Priority Events Determination For The Risk-oriented Management Of Electric Power System

The task of risk-oriented management of the electric power system in conditions of multi-criteria choice is considered. To determine the most effective measures, the implementation of which will reduce the magnitude of the risk of an emergency situation, multi-criteria analysis methods are applied. A comparative analysis of the multi-criteria alternative (ELECTRE) ranking method based on utility theory and the Pareto method, which defines a subset of non-dominant alternatives, is carried out. The Pareto method uses in its algorithm only qualitative characteristics of the advantage and allows only to distinguish a group of competitive solutions with the same degrees of non-dominance. Given the large number of evaluation criteria, the Pareto method is ineffective because the resulting subset of activities is in the field of effective trade-offs, when no element of the set of measures can be improved without degrading at least one of the other elements. The ELECTRE method is a pairwise comparison of multi-criteria alternatives based on utility theory. This method allows to identify a subset of the most effective activities. The number of elements of the resultant subset is regulated by taking into account the coefficients of importance of optimization criteria and expert preferences

Development of Fuzzy Statistical Method of Optimal Resource Allocation Among Technical Departments of an Electric Utility Company

We formulated the approach to solving specific aspects of the task of strategic planning of sustainable development of an electric utility enterprise as a multi-criteria decision-making problem, which can be solved under conditions of fuzzy initial information. To solve this task, the method of constructing a set of feasible solutions was proposed, based on the specific functioning of an enterprise divisions. The set of feasible variants is compiled according to the Pareto method, when no element can be improved without worsening of at least one of the other elements, which makes it possible to define a compromise allocation of funding, at which the minimum possible value of the risk of an accident in the electric utility enterprise's networks is provided. As an optimizationl criterion, we adopted the risk of an accident occurrence in an electric utility system.To solve the task of risk evaluation at solving a linear programming problem, we applied the method, which allows evaluating the risk by analytical way without carrying out probabilistic-statistical modeling.As a result, the developed method is efficient for practical application during an express evaluation of the risk at different variants of the allocation of funds among the units of electric utility enterprise without carrying out of cumbersome probabilistic-statistical modeling

Construction of Models for Estimating the Technical Condition of a Hydrogenerator Using Fuzzy Data on the State of Its Local Nodes

The task on estimating the technical condition of a hydrogenerator under conditions of fuzzy information has been resolved. To this end, a series of models have been constructed for the integrated estimation of the technical condition of a hydrogenerator based on data about the states of its local nodes. The technical states of local nodes are determined based on the earlier devised fuzzy models of the Mamdani type and represent the fuzzy values, which was taken into consideration in the model for estimating technical condition of a hydrogenerator.The fuzzy methods by Mamdani, Sugeno, Zadeh, as well as the simplified fuzzy inference, were used to build the models. The fuzzy model by Mamdani has a qualitative base of rules only, which simplifies its construction by an expert. The models based on the fuzzy algorithm by Sugeno imply a rule base with weight coefficients, determined by the Saati method. The simplified method and the method by Zadeh require minimal expert participation when constructing a fuzzy model. Examples of estimating the technical condition of a hydrogenerator have been considered based on five devised fuzzy models; the sensitivity of models to the quality and reliability of input information has been tested.It has been determined that the most reliable result from estimating the state of a hydrogenerator with an error of 1.5–2 % is produced by models built according to Zadeh method and the simplified fuzzy inference, since they have the least dependence on the uncertainty of input data on the states of local nodes, which themselves were obtained based on fuzzy models. High accuracy of these models and low dependence on the quality of incoming information are explained by the minimal participation of an expert during its configuration. The fuzzy models built using the algorithms by Mamdani and Sugeno yield a greater error of 3–4 %. Oure findings could be used to assess the remaining or spent resource of hydrogenerators, the probability of their failure over a time interval, and to execute the risk-oriented control over an electricity energy system and its subsystem

Construction of Models for Estimating the Technical Condition of a Hydrogenerator Using Fuzzy Data on the State of Its Local Nodes

The task on estimating the technical condition of a hydrogenerator under conditions of fuzzy information has been resolved. To this end, a series of models have been constructed for the integrated estimation of the technical condition of a hydrogenerator based on data about the states of its local nodes. The technical states of local nodes are determined based on the earlier devised fuzzy models of the Mamdani type and represent the fuzzy values, which was taken into consideration in the model for estimating technical condition of a hydrogenerator.The fuzzy methods by Mamdani, Sugeno, Zadeh, as well as the simplified fuzzy inference, were used to build the models. The fuzzy model by Mamdani has a qualitative base of rules only, which simplifies its construction by an expert. The models based on the fuzzy algorithm by Sugeno imply a rule base with weight coefficients, determined by the Saati method. The simplified method and the method by Zadeh require minimal expert participation when constructing a fuzzy model. Examples of estimating the technical condition of a hydrogenerator have been considered based on five devised fuzzy models; the sensitivity of models to the quality and reliability of input information has been tested.It has been determined that the most reliable result from estimating the state of a hydrogenerator with an error of 1.5–2 % is produced by models built according to Zadeh method and the simplified fuzzy inference, since they have the least dependence on the uncertainty of input data on the states of local nodes, which themselves were obtained based on fuzzy models. High accuracy of these models and low dependence on the quality of incoming information are explained by the minimal participation of an expert during its configuration. The fuzzy models built using the algorithms by Mamdani and Sugeno yield a greater error of 3–4 %. Oure findings could be used to assess the remaining or spent resource of hydrogenerators, the probability of their failure over a time interval, and to execute the risk-oriented control over an electricity energy system and its subsystem