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 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.

Techniques for the Identification of Critical Nodes Leading to Voltage Collapse in a Power System

2018 ◽  
Vol 19 (2) ◽  
Author(s):  
Isaiah Adebayo ◽  
Adisa Jimoh ◽  
Adedayo Yusuff
Keyword(s):  
Power Systems ◽  
Power System ◽  
Power Flow ◽  
Eigenvalue Decomposition ◽  
Step Size ◽  
Suggested Approach ◽  
Voltage Instability ◽  
Critical Nodes ◽  
Voltage Stability Enhancement ◽  
Stability Enhancement

AbstractThis paper proposes two techniques for the identification of critical buses in a power system. The technique of Network Structural Theory Participation Factor (NSTPF) depends on the network structural interconnection of buses as captured by the admittance matrix of the system and is formulated based on the fundamental circuit theory law using eigenvalue decomposition method. Another power flow based technique which depends on the system maximum loadability, the system step size among other factors is also proposed. Traditional power flow based techniques are used as benchmarks to determine the significance of the proposed methods. To ensure voltage stability enhancement, STATCOM FACTS device is installed at the selected weak load buses of the practical Nigerian 24 bus and IEEE 30 bus test systems. The results of the simulation obtained show that, the suggested approach of NSTPF is more suitable in the identification of weak buses that are liable to voltage instability in power systems as it requires less computational burden and also saves time compared to techniques based on power flow solutions.

scholarly journals Comparative performance analysis of hybrid differential evolution and pattern search technique for frequency control of the electric power system

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Pratap Chandra Pradhan ◽  
Rabindra Kumar Sahu ◽  
Sidhartha Panda
Keyword(s):  
Genetic Algorithm ◽  
Power Systems ◽  
Power System ◽  
Differential Evolution ◽  
Frequency Control ◽  
Electrical Power ◽  
Pattern Search ◽  
Thermal System ◽  
Electrical Power Systems ◽  
Suggested Approach

AbstractIn the current situation, operation and control of power system is a greater challenge. The most significant situation in power system control is load frequency control. In the present work, a hybrid differential evolution and pattern search (hDE-PS) method has been suggested for frequency regulation of electrical power systems. Fractional-order proportional integral derivative (FOPID) controller is implemented for design and analysis purpose. The suggested control method has been applied for two electrical power systems model, i.e., 2-area diverse source power system with/without HVDC linkage and 2-area thermal system. The performances of the suggested controller have been evaluated with PID and optimal controller. The simulation results indicate that system performances are enhanced with the suggested approach for identical structure. Robustness of the suggested approach has been analyzed by variation in random load and the system parameters. The suggested method (hDE-PS tuned FOPID) is further investigated with a 2-area thermal system. The performance of the recommended approach is analyzed by equating the results with other newly available approaches, like Genetic Algorithm (GA), Bacteria Foraging Optimization Algorithm (BFOA), Particle Swarm Optimization (PSO), hybrid BFOA and PSO (hBFOA-PSO), multi-objective Non-dominated Sorting Genetic Algorithm (NSGA)-II and Firefly Algorithm for the similar structure.

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

scholarly journals Algorithm for optimization of power system short-term mode in conditions of partial uncertainty of initial information taking into account the frequency change

2020 ◽  
Vol 216 ◽  
pp. 01100
Author(s):  
Tulkin Gayibov
Keyword(s):  
Power Systems ◽  
Power System ◽  
Economic Effect ◽  
Active Power ◽  
Computational Experiments ◽  
Frequency Change ◽  
Short Term ◽  
Initial Information ◽  
The Real ◽  
System Mode

Many existing methods and algorithms for optimization of short-term modes of power systems provide in calculations the introduction of a slack bus station, which ensures the balance of active power and, accordingly, the permissible frequency. In cases where the real load deviates from the planned one, determined by forecasting, the power system mode may turn out to be not optimal, and sometimes even not acceptable. This factor is especially noticeable in conditions of partial uncertainty of initial information about loads of nodes. To overcome this problem, planning of power system mode should be carried out taking into account the frequency change and, accordingly, the regulatory capabilities of all stations. This paper proposes an algorithm for optimization of modes of power systems in terms of partial uncertainty of initial information about loads, taking into account the frequency change. On the basis of computational experiments using the proposed algorithm, it is shown that taking into account the frequency change when planning modes of power systems with partially undefined loads of nodes can give a significant economic effect.

Open Knowledge Base: Resources and Units of Knowledge

2020 ◽  
Author(s):  
Matheus Pereira Lobo
Keyword(s):  
Knowledge Base ◽  
Knowledge Bases

This paper is about highlighting two categories of knowledge bases, one built as a repository of links, and other based on units of knowledge.

POWER SYSTEM STATE ESTIMATION USING A ROBUST ESTIMATOR

2019 ◽  
Vol XVI (4) ◽  
pp. 53-65
Author(s):  
Zahid Khan ◽  
Katrina Lane Krebs ◽  
Sarfaraz Ahmad ◽  
Misbah Munawar
Keyword(s):  
Power Systems ◽  
State Estimation ◽  
Loss Function ◽  
Weighted Least Squares ◽  
Primary Data ◽  
Robust Estimator ◽  
System State ◽  
State Estimator ◽  
Suggested Approach ◽  
Power System State Estimation

State estimation (SE) is a primary data processing algorithm which is utilised by the control centres of advanced power systems. The most generally utilised state estimator is based on the weighted least squares (WLS) approach which is ineffective in addressing gross errors of input data of state estimator. This paper presents an innovative robust estimator for SE environments to overcome the non-robustness of the WLS estimator. The suggested approach not only includes the similar functioning of the customary loss function of WLS but also reflects loss function built on the modified WLS (MWLS) estimator. The performance of the proposed estimator was assessed based on its ability to decrease the impacts of gross errors on the estimation results. The properties of the suggested state estimator were investigated and robustness of the estimator was studied considering the influence function. The effectiveness of the proposed estimator was demonstrated with the help of examples which also indicated non-robustness of MWLS estimator in SE algorithm.

Markov Jump Linear System Analysis of a Microgrid Operating in Islanded and Grid Tied Modes

2020 ◽  
Author(s):  
Gilles Mpembele ◽  
Jonathan Kimball
Keyword(s):  
Monte Carlo ◽  
Power Systems ◽  
Power System ◽  
System Analysis ◽  
Differential Algebraic Equations ◽  
Algebraic Equations ◽  
Markov Jump ◽  
Numerical Application ◽  
Conditional Moments ◽  
Markov Jump Linear Systems

<div>The analysis of power system dynamics is usually conducted using traditional models based on the standard nonlinear differential algebraic equations (DAEs). In general, solutions to these equations can be obtained using numerical methods such as the Monte Carlo simulations. The use of methods based on the Stochastic Hybrid System (SHS) framework for power systems subject to stochastic behavior is relatively new. These methods have been successfully applied to power systems subjected to</div><div>stochastic inputs. This study discusses a class of SHSs referred to as Markov Jump Linear Systems (MJLSs), in which the entire dynamic system is jumping between distinct operating points, with different local small-signal dynamics. The numerical application is based on the analysis of the IEEE 37-bus power system switching between grid-tied and standalone operating modes. The Ordinary Differential Equations (ODEs) representing the evolution of the conditional moments are derived and a matrix representation of the system is developed. Results are compared to the averaged Monte Carlo simulation. The MJLS approach was found to have a key advantage of being far less computational expensive.</div>

Grasshopper Algorithm Optimized Fractional Order Fuzzy PID Frequency Controller for Hybrid Power Systems

2019 ◽  
Vol 12 (6) ◽  
pp. 519-531
Author(s):  
Deepak Kumar Lal ◽  
Ajit Kumar Barisal
Keyword(s):  
Power Systems ◽  
Power System ◽  
Fractional Order ◽  
Pid Controller ◽  
Load Frequency Control ◽  
Pid Controllers ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Hybrid Power ◽  
Increasing Demand

Background: Due to the increasing demand for the electrical power and limitations of conventional energy to produce electricity. Methods: Now the Microgrid (MG) system based on alternative energy sources are used to provide electrical energy to fulfill the increasing demand. The power system frequency deviates from its nominal value when the generation differs the load demand. The paper presents, Load Frequency Control (LFC) of a hybrid power structure consisting of a reheat turbine thermal unit, hydropower generation unit and Distributed Generation (DG) resources. Results: The execution of the proposed fractional order Fuzzy proportional-integral-derivative (FO Fuzzy PID) controller is explored by comparing the results with different types of controllers such as PID, fractional order PID (FOPID) and Fuzzy PID controllers. The controller parameters are optimized with a novel application of Grasshopper Optimization Algorithm (GOA). The robustness of the proposed FO Fuzzy PID controller towards different loading, Step Load Perturbations (SLP) and random step change of wind power is tested. Further, the study is extended to an AC microgrid integrated three region thermal power systems. Conclusion: The performed time domain simulations results demonstrate the effectiveness of the proposed FO Fuzzy PID controller and show that it has better performance than that of PID, FOPID and Fuzzy PID controllers. The suggested approach is reached out to the more practical multi-region power system. Thus, the worthiness and adequacy of the proposed technique are verified effectively.

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