Automatic Control of the Structure of Dynamic Objects in High-Voltage Power Smart-Grid

Никифоров, А. П.

doi:10.5772/intechopen.91664

Cited by 2 publications

(4 citation statements)

References 10 publications

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“…Next, in step 2, the choice of the architecture of the NFR, which consists of three parts in Figure 1 is carried out. In step 3 the formation of the fuzzy description of input and output parameters in the form of a term set of linguistic variables is carried out [22]. This includes defining the boundaries of the thermos (𝑥 1 , 𝑥 2 , … , 𝑥 𝑛 ), the definition area of the term set (𝑇 1 , 𝑇 2 , … , 𝑇𝑛, [𝑥 𝑚𝑖𝑛 , 𝑥 𝑚𝑎𝑥 ]), and the membership function of each of the thermos ( (𝑥)) as illustrated in Figure 2.…”

Section: Methodsmentioning

confidence: 99%

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Synthesis of the neuro-fuzzy regulator with genetic algorithm

Siddikov,

Porubay,

Rakhimov

2024

IJECE

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Real-acting objects are characterized by the presence of various types of random perturbations, which significantly reduce the quality of the control process, which determines the use of modern methods of intellectual technology to solve the problem of synthesis of control systems of structurally complex dynamic objects, allowing to compensate the influence of external factors with the properties of randomness and partial uncertainty. The article considers issues of synthesis of the automatic control system of dynamic objects by applying the theory of intelligent control. In this case, a neural network based on radial-basis functions is used at each discrete interval for neuro-fuzzy approximation of the control system, allowing real-time adjustment of the regulator parameters. The radial basis function is designed to approximate functions defined in the implicit form of pattern sets. The neuro-fuzzy regulator's parameter configuration is accomplished using a genetic algorithm, enabling more efficient computation to determine the regulator's set parameters. The regulator's parameters are represented as a vector, facilitating their application to multidimensional objects. To determine the optimal tuning parameters of the neuro-fuzzy regulator, characterized by high convergence and the possibility of determining global extrema, a genetic algorithm was used. The effectiveness of the neuro-fuzzy regulator is explained by the possibility of providing quality control of the dynamic object under random perturbations and uncertainty of input data.

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Section: Methodsmentioning

confidence: 99%

“…Step 8, introducing one formal neuron into NFR, which makes it possible to set the weight of each rule when constructing the resulting inference. The result is an NFR structure Figure 3 In this case, the value of the activation function 𝑔 is defined as (6) [22]:…”

Section: Methodsmentioning

confidence: 99%

Synthesis of the neuro-fuzzy regulator with genetic algorithm

Siddikov,

Porubay,

Rakhimov

2024

IJECE

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“…Each component is formed by the amplitude "Ξ" and time "H" parameters of the UIN signals. The initial amplitude Ξ-window starts when the initiating TS1 appears, which is known for a specific transient recognition problem [7,8]. The result of each Ξ,Ηwindow triggering has its own significance KN coefficient.…”

Section: Formulation Of the Problem Relevance Of Detecting Scen Aries In Dynamic Objectsmentioning

confidence: 99%

“…The tasks of relay protection and automation (RPA) [5], diagnostics [6], self-control [7], economics [8] and others are reduced to the management of such a group of dynamic OCP. The tasks of recognising the semantic events SN, and SceN are characterized by irregularity, discontinuity of changes in time of development of transient processes [9,10].…”

Section: Introductionmentioning

confidence: 99%

Detecting development scenarios of dynamic events in electric power networks smart-grid Part1 “Method”

Sivokobylenko¹,

Nikiforov²,

Zhuravlov³

2021

AAIT

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A method for constructing a semantic S-detector for the senior hierarchical level of pattern recognition in dynamic objects is proposed. The S-detection method is based on a uniform synthesis of all hierarchically subordinate detectors and information preparation schemes, based on the tasks of the upper hierarchical level of recognition of scenarios for the development of processes in an object. The method can be used to solve problems of relay protection, emergency control automation, to identify rare events in impulse, short-term input signals when implementing the concept of developing of electric power smart-grid. The synthesis of the Sdetector of scenarios for the development of transient processes was the result of the development of a structural-information SImethod for processing information components. A mathematical SI-model is presented that allows you to control the mutual correspondence of the structure of the formation tree in the object and the device recognition tree. The task is to improve the stability of the device recognition algorithm. The Part 1 describes the theoretical provisions of the application of the recognition method. It is proposed to unify the trees for generating recognition scenarios in the industry, similar to the IEEE high-voltage network diagrams. The S-detector algorithm based on the formation of a semantic signal and on the selective search for the required amount of information for automatic decision-making is presented. The facts of the appearance of elementary information events in the input signals of the detector are controlled by Ξ,H-selectivity windows, which are sequentially opened depending on the previous development of events. The block diagram of the S-detector of the scenario is presented, which can be synchronous, multichannel, with a high signal processing speed, without losing rapidly changing information when slow and infraslow information is detected. Combines useful properties of instantaneous and inertial detection algorithms. The output of the S-detector is a series of responses with different weights. This allows elementary detectors to be combined into sequential chains at different hierarchical levels of recognition. Part 2 provides an example of the application of the scenario detection method to solve the problem of increasing the stability of the operation of a selective protection relay against single-phase earth faults based on medium-frequency signals in 6-35 kV networks with an arc suppression Petersen’s coil. The results of modelling the operation of the S-detector algorithm on the signals of real emergency files recorded by high-frequency recorders of transient processes in the network are presented.

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Automatic Control of the Structure of Dynamic Objects in High-Voltage Power Smart-Grid

Cited by 2 publications

References 10 publications

Synthesis of the neuro-fuzzy regulator with genetic algorithm

Synthesis of the neuro-fuzzy regulator with genetic algorithm

Detecting development scenarios of dynamic events in electric power networks smart-grid Part1 “Method”

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