scholarly journals Development of software control tools for power systems of mining and metallurgical regions

2021 ◽  
Vol 280 ◽  
pp. 05002
Author(s):  
Vladimir Morkun ◽  
Igor Kotov
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Power Systems ◽  
Support System ◽  
New Formalism ◽  
Smart Systems ◽  
Algorithm Visualization ◽  
New Interpretation ◽  
Functioning Mechanism ◽  
Outer Environment

There are presented results of developing a conceptual trigger chart of the functioning mechanism of the decision support system. The suggested model of visualizing algorithms as a trigger net of states of the computer decision support system provides for interaction of power objects of mining and metallurgical complexes and regions. The authors introduce new interpretation of components of the network trigger model. The model is interactively connected with both the user-operator’s actions and states of power system components. With that, the state of the automatic model is associated with realizing a set of metarules to control the logic output. The authors elaborate a new formalism of representing algorithms of controlling knowledgebases interacting with the outer environment which aggregates primitives of conditions, triggers and transactions of operations and greatly generalizes standard languages of algorithm visualization. It enhances elaboration of standardized smart systems interacting with the external environment. This allows description of functioning algorithms of knowledgebases and the event-driven output to ensure development of reliable standardized smart systems interacting with control objects of power systems in mining and metallurgical regions.

scholarly journals PRODUCTION RULE ONTOLOGY OF AUTOMATIZED SMART EMERGENCY DISPATCHING SUPPORT OF THE POWER SYSTEM

2021 ◽  
Vol 4 (2) ◽  
pp. 168-184
Author(s):  
Vladimir S. Morkun ◽  
Ihor A. Kotov ◽  
Oleksandra Y. Serdiuk ◽  
Iryna A. Haponenko
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Power Systems ◽  
Power System ◽  
Support System ◽  
External Environment ◽  
Software Complex ◽  
Smart Systems ◽  
Algorithm Visualization ◽  
New Interpretation

The research deals with improving methods and systems of control over power systems based on intellectualization of dispatch decision support. There are results of developing a principal trigger scheme of the decision support system algorithm. The proposed model of algorithm visualization in the form of a trigger state network of the computer system provides interaction with power objects of mining and metallurgical complexes and regions. A new interpretation of components of the network trigger model is introduced. The model is interactively related to both user-operator actions and states of power system components. With that, the state of the automata model is associated with fulfillment a set of metarules to control the logical inference. There are new forms of presenting algorithms controlling knowledgebases that interact with the external environment and aggregate primitives of states, triggers and transactions of operations and generalize standard visualization languages of algorithms are proposed. This allows unification of smart systems interacting with the external environment. The authors develop models for representing knowledgebase processing algorithms interacting with power objects that combine states, triggers and transaction operations and generalize standard visualization languages of algorithms. This enables description of functioning database algorithms and their event model, which provides a reliable unification of smart systems interacting with control objects of mining and metallurgical power systems. The research solves the problem of building a knowledgebase and a software complex of the dispatch decision support system based on the data of computational experiments on the power system scheme. The research results indicate practical effectiveness of the proposed approaches and designed models

Software and Hardware Decision Support System for Operators of Electrical Power Systems

2021 ◽  
pp. 1-1
Author(s):  
Nikolay Ruban ◽  
Aleksey Suvorov ◽  
Mikhail Andreev ◽  
Ruslan Ufa ◽  
Alisher Askarov ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Power Systems ◽  
Support System ◽  
Electrical Power ◽  
Electrical Power Systems ◽  
Software And Hardware

Ambient-Intelligent Decision Support System (Am-IDSS) for Smart Manufacturing

2021 ◽  
pp. 2338-2351
Author(s):  
Marzieh Khakifirooz ◽  
Mahdi Fathi ◽  
Yiannis Ampatzidis ◽  
Panos M. Pardalos
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Smart Manufacturing ◽  
Sensors And Actuators ◽  
Smart Systems ◽  
Intelligent Decision Support System ◽  
Ambient Environment ◽  
Intelligent Decision ◽  
Intelligent Decision Support

Ambient Intelligence (AmI) is built using sensors and actuators connected through real-time networks for smart systems. The data and signals captured from sensors are ambiguous for both human and machine. Artificial Intelligence (AI) is merged into an ambient environment to translate data and signals into a language understandable by human users and to transform an operational setting from machine-centered to human-centered. However, the implementation of AI technology into an ambient environment requires quantitative modeling approaches to emphasize system requirements. This article aims to give a clear snapshot of the design and structure of advanced AmI technology for an AmI-based decision support system (Am-IDSS). The proposed approach explores the basic principles of an Am-IDSS structure concerning the role of the Internet, data, Industrial robotics, and other AI technologies for smart manufacturing. To supplement this research, the study is concluded by proposing managerial suggestions for systems development and observations about future trends in implementing Am-IDSS.

Ambient-Intelligent Decision Support System (Am-IDSS) for Smart Manufacturing

2021 ◽  
pp. 864-879
Author(s):  
Marzieh Khakifirooz ◽  
Mahdi Fathi ◽  
Yiannis Ampatzidis ◽  
Panos M. Pardalos
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Smart Manufacturing ◽  
Sensors And Actuators ◽  
Smart Systems ◽  
Intelligent Decision Support System ◽  
Ambient Environment ◽  
Intelligent Decision ◽  
Intelligent Decision Support

Ambient Intelligence (AmI) is built using sensors and actuators connected through real-time networks for smart systems. The data and signals captured from sensors are ambiguous for both human and machine. Artificial Intelligence (AI) is merged into an ambient environment to translate data and signals into a language understandable by human users and to transform an operational setting from machine-centered to human-centered. However, the implementation of AI technology into an ambient environment requires quantitative modeling approaches to emphasize system requirements. This article aims to give a clear snapshot of the design and structure of advanced AmI technology for an AmI-based decision support system (Am-IDSS). The proposed approach explores the basic principles of an Am-IDSS structure concerning the role of the Internet, data, Industrial robotics, and other AI technologies for smart manufacturing. To supplement this research, the study is concluded by proposing managerial suggestions for systems development and observations about future trends in implementing Am-IDSS.

scholarly journals A Decision Support System Tool to Manage the Flexibility in Renewable Energy-Based Power Systems

Energies ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 153 ◽  
Author(s):  
Marco Badami ◽  
Gabriele Fambri ◽  
Salvatore Mancò ◽  
Mariapia Martino ◽  
Ioannis G. Damousis ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Decision Support ◽  
Decision Support System ◽  
Power Systems ◽  
Support System ◽  
Renewable Energy Sources ◽  
Economic Benefits ◽  
Energy Storage And Conversion ◽  
Specific Reference ◽  
Power To Gas

Renewable Energy Sources (RES) have taken on an increasingly important role in the energy mix in the last few years, and it has been forecasted that this trend will continue in the future. The energy production from these sources is not dispatchable, and the increasing penetration of RES in energy mixes may therefore lead to a progressive loss of generation control and predictability. It has become clear that, to reach higher RES penetration levels, it is essential to increase power system flexibility in order to ensure stable operations are maintained. An ICT (Information and Communication Technology) tool that may be used to manage and optimize the flexibility offered by energy storage and conversion systems is described in this paper with specific reference to the Decision Support System (DSS) developed within the H2020 PLANET (PLAnning and operational tools for optimizing energy flows and synergies between energy NETworks) project. The paper focuses on how the PLANET DSS tool evaluates, manages, and dispatches the flexibility of Power to Gas/Heat (P2X) technologies. Moreover, the tool has been used to analyze a realistic case in order to show how the PLANET DSS tool could be used to evaluate the energy and economic benefits of taking advantage of the flexibility of P2X technologies.

scholarly journals Intellectualization of Emergency Control of Power Systems on the Basis of Incorporated Ontologies of Knowledge-Bases

2019 ◽  
Vol 13 (2) ◽  
pp. 86-94
Author(s):  
Vladimir Morkun ◽  
Ihor Kotov
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Power Systems ◽  
Power System ◽  
Knowledge Base ◽  
Support System ◽  
Large Scale ◽  
Knowledge Bases ◽  
Experiment Planning ◽  
Control Actions

Abstract The research deals with improvement of methods and systems of controlling integrated power systems (IPSs) on the basis of intellectualization of decision-making support. Complex analysis of large-scale accidents at power facilities is performed, and their causes and damages are determined. There is substantiated topicality of building condition knowledge-bases as the foundation for developing decision-support systems in power engineering. The top priorities of the research include developing methods of building a knowledge base based on intensity models of control actions influencing the parameters of power system conditions and introducing the smart system into information contours of the automated dispatch control system (ADCS), as well as assessing practical results of the research. To achieve these goals, the authors apply methods of experiment planning, artificial intelligence, knowledge presentation, mathematical simulation, and mathematical statistics as well as methods of power systems studying. The basic research results include regression models of a power system sensitivity to control actions, methods of building a knowledge base based on the models of sensitivity matrices, a structure of the smart decision-support system, a scheme of introducing the decision-support system into the operating ADCS environment. The problem of building a knowledge base of the dispatch decision-support system on the basis of empirical data resulted from calculating experiments on the system diagram has been solved. The research specifies practical efficiency of the suggested approaches and developed models.

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