System Operation Quality Research Articles

Energy-Aware Multicriteria Control Performance Assessment

Generally, control system design and the associated assessment of control system quality focuses on cutting-edge performance. Most of the approaches and applied indicators aim for this goal. However, the current times increasingly indicate the need to consider, at least on an equal level, the issue of the resistance of the control system and the energy that it consumes. Indicators for the assessment of the quality of control system operation should take these aspects into account. This study focuses on energy issues. It should be noted that, very often, an actuator device, such as a pump, motor, or actuator, consumes energy. In small single-loop systems, the share of this energy is usually negligible, but in large installations, it begins to reach significant values. This work proposes a multi-criteria assessment of the operation of control systems using information about the control signal. The energy factor can be considered in the form of a quadratic relationship or using the valve travel and valve stroke indicators known in other contexts. The index ratio diagram (IRD) approach is utilized as an energy assessment tool. At the same time, an analysis is carried out showing the impact of energy on other known indicators based on the control error. Finally, a methodology incorporating energy consumed by the control system is proposed.

Construction of power load control and management terminal operation system based on machine learning technology

With the increasing Power Load (PL), the operation of the power system is facing increasingly severe challenges. PL control is an important means to ensure the stability of power system operation and power supply quality. However, traditional PL control methods have limitations and cannot meet the requirements of load control in the new era of power systems. This is because with the development of modern industry and commerce, the demand for electricity is gradually increasing. This article constructed a PL control and management terminal operating system based on machine learning technology to achieve intelligent management of PL, so as to improve the operational efficiency and power supply quality of the power system. This article identified the design concept of a PL control management terminal operating system based on machine learning technology by reviewing the current research status of PL control technology. Based on the operational characteristics and data characteristics of the power system, this article selected suitable machine learning algorithms to process and analyze load data, and established a prototype of a PL control and management terminal operating system based on machine learning technology, so as to realize intelligent processing and analysis of load data and conduct experimental verification. The experimental results show that through the comparative study of 6 sets of data in the tertiary level, the difference between the system and the real tertiary level is 0.079 kw, 0.005 kw and 0.189 kw respectively. Therefore, therefore, the average difference between the predicted value and the measured value of the PL system is about 0.091 kw. This indicated that the system had high accuracy and real-time performance in predicting PL, which could effectively improve the load control efficiency and power supply quality of the power system. The PL control management terminal operating system based on machine learning technology constructed in this article provided new ideas and methods for the development of PL control technology. In the future, system algorithms can be further optimized and a more intelligent PL control and management terminal operating system can be constructed to cope with the growing PL and increasingly complex power system operating environment.

Use of Information Systems in Emergency Department and employee satisfaction

Introduction: The existence and usage of an appropriately designed information system is obligatory for efficient function of the Emergency Department (ED). Purpose: Factors that determine Emergency Department workers’ satisfaction by Information System (IS) and the improvement measures that can be implemented. Material and Method: Non-experimental quantitative cross-sectional online study of 88 Emergency Department health care workers with questionnaire included from Nurses Attitudes Toward Computerization (NATC) by Brodt & Stronge (1984) and End-User Computing Satisfaction by Bailey and Pearson (1983). The statistical package SPSS version 26 was used for data analysis and the level of statistical significance was set at 0.05. Results: Of 88 workers, 33 were male and 55 were female. The level of satisfaction was high in terms of reliability (M.T. 3.97) and low in terms of system operation speed (M.T. 3.25) and quality of support (M.T. 3.30). Demographic characteristics were not associated with attitudes toward PC use and satisfaction with the information system, while participant satisfaction was associated with the contribution of PCs to quality health care delivery and increased staff efficiency and capabilities (p<0.01). The use of PCs appeared to contribute to the reduction of jobs positions (p=0.01) and to the increase of staff legal liability (p=0.01). Conclusions: Information Systems can contribute to the improvement of the working conditions of the EDs, to increase the efficiency, effectiveness and improvement of the quality care. The experience and training of the staff in the use of PCs plays a decisive role in the optimal utilization of the information systems.

An Efficient Primal-Dual Interior-Point Algorithm for Volt/VAR Optimization in Rectangular Voltage Coordinates

Security and reliability of electrical power supply has become indispensable to modern society, and the system operator is challenged to manage the increasingly complex modern power system in a manner that ensures the expected reliability and security of system operation. In this context, Volt/VAR optimization (VVO) plays a key role in the efficient delivery of power through the transmission system, contributing significantly to the security, reliability, quality and economy of system operation. This article presents the design and implementation of an efficient primal-dual interior-point algorithm for the solution of the VVO problem. The primal-dual interior-point method combines efficient constraint handling by means of logarithmic barrier functions, Lagrangian theory of optimization, and the Newton method to constitute one of the most efficient deterministic algorithms for large-scale nonlinear optimization. The developed algorithm also incorporates the efficient Newton-Raphson load flow computation, which ensures that the solution is feasible with respect to the power flow balance equations at each iteration of the VVO algorithm. Both the VVO and Newton-Raphson load flow problems are formulated in the rectangular coordinates of system voltages. This is a departure from most researchers, who make use of the polar formulation, and adds considerably to the efficiency of the developed algorithm. The efficiency and effectiveness of the developed algorithm has been demonstrated by means of case studies performed on the 6-bus and IEEE 14-bus, 30-bus and 118-bus test systems, which have been selected to analyse the computational efficiency and scalability of the algorithm as it is applied to systems of various sizes. The extensive analyses that have been conducted reveal the developed primal-dual interior-point algorithm’s effectiveness and efficiency, particularly in being able to successfully solve the VVO problem for systems of widely varying sizes without disproportionate increase in computational cost or deterioration in the quality of the results. The developed algorithm exhibits characteristics of fast convergence, high efficiency, and scalability to large-scale problems.

Risk-Averse Multiobjective Optimization for Integrated Electricity and Heating System: An Augment Epsilon-Constraint Approach

Uncertainties including demand and environmental factors would increase the operational risk of the energy supply networks. It significantly affects the technical and financial aspects of the integrated electricity and heating system (IEHS). This article presents a risk-averse multiobjective optimization strategy for short-term decision-making. The objective is to optimize the total cost and the technical dissatisfaction in a way that the economy of system operation and energy supply quality for the risk-averse scheme is guaranteed simultaneously. Based on the trapezoidal fuzzy membership function, the fuzzy constraint is constructed to quantify the technical dissatisfaction of the nodal voltage and supply temperature. Then, a multiobjective min–max–min problem is formulated to hedge the IEHS against risk imposed by the uncertain variables. Since the formulated two objectives compete with each other, a risk-averse multiobjective solution procedure based on the augmented epsilon-constraint algorithm is developed to recast the multiobjective problem into its equivalent single objective problem. And the accurate Pareto fronts under different risk levels are obtained with several iterations. Numerical case studies are conducted to evaluate the effectiveness and applicability of the proposed method. It provides benefits in the aspect of balancing the economy and energy supply quality under network constraints and uncertainties.

Regional Economic Forecasting Method Based on Recurrent Neural Network

Macroeconomic situation is the overall performance of the economic situation of a country and region. Making accurate forecasts of macroeconomic trends is of great significance for analyzing the success or failure of macroeconomic control policies, evaluating the quality of economic system operation, and correctly formulating future development planning strategies. The macroeconomic system is a nonlinear system, the environment is constantly changing, and additional disturbing factors directly affect the operation of the macroeconomic system, which has a great impact on the forecast results. The historical information required for macroeconomic modeling is unstable, unclear, and incomplete, which makes it very difficult to solve such problems with traditional forecasting methods. In response to the multivariate and nonlinear characteristics of macroeconomic forecasting, this paper proposes the application of artificial neural networks for forecasting. This paper introduces the recurrent neural network into the field of economic forecasting to solve the problems of the traditional BP (back propagation) neural network method. The experimental data are verified and the experimental results prove that the studied scheme based PSO-GRU improve the performance of economic forecasting.

Analysis of grid-connected operation characteristics and limit access capacity of offshore wind farms

Wind power is a relatively ripe renewable energy power generation technology, which has the superiority of large-scale development and utilization. Large-scale deep-sea wind farms are a significant direction for wind power development. With the continuous growth of the capacity of a single offshore wind farm, it is necessary to study the impact of grid connection of large-capacity offshore wind farms on the normal operation of the power grid, which can guarantee the safety and stability of the power grid. Based on the smooth working of the power system, it is meaningful to determining the limit access capacity of offshore wind farms for guiding offshore wind power planning. In this paper, an evaluation index system for the operation characteristics of offshore wind farms integrated into regional power grids is constructed, and based on that, the influence of offshore wind farms on the safety, stability, economy and power quality of regional power system operation is studied, and the grid-connected power limit of offshore wind farms is further calculated.

Rail surface defect detection based on improved Mask R-CNN

Rail surface defects are serious to the quality and safety of railroad system operation. Due to the diversity and randomness of rail defects form, the detection of rail surface defects is a challenging task. Therefore, this paper proposes a new surface defect detection network based on Mask R-CNN to detect rail defects. The detection network is designed with a new feature pyramid for multi-scale fusion; a new evaluation metric complete intersection over union (CIOU) is used in the region proposal network to overcome the limitations of intersection over union (IOU) in some special cases; in the training phase, both transfer learning and data augmentation are used to solve the problem of small defective datasets. The experimental evaluation shows that the model proposed in this paper achieves 98.70% mean average precision (MAP) on the proposed dataset and can locate the defect location more accurately.

Information and analytical support for making well-informed administrative decisions in civil protection system

Purpose. To substantiate the basic requirements for information and to develop a quality evaluation method of the civil protection information and analytical support system operation in public administration. Methodology. During the research, a set of general and special methods were used: regular observation and comparative analysis, content analysis, logical generalization, quantitative and qualitative comparison, scientific abstraction and systematization. Aquality evaluation method of the civil protection information and analytical support system operation was applied, which led to outlining the quality of information as sufficient, corresponding with situation changes, and significant information for appropriate decision-making by the head of authority under certain conditions. Findings. The basic information requirements are substantiated and its quality is defined as a set of characteristics (adequacy, completeness, responsiveness and utility) that outlines the degree of its suitability for achieving the goals of the information and analytical support system in civil protection. The quality evaluation method of the information and analytical support system operation in civil protection during emergencies was elaborated; it allows evaluating quantitatively the correspondence of the quality of system operation with the requirements stipulating usage of the integrated indicator the extent of information and analytical support for the authority concerning its activity arrangement in emergencies. The obtained results of quality evaluation of the civil protection information and analytical support system operation were proposed to determine the rational method of its operation during the decision-making process by the head of authority under certain conditions. Originality. The evaluation criterion was defined: achieving the condition when the extent of implementing the information and analytical support is higher or equal to the required one and provides for further evaluation of the operation methods of the system. Practical value. It is proved that attaining the criterion of information and analytical support system operation quality in civil protection is a connecting link to the methodological approach. Therefore, there is a possibility to determine a rational method of the system operation using the hierarchical model of alternative method comparison taking into consideration analytic hierarchy process (AHP), which ensures the head of authority to perform the assigned tasks qualitatively, completely and timely.

IoT-Based Hybrid Renewable Energy System for Smart Campus

There is a growing interest in increasing the penetration rate of renewable energy systems due to the drawbacks associated with the use of fossil fuels. However, the grid integration of renewable energy systems represents many challenging tasks for system operation, stability, reliability, and power quality. Small hybrid renewable energy systems (HRES) are small-scale power systems consisting of energy sources and storage units to manage and optimize energy production and consumption. Appropriate real-time monitoring of HRES plays an essential role in providing accurate information to enable the system operator to evaluate the overall performance and identify any abnormal conditions. This work proposes an internet of things (IoT) based architecture for HRES, consisting of a wind turbine, a photovoltaic system, a battery storage system, and a diesel generator. The proposed architecture is divided into four layers: namely power, data acquisition, communication network, and application layers. Due to various communication technologies and the missing of a standard communication model for HRES, this work, also, defines communication models for HRES based on the IEC 61850 standard. The monitoring parameters are classified into different categories, including electrical, status, and environmental information. The network modeling and simulation of a university campus is considered as a case study, and critical parameters, such as network topology, link capacity, and latency, are investigated and discussed.

Assessment of the shovel-truck system operation quality at open-pit mines in Kuzbass

Assessment of the shovel-truck system (STS) operation quality is based on the well-known method of non-expert assessment of the quality of mining machines. The methodology is based on the fundamental principles of qualimetry and allows making the assessment of functionally homogeneous machines of different sizes, types and designs based on the functional criterion of the machine, which determines its main purpose. In this work, the quality assessment is made not for a single machine, but for a set of machines, taking into account their interaction. Assessment of the STS operation quality allows us to create a basis for the selection of priority areas for its improvement. The work uses methods of mathematical modeling, data collection and processing, statistics, analysis and synthesis. A comprehensive quality assessment makes it possible to predict the level and select priority areas for improving existing STSs or STSs being projected.

Computational procedure for preparing the technical conditions for stowage and securing cargo in rail cars and containers

The transition of the railway industry from information management systems to systems with full management can be achieved by combining automated information systems integrated into production processes in the railway network. Russian Railways OAO acts as a driver for the development of modern technologies in the transport sector, aiming to increase efficiency in organizing the transportation process. Monitoring changes in customer needs, as well as focusing on increasing the value of services and products for consumers, including service quality improvement by digitalizing individual operations related to the cargo handling during loading, is becoming increasingly important. The introduction of the developed automated system for the preparation of technical specifications for the stowage and securing of cargo in rail cars and containers will increase production system organization quality in railway transport, as it will eliminate the incompetence, negligence and irresponsibility of workers associated with the handling, stowage and securing, reduce the time for preparing technical documentation, and improve the transport system operation quality. To achieve the stated goal, based on the studies, the author developed a computational decision-making procedure for the stowage and securing of cargo in the rail car, taking into account a possible two-coordinate shift. The procedure allows employees responsible for accepting cargo for transportation to assess the quality of the cargo securing according to the criterion of permissible shift at the initial stage of the transportation process. The developed automated system has many positive aspects. The security of the system significantly increases, the risk of errors is reduced, and the influence of the human factor is minimized. The complexity of the process of compiling a sketch of the stowage and securing of the cargo in the rail car loaded in accordance with the Technical Specifications is reduced. Most of the work is done by automated software, the cargo shipper has more time to control the loading process; time limits of various works and projects generally decrease.

Fault Isolation for A Complex Decentralized Waste Water Treatment Facility

SummaryDecentralized waste water treatment facilities monitor many features that are complexly related. The ability to detect the onset of a fault and to identify variables accurately that have shifted because of the fault are vital to maintaining proper system operation and high quality produced water. Various multivariate methods have been proposed to perform fault detection and isolation, but the methods require data to be independent and identically distributed when the process is in control, and most require a distributional assumption. We propose a distribution-free retrospective change-point-detection method for auto-correlated and non-stationary multivariate processes. We detrend the data by using observations from an in-control time period to account for expected changes due to external or user-controlled factors. Next, we perform the fused lasso, which penalizes differences in consecutive observations, to detect faults and to identify shifted variables. To account for auto-correlation, the regularization parameter is chosen by using an estimated effective sample size in the extended Bayesian information criterion. We demonstrate the performance of our method compared with a competitor in simulation. Finally, we apply our method to waste water treatment facility data with a known fault, and the variables identified by our proposed method are consistent with the operators’ diagnosis of the fault's cause.

Optimization techniques applied for optimal planning and integration of renewable energy sources based on distributed generation: Recent trends

Numerous potential advantages to the requirements and effectiveness of the supplied electricity can be accomplished by the installation of distributed generation units. In order to take full advantage of these benefits, it is essential to position the Distributed Generation (DG) units in appropriate locations. Otherwise, their installation may have an adverse effect on the quality of energy and system operation. Several optimization techniques have been created over the years to optimize distributed generation integration. Optimization techniques are therefore constantly changing and have been the main attention of many fresh types of research lately. This article evaluates cutting-edge techniques of optimizing the issue of positioning and sizing distributed generation units from renewable energy sources based on recent papers that have already been applied to distribution system optimization. Furthermore, this article pointed out the environmental, economic, technological and regulatory drivers that lead to a rapid interest in the DG system based on renewable sources. A summary of popular meta-heuristic optimization tools discussed in table form with merits and demerits to increase fresh prospective paths to multi-approach that have not yet been studied.

Priorities for Russian Education System Reformation

In the modern conditions of the knowledge economy, when professional knowledge becomes obsolete quickly, the increased attention of the state to the sphere of education is noted. Accordingly, it is necessary to revise the approaches to the management of education sphere in the long term. The prerequisites for education sphere reformation in Russia were the transformational processes of the social reorganization of the Russian state. An effective organization of the education system in modern conditions is the basis for an economic growth achievement. Therefore, it is necessary to apply new principles for the training of professional personnel, taking into account the needs of the emerging innovative market economy. The sphere of education as one of the most important aspects of society life is in the joint responsibility of the federation and its subjects. At the federal level, they determine the vector and the main priorities for the development of the state educational system, at the regional level they develop the main ideas of federal policy taking into account regional peculiarities, needs and opportunities. The standard of living and well-being of Russian society, its general economic and social development, the level and the pace of scientific and technical achievements are determined by the level and the quality of the state educational system operation. Besides, the structure and the content of the education system itself, its competitiveness in the world arena, the compliance with international quality standards and requirements, determine the level of innovative development of the country economy, the intensification of economic development, a favorable social atmosphere and the national security at the international, national and regional levels .

Cascading Collapse of a Large-Scale Mixed Source Microgrid Caused by Fast-Acting Inverter-Based Distributed Energy Resources

Power electronic converter-interfaced distributed energy resources (DERs) are being increasingly deployed for achieving high energy efficiency, power quality, and flexibility of power system operation and controls. They facilitate access to a wide array of energy sources, including renewables, fuel cells, microturbines, variable speed engine-generator sets, etc. However, recent tests carried out at the Consortium for Electric Reliability Technology Solutions (CERTS) Microgrid have indicated that their deployment in the mixed source microgrid can cause a cascading collapse during extreme events. To investigate the problem, simulation models of two types of DERs are developed in PSCAD/EMTDC software and validated with the experimental test results. Furthermore, the validated models are used to study a cascading collapse problem in a large-scale mixed source microgrid on the benchmark IEEE 33-bus test system. In this paper, three alternative techniques are evaluated to prevent the cascading collapse in the large-scale microgrid caused by fast-acting inverter-based DERs.

Multi-threshold control by a single-server queuing model with a service rate depending on the amount of harvested energy

We consider a single-server queuing model with energy harvesting. Customers and energy units arrive in the marked Markovian arrival flow. Buffers for customers and energy are finite. There are several service modes distinguished by the number of required units of energy, the service rate and the quality of service. The choice of the service mode for the next customer depends on the current number of energy units in the system. The quality of system operation is assumed to be defined by a customer’s loss probability. Loss can occur due to buffer overflow, low-quality service or impatience during the waiting time. The control strategy is of a multi-threshold type with thresholds defined by the amount of available energy. Under the fixed values of the thresholds, the behaviour of the system is described by a multi-dimensional Markov chain. The generator of this chain is derived. The main performance measures are calculated. The distribution of the waiting time is derived in explicit form. A numerical study of the model via extensive experiments that provide insight into the quantitative behaviour of the system is presented.

Optimisation of changes of the operation quality of the transportation system in the fuzzy quality states space

The main objective of the management and control of the transportation system operation is to achieve the highest quality of its operation tasks execution. However, because of the system complexity the accurate determination of the system operation quality is very complicated. To optimize the efficiency of the activities performed to increase the operation quality, it was expressed in the quality states space. In the space the subspaces of the inadvisable, advisable, limited, acceptable and desired quality of operation were defined and the momentary quality of the system operation was expressed in form of the point. Taking into account the subjective character of the survey results and their linguistic inaccuracy the space was transformed into the fuzzy quality states space. Subsequently, the distance between the fuzzy set of the momentary system operation quality and the border of the desired quality subspace was defined. This way, for the quality states not belonging to the desired quality subspace, the minimal changes of the system features required to move this state to the subspace were calculated. The presented in the paper method allows optimizing the efficiency of the activities performed to increase the operation quality of the transportation system.

МЕТОДИКА АГРЕГИРОВАННОЙ ОЦЕНКИ СОСТОЯНИЯ ПРОИЗВОДСТВЕННО-ЭКОНОМИЧЕСКОЙ СИСТЕМЫ НА ПРИМЕРЕ СТАНЦИИ УЛАН-БАТОРСКОЙ ЖЕЛЕЗНОЙ ДОРОГИ

The PURPOSE of this work is to discuss the methods of production-economic system operation quality assessment on example of one of the stations of the Ulan Bator railway. METHODS. The methodology is based on the developed ontology of the station transformed into a production knowledge base of a special type. Every product has truth value specified by experts on a scale [0,1]. It is considered as a relative value component of the system. The assessment procedure is represented in the form of a dialogue with the expert system into which functional element state estimations are introduced. As a result an aggregate assessment is derived in the form of a number within the interval [0,1] that measures the truth value of the assertion on system functionality. RESULTS. The study has resulted in the development of fuzzy inference-based aggregate estimation of a production and economic system involving the technology of expert systems. CONCLUSIONS. The methodology can be applied for estimation aggregation in various object domains.

Synthesis of robust controller with an internal model for objects without self-alignment

We examined the synthesis of an automated control system, which ensures the required operation quality of objects without self-alignment. As a result of employing as an optimality criterion a minimum of the Н∞-norm of a transfer function of the closed system, we obtained structures of the controllers with an internal model for the objects without self-alignment of first and second order with a delay. It was found that such controllers had one adjustable parameter, which is a compromise between the quality and the robustness of the closed system. By changing this parameter, it is possible to receive different quantitative indicators of the system operation quality. We derived direct and unambiguous dependences of key quality indicators of the system on the parameter of Н∞-controller. Results of these dependences are entered into a database. Based on these data, we created a program that determines such settings of the controller, which provide the required quality of a control system. Therefore, it is possible to ensure with a guarantee maintaining the assigned quality indicator, which is convenient for practice, or achieve the desired combination of several quality indicators that is executed over the entire range of system operation, thereby ensuring its robustness.