Abstract.In the reliability analysis of the distribution network, information entropy is considered as the measure of uncertainty. The simple mathematical model that allows determining an entropy of a network structure is offered. The model is based on Shannon's approach to the determination of information. Reliability analysis comes down to the comparison of two components of entropy: the first is the entropy of connection a sourceelectroreceiver in the structure; the second is a boundary entropy as information of observance of the requirement to support the required reliability level of electrical power supply of the electroreceiver. The example and the procedure how to perform the necessary calculations for the analysis are provided.
IntroductionThe design and operation of systems of external power supply of mining enterprises are aimed to ensure the no-break operation of electroreceivers. One of the criteria of viability evaluation of the system is its reliability in electricity power supply of customers. The regular monitoring of system operation of electrical power supply, data processing and analysis allow designers and operators to develop effective solutions for compliance with a specified level of reliability.There are many schemes of electrical power supply of mining enterprises. Let's address to the schemes of radial distributive networks, which are used to internal electrical power supply of quarries (mines). Such networks have a simple structure and successfully provide the given level of structural reliability. When analyzing structural reliability of the network, the statistical indices are considered to be the most important: failure flow frequency; the recovery time of damages; the states probabilities of the network elements, etc.When performing reliability analysis of a distribution network of mining enterprises electrical power supply, then promising direction can be considered the estimation of information uncertainty about the state of the structure. The information uncertainty (its measure) is one of the criteria of the reliability evaluation of technical systems.
Abstract. The role of information uncertainty in the structure of a technical system is defined. The application possibility of the R. Hartley's and C.E. Shannon's approaches in determination of entropy and negentropy of structural content of the system are selected and justified. The connection between entropy and negentropy in the case of system states changes is justified. The determination example of the quantitative values of information that characterizes connection association between entropy and negentropy is done.
The model is based on the criteria of costeffectiveness and information uncertainty. The created model has fundamental difference from the current classical economicmathematical models. As constraints it is proposed to use the mathematical expressions of the information entropy determination of two states of the system: operable and nonoperable. These expressions are the constraints imposed in the task that creates an optimal radial network with redundancy. Expressions are constructed as all the elements reserving the each other are similar, i.e. they have the same performance. The given example shows how to calculate the information entropy, where a constraint is a problem solution, as well as the possibility of both applications of probabilities and numerical values for the information entropy determination is proved.
The possibilities of assessing the integration processes in agro-industrial complex are considered. Preference is given to the study of the influence of network research structures for obtaining, processing and transformation of information. The necessity of development of system recommendations taking into account theoretical achievements and analytical studies based on network analysis and the concept of entropy is indicated. The main directions in the study of integration processes based on the construction and analysis of network structures are briefly considered. The main attention is paid to the entropy approach of evaluation of integration processes. Interpretations of the measure of information uncertainty (entropy) are proposed in order to perform network analysis. Among the preferred models to determine the amount of entropy, the following are proposed: K. Shannon’s measure of uncertainty; cross-entropy and Kullback-Leibler divergence.
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