Operation Of Individual Systems Research Articles

СОВЕРШЕНСТВОВАНИЕ ПОДХОДОВ К ДИАГНОСТИРОВАНИЮ ДЛЯ УПРАВЛЕНИЯ НАДЕЖНОСТЬЮ СЕЛЬСКОХОЗЯЙСТВЕННОЙ ТЕХНИКИ

Reducing the cost of the life cycle of machines and aggregates, optimizing the cost of operation and timely maintenance, carrying out work in the required agrotechnical terms are indicators of the effectiveness of managing the reliability of agricultural machinery. This aspect is significantly influenced by the perfection of approaches to maintenance and diagnostics, taking into account the use of digital monitoring tools for resource-determining units and assemblies. Effective implementation of reliability management minimizes costs from the consequences of failures of II and III complexity groups, reduces the cost of production and corrects the time of service work. Therefore, the improvement of approaches for routine maintenance, including diagnostics, is an urgent issue to improve the efficiency of domestic equipment in operation. (Research Purpose) The research purpose is analyzing previously applied approaches to assessing the technical condition for managing the reliability of agricultural machinery and developing experimental samples of digital diagnostic tools to improve the assessment of the technical condition. (Materials and methods) Reviewed the process of creating experimental digital diagnostic tools for improving approaches to reliability management, taking into account the recommendations of the regulatory and technical documentation of the departmental project «Digital Agriculture» of the Ministry of Agriculture of the Russian Federation. (Results and discussion) It was shown that the use of previously developed methods and means of diagnosing agricultural machinery significantly increased the efficiency of its operation. It was substantiated that now it is necessary to take into account methodological experience, which allows to increase the level of diagnostics of operating equipment on the basis of new multifunctional research tools. We have developed experimental digital means of monitoring the technical condition, which provide control over compliance with the rules of operation of individual systems and units. (Conclusions) It was revealed that digital diagnostic and monitoring tools could reduce the cost of the life cycle of equipment, optimize operating costs, and ensure maintenance.

Study of the Impact оf strategic Outsourcing оn the Interacting Market in Entrepreneurial Training and Human Capital Development

Due to the rapid development of digital technology, the structure of future jobs is becoming increasingly complex, and university graduates need to acquire the right combination of skills to succeed in a rapidly changing world. The need for continuous replenishment and updating of professional knowledge is determined by the pace of scientific and technological progress, the transition to the information stage of the development of society, and the widespread use of innovative technologies. There are prerequisites for the formation and development of the category of “strategic outsourcing”. Unlike the services of the service, which have a one-time, episodic nature, strategic outsourcing is usually transferred to the functions of professional support for the uninterrupted operation of individual systems and infrastructure based on a long-term contract. Strategic outsourcing allows not only to restructure business processes radically but also significantly improve opportunities and prospects. The purpose of this study is to study the concept of outsourcing in entrepreneurial training and the development of human capital.

Economic-environmental equilibrium-based bi-level dispatch strategy towards integrated electricity and natural gas systems

Even though economic dispatch of integrated electricity and natural gas systems using optimization techniques has been widely conducted, a cooperative distributed and multi-objective optimization is still needed for meeting multi-energy demands from both conventional and renewable energy resources. In this study, an original bi-level economic-environmental equilibrium model is proposed to optimize a dispatch strategy for an integrated system, which include combined cooling, heating, and power and power to gas technologies. By optimizing cooperative distributed decisions, the system attempts to provide heat/cooling, power and natural gas loads. An equilibrium consideration of economic energy supply and environmental carbon emission control is achieved using a multi-objective optimization in the model. To reflect interactions of individual system operators in a cooperative distributed manner, a bi-level optimization is applied to address the respective decisions and objective functions. Subsequently, an interactive solution approach based on Non-dominated Sorting Genetic Algorithm-II and genetic algorithm is specifically designed to solve the model by updating individual decisions interactively and iteratively, and the optimality of an integrated solution lies in the capability to coordinate two system operators for a reliable, economic and environmental energy supply. Performance of the dispatch strategy is validated for a case with various system configurations. The obtained results showed that multi-energy needs are met, economic-environmental trade-offs achieved and hierarchical interactions addressed. Proper managerial suggestions are also provided based on comparison analyses. The proposed method is therefore worthy of being popularized in integrated systems.

IoT visualization of Smart Factory for Additive Manufacturing System (ISFAMS) with visual inspection and material handling processes

The challenges in a manufacturing system are lack of timely, accurate, and lack of information to featured product prediction, shop floor resources, product flow, product inspection, product status to customer, product delivery status and factory adaption for customized product. The proposed idea is to design IoT visualization based Smart Factory for Additive Manufacturing System (ISFAMS) that creates a way towards progressively from traditional automation to a fully connected mass customization and flexible cyber-physical system. The ISFAMS utilize a consistent stream of information from associated tasks and creating frameworks to learn and adjust factory productions to new requests from the customer. The system utilizes the Industrial Controller to control the operation of individual systems and sequence of product flow in the Smart Factory setup. The wireless sensor network acquires real-time manufacturing information and information is stored, accessed and visualized using cloud computing. The vision system and automated platform enable the inspection of products shape and dimensions based on the machine learning approach and to transfer the product from section to section and separate the product for packaging section. This digitization of manufacturing system increases flexibility, reliability, smart sensing and control, resource wastage, easy access to manufacturing information and logistics management.

A Fixed-Point Based Distributed Method for Energy Flow Calculation in Multi-Energy Systems

Energy flow calculation (EFC) plays an important role in steady-state analysis of multi-energy systems (MESs). However, the independent management of sub-energy systems (subsystems) poses a considerable challenge to solve the high-order nonlinear energy flow model due to the limited information exchange between these subsystems. In this article, a fixed-point based distributed method is proposed for EFC in an electricity-gas-heating system. Firstly, the mathematical modeling of each subsystem with coupling units is introduced. Then, two information exchange structures among subsystems are presented as sequential and parallel structures. Based on the fixed-point theorem, novel distributed sequential and parallel methods for EFC are proposed to calculate energy flow distribution in MESs. In our proposed method, the EFC in subsystems is implemented by the individual system operators, with limited information exchange between subsystems. Therefore, the information privacy of subsystems can be preserved in this solution process. Moreover, the convergence of the proposed method is guaranteed, and the sufficient conditions for the convergence are presented. Lastly, simulations on a MES demonstrate the effectiveness of the proposed method and the quantified superiority over the existing methods in computation time, accuracy and reliability.

Distributed Design of Local Controllers for Transient Stabilization in Power Grids

In this paper, we develop a distributed method for designing local controllers that perform transient stabilization of dynamic response for deflections caused by contingencies in a large power system where multiple independent system operators exist and manage their corresponding generators. The system models associated with individual system operators should be private and be unavailable for deciding control policies of other system operators. We formulate the controller design problem where each controller is designed using its corresponding local system model and they achieve a desired local transient response performance. Our proposed method based on hierarchical state-space expansion enables us to solve the controller design problem and the resulting system satisfies the requirements. Through numerical simulations for the IEEJ EAST 10-machine power system, the effectiveness of our proposed method is verified.

Evaluating the role of risk networks in risk identification, classification and emergence

Modern society heavily relies on strongly connected, socio-technical systems. As a result, distinct risks threatening the operation of individual systems can no longer be treated in isolation. Consequently, risk experts are actively seeking for ways to relax the risk independence assumption that undermines typical risk management models. Prominent work has advocated the use of risk networks as a way forward. Yet, the inevitable biases introduced during the generation of these survey-based risk networks limit our ability to examine their topology, and in turn challenge the utility of the very notion of a risk network. To alleviate these concerns, we proposed an alternative methodology for generating weighted risk networks. We subsequently applied this methodology to an empirical dataset of financial data. This paper reports our findings on the study of the topology of the resulting risk network. We observed a modular topology, and reasoned on its use as a robust risk classification framework. Using these modules, we highlight a tendency of specialization during the risk identification process, with some firms being solely focused on a subset of the available risk classes. Finally, we considered the independent and systemic impact of some risks and attributed possible mismatches to their emerging nature.

Security of interdependent and identical networked control systems

This article studies security decisions of identical plant-controller systems, when their security is interdependent due to network induced risks. Each plant is modeled by a discrete-time stochastic linear system, with the systems controlled over a shared communication network. We formulate the problem of security choices of the individual system operators (also called players) as a non-cooperative game. We consider a two-stage game, in which on the first stage the players decide whether to invest in security or not; and on the second stage, they apply control inputs to minimize the average operational costs. We characterize the equilibria of the game, which includes the determination of the individually optimal security levels. Next, we solve the problem of finding the socially optimal security levels. The presence of interdependent security causes a negative externality, and the individual players tend to under invest in security relative to the social optimum. This leads to a gap between the individual and the socially optimal security levels for a wide range of security costs. From our results, regulatory impositions to incentivize higher security investments are desirable.

Optimal sizing of residential SOFC cogeneration system for power interchange operation in housing complex from energy-saving viewpoint

A power interchange operation, in which electric power generated by multiple residential solid oxide fuel cell cogeneration systems (R-FCGSs) is shared among residences in a housing complex with no reverse power flow to a commercial electric power system, has a high energy-saving effect as compared with a stand-alone operation of individual systems. To further improve its energy-saving effect, the optimal sizing of the R-FCGS for this power interchange operation is discussed from the energy-saving viewpoint by conducting optimal operational planning based on mixed-integer linear programming. The energy-saving effect of the power interchange operation is analyzed for 14 different scales of the R-FCGSs with the rated electric power output ranging from 0.2 to 1.5 kW per 0.1 kW. The analysis for a housing complex with 20 residences located in Japan reveals that the power interchange operation has an advantage over the stand-alone operation in terms of energy saving for any scale of the R-FCGS investigated in this study. Furthermore, it is found that the 0.6-kW R-FCGS is the optimal scale for the power interchange operation in terms of the energy saving and saves the annual primary energy consumption of 17% as compared with the conventional energy supply with no R-FCGS.

PETROBRAS STARTS PLATFORM BIDDING

Even though economic dispatch of integrated electricity and natural gas systems using optimization techniques has been widely conducted, a cooperative distributed and multi-objective optimization is still needed for meeting multi-energy demands from both conventional and renewable energy resources. In this study, an original bi-level economic-environmental equilibrium model is proposed to optimize a dispatch strategy for an integrated system, which include combined cooling, heating, and power and power to gas technologies. By optimizing cooperative distributed decisions, the system attempts to provide heat/cooling, power and natural gas loads. An equilibrium consideration of economic energy supply and environmental carbon emission control is achieved using a multi-objective optimization in the model. To reflect interactions of individual system operators in a cooperative distributed manner, a bi-level optimization is applied to address the respective decisions and objective functions. Subsequently, an interactive solution approach based on Non-dominated Sorting Genetic Algorithm-II and genetic algorithm is specifically designed to solve the model by updating individual decisions interactively and iteratively, and the optimality of an integrated solution lies in the capability to coordinate two system operators for a reliable, economic and environmental energy supply. Performance of the dispatch strategy is validated for a case with various system configurations. The obtained results showed that multi-energy needs are met, economic-environmental trade-offs achieved and hierarchical interactions addressed. Proper managerial suggestions are also provided based on comparison analyses. The proposed method is therefore worthy of being popularized in integrated systems.