up of heat pipe reactor based on neural network and decision tree

The effective control of start-up and power-up processes is essential if thermal power reactors are operated autonomously. The decision-making processes of an autonomous operating system must anticipate and suppress unwanted power fluctuations in a timely manner. The rapid and accurate predictions of the peak power to be expected in a surge can help an autonomous operating system to make more appropriate and timely decisions. This paper compares the predictive performance of the neural network with that of the decision tree, where both are based on peak power datasets for start-up and power-up processes. We explain how the datasets are constructed, i.e., by coupling the Monte Carlo sampling methods with the analysis of the system analysis procedure. We introduce a framework for the comprehensive evaluation of both prediction algorithms. We conclude that the neural network has better intrinsic predictive accuracy than the decision tree for the control of start-up and power-up processes. With further expansion of the datasets, it is expected that the predictive advantage of the neural network will become more evident. However, predictive accuracy is not the only criterion by which different predictive algorithms can be compared. The poor interpretability and high training costs of the neural network limit its application in practice while the accuracy of the decision tree can be improved via ensemble strategies. Therefore, deciding an algorithm to use is a complex selection process that should reflect the constraints of the specific application.

A bi-level approach for participation of hybrid transmission operating companies in the day-ahead market, considering energy storage systems

This paper presents a new approach for participation strategy of Hybrid Transmission Operating Companies (HTOCs) in the day-ahead energy market. In this paper HTOC refers to private companies that have won physical transmission rights (PTR) and also own energy storage facilities. In the introduced hybrid structure, the HTOC can make profit in two different ways; first, through the flow of transmission lines (the MW-Mile transmission pricing method is used here); and second, through an optimum scheduling of its energy storage system. The optimum charge/discharge pattern of energy storage systems, evaluated in this paper, would also increase the MW-Mile profit of the company. The proposed method is a bi-level optimization model. In the upper level the profit of the HTOC is maximized and in the lower level the market clearing process of the independent system operator (ISO) has been modeled. The uncertain behavior of rival units is modeled using robust optimization (RO) method. The Karush-Kuhn-Tucker (KKT) optimality conditions are implemented to convert the proposed bi-level problem into its equivalent single-level problem. The Big-M method and the strong duality theorem (SDT) are used to linearize the proposed method. To demonstrate the performance of the introduced structure for HTOC, the proposed strategy has been implemented on a standard IEEE 9-bus and 57-bus test systems. The results show that HTOC can achieve a maximum guaranteed profit using storage resource (SR). It is also concluded that the presence of SR has not only increased HTOC's profit but also helped to make the structure more flexible against the uncertain parameters. In addition, the RO as a calculation risk method has been perfectly matched with the implementation of SR as a source of hedging uncertainties in managing the risk.

A Traceable Vaccine Supply Management System.

Everyone should be vaccinated, but the eligibility and safety of the vaccine are always overlooked by most people. The outbreak of COVID-19 has led many countries to intensify the development and production of the COVID-19 vaccine. and some countries have even required universal vaccination against this epidemic. However, such popularization of vaccination has also exposed various flaws in vaccine management that existed in the past, and vaccinators have become more concerned about the effectiveness of their vaccinations. In this paper, we propose a blockchain-based traceable vaccine management system. First, the system uses smart contracts to store the records generated during the whole process, from vaccine production to vaccination. Second, the proposed scheme uses the Edwards-curve digital signature algorithm (EdDSA) to guarantee the security and integrity of these data. Third, the system participants can access the corresponding data according to their authority to ensure the transparency of the whole system operation process. Finally, this paper will also conduct a security analysis of the whole system to ensure that the system can resist potential attacks by criminals.

An improved affine arithmetic‐based optimization method for district energy systems with uncertainties

AbstractIn the process of the district energy system (DES) operation and dispatching, there are various uncertainties brought by the strong coupling of equipment and the fluctuation of internal and external surroundings, and these uncertain parameters are often correlated. In this paper, an improved affine arithmetic‐based method is proposed to solve the economic dispatching problem of DES with correlated uncertainties. First, an optimal dispatching model considering economic and environmental factors is constructed. An affine algorithm is introduced and interval arithmetic is used to improve the problem of interval extension and high‐order noise element. Taking a classical DES system as an example, the optimal dispatching of the system is analyzed using deterministic method, interval method, and proposed method. The application effect of the proposed method under different uncertainties scale and amplitude is also discussed. The results show that the proposed method can effectively reduce the width of target value interval compared with the traditional interval optimization method, which can further contribute to the optimal operation decision.

Research on three-dimensional visualization system of Natech events triggered domino accidents in oil-gas depots

Natech events and domino accidents happen worldwide and usually lead to severe consequences, especially in hazardous areas such as Oil-Gas depots. With the continuous development of the Oil-Gas industry and information technology, it is essential to realize the three-dimensional management and monitoring of hazardous substances. To evaluate the consequences caused by Natech events triggered domino accidents (accident chain), a matrix loop method was proposed to calculate the probability and evolution path of the accident chain. The actual layout and the real-time data of the Oil-Gas depot are input into the evaluation method in matrices, thus making the results reliable and updated. Besides, a B/S architecture system is developed to present the evaluation consequences of the proposed method. The three-dimensional visualization effects of natural disasters, technological accidents and the dynamic propagation process of the accident chain are also realized in the system to enhance the user's experience. A system application regarding lightning-triggered domino accidents was carried out to demonstrate the feasibility and rapidity of the proposed evaluation method and perform the system's operation process and visualization effects. The application results show that the system can provide effective decision-making assistance to safety management workers before the accident and guidance for emergency rescue operations during the accident.

Multi-voltage level distributed backward–forward sweep power flow algorithm in an agent-based discrete-event simulation framework

In the energy transition context, the use of steady-state time series is a promising approach to account for temporal interdependencies and flexibilities in modern distribution power system analysis, planning, and operation processes. This paper proposes a distributed backward–forward sweep power flow algorithm executed in a discrete-event, agent-based simulation framework. The algorithm shows fast convergence, allows for concurrent execution, and scales up to large-scale multi-voltage level grids with arbitrary topology. An agent-based simulation model integrates the developed algorithm to generate detailed grid utilization, asset, and system participant time series. We demonstrate the capabilities of our approach by performing several simulations, leveraging the proposed algorithm, on nine different benchmark grid models. The selected models comprise grids at a single voltage level, medium voltage level, and combined multi-voltage levels. The evaluation of the numerical results validates the approach and demonstrates its capabilities.

고교학점제 운영 과정에서 고교 교사들이 겪은 어려움에 대한 인식과 역할 내용 탐색

Objectives For the successful introduction and settlement of the high school credit system, it is important to expand the role of teachers related to the operation of the high school credit system and secure expertise. To this end, it is necessary to examine the actual difficulties experienced by high school teachers in the process of operating the high school credit system and derive the new role performance required by teachers based on this.
 Methods Therefore, in this study, the difficulties experienced by teachers with experience in operating the high school credit system in terms of ‘formation of school culture’, ‘curriculum organization and operation’, ‘career and academic design guidance’, ‘school designs and support for related departments’, etc. were analyzed through focus group interviews. Then, we looked at the role of field teachers who are to operate the high school credit system in the future.
 Results As a result of the analysis, it was found that teachers were required to have the ability to perform roles related to the formation of a school culture suitable for the operation of the high school credit system and the establishment⋅support of the operating system. In addition, since the organization and operation of the student-selective curriculum is the core of the high school credit system operation process, it was confirmed that it was essential for teachers to secure the role performance ability to prepare and operate the educational system that students need. Finally, it was found that teachers were required at a professional level to have the ability to perform roles that support students to design and perform their own studies according to their aptitude and career path.
 Conclusions In the future, it is expected that understanding of the role of teachers essential for the operation of the high school credit system derived in this study will be helpful in providing various administrative support to secure teachers' expertise and improve their capabilities.