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.

scholarly journals Knowledge base formation for automation of dispatch control over power systems of the mining and metallurgical complex

2021 ◽  
pp. 103-109
Author(s):  
V.S Morkun ◽  
I.A Kotov
Keyword(s):  
Decision Support ◽  
Power Systems ◽  
Power System ◽  
Knowledge Base ◽  
Economic Effect ◽  
Online Control ◽  
Knowledge Bases ◽  
Suggested Approach ◽  
Controlling Actions ◽  
Emergency Mode

Purpose. The research is aimed at developing and introducing methods of knowledge extraction concerning online control over power systems under emergency modes and building smart complexes of automatizing managerial decision making based on incorporated ontological knowledge bases. Methodology. The authors use the calculated planned experiment method applied to building sensitivity matrices of controlled parameters of power systems in sensor points to controlled factors and introduction of sensitivity coefficients into knowledge bases. Findings. The research suggests methods for obtaining and building a knowledgebase of professional ontologies for online control over power system modes. The problem of calculating sensitivity of controlled parameters to controlling actions is solved. Calculation results for the emergency mode enable building impact functions and determining sensitivity matrix coefficients. The smart system knowledgebase is built to provide decision support for dispatch control over power system modes under standard and emergency conditions. There are obtained sets of mode data used as knowledgebase components enabling efficient assessment of the emergency mode rate and its dispatch correction. Besides calculation parameters of intensity of controlling actions, the knowledgebase also comprises linguistic concepts, facts and rules of instructive dispatch materials. A knowledge base has been built on the basis of a subset of the linguistic corpus of concepts for the professional area of emergency response in the power system. Originality. For the first time, there is suggested an approach to incorporating various linguistic knowledge forms represented by a single ontological model and numerical parameters of sensitivity of the power system mode to controlling actions into an integrated knowledgebase, which enables building effective smart systems of dispatch decision support and implementing them into the operating automatized dispatch control system. Practical value. The ontological knowledgebase of online dispatch control is built that enables realizing a software complex of a decision support system aimed at automatizing online dispatch control over standard and emergency modes of power systems. Application of the suggested approach to building the knowledgebase and its use with online dispatch personnels decision support enhance reliability and increase maximum accessible time of personnels non-stop work by 1.5 years with absolute accident elimination, thus providing a significant economic effect.

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

scholarly journals A Decision Support System for Public Funding of Experimental Development in Energy Research

Energies ◽  
2018 ◽  
Vol 11 (6) ◽  
pp. 1357 ◽  
Author(s):  
Simon Hirzel ◽  
Tim Hettesheimer ◽  
Peter Viebahn ◽  
Manfred Fischedick
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Large Scale ◽  
Public Funding ◽  
Evaluation Process ◽  
Decision Makers ◽  
Market Failures ◽  
Energy Research ◽  
Experimental Development

New energy technologies may fail to make the transition to the market once research funding has ended due to a lack of private engagement to conclude their development. Extending public funding to cover such experimental developments could be one way to improve this transition. However, identifying promising research and development (R&D) proposals for this purpose is a difficult task for the following reasons: Close-to-market implementations regularly require substantial resources while public budgets are limited; the allocation of public funds needs to be fair, open, and documented; the evaluation is complex and subject to public sector regulations for public engagement in R&D funding. This calls for a rigorous evaluation process. This paper proposes an operational three-staged decision support system (DSS) to assist decision-makers in public funding institutions in the ex-ante evaluation of R&D proposals for large-scale close-to-market projects in energy research. The system was developed based on a review of literature and related approaches from practice combined with a series of workshops with practitioners from German public funding institutions. The results confirm that the decision-making process is a complex one that is not limited to simply scoring R&D proposals. Decision-makers also have to deal with various additional issues such as determining the state of technological development, verifying market failures or considering existing funding portfolios. The DSS that is suggested in this paper is unique in the sense that it goes beyond mere multi-criteria aggregation procedures and addresses these issues as well to help guide decision-makers in public institutions through the evaluation process.

Decision support system for corrective maintenance in large-scale photovoltaic systems

2021 ◽  
Author(s):  
Andreas Livera ◽  
Marios Theristis ◽  
Alexios Charalambous ◽  
Joshua S. Stein ◽  
George E. Georghiou
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Large Scale ◽  
Photovoltaic Systems ◽  
Corrective Maintenance

scholarly journals Intelligent decision support method in a typical situation

2021 ◽  
Vol 11 (1) ◽  
pp. 126-136
Author(s):  
V.V. Antonov ◽  
◽  
K.A. Konev
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Knowledge Base ◽  
Business Process ◽  
Support System ◽  
System Integration ◽  
General Structure ◽  
Typical Situation ◽  
Ontological Model ◽  
Decision Support Method

The article discusses a decision support method using a knowledge base. The relevance of the study of issues related to decision-making in typical situations is shown. In order to increase the effectiveness of management activities, the is-sues of system integration of the regulatory framework, ontological model and knowledge base of the intelligent sub-system of decision support within the framework of the business process are considered. In support of the proposed method, a model has been formed for replenishing the knowledge base both at the structural and analytical levels, which demonstrates the connection between the most important elements of the system: the ontological model, the knowledge base and the normative subsystem. An example of using the proposed scheme is shown. To demonstrate the model of functioning of the decision support system, an algorithm for replenishing the knowledge base is proposed and described. As a conceptual basis for the formal description of the model, operations for working with knowledge are described in the set-theoretic aspect. The principles of adaptation of the ontological model as an information object for linking with the knowledge base are considered. The conceptual diagram of the general structure of the ontological model for making decisions within the framework of the business process as a set of interrelated concepts is proposed and demonstrated. An information model of a specialized database has been developed and presented, serving as a technical basis for building a knowledge base of a decision support system in a typical situation, its main structural el-ements, the principles of their interrelation and an approach to ensuring the consistency of its internal structure are de-scribed.

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