Intelligent Distribution Electrical Grid Section Efficiency Analysis

In this chapter, we illustrate the possibilities of using the apparatus of semi-Markov process theory with a common phase space of states and the hidden Markov model theory for estimating and predicting system states on the example of an intelligent distribution power grid section. First, we're constructing a semi-Markov model of a digital polygon distribution power grid section, which is an intelligent network, and determining its stationary reliability and time characteristics as well. Using the algorithm of stationary phase enlargement and the obtained results, we construct a merged semi-Markov model, determine parameters and develop a hidden Markov model. Based on a given signal vector, the model allows finding the most probable states corresponding to it and elements of subsequent states of the simulated system. We use a constructed hidden Markov model to solve different problems, such as predicting signals and states during the functioning of the grid section. The results of the chapter open the possibility of assessing the system's effectiveness, taking into account the information received during its operation.