Justification of Financing of Measures to Prevent Accidents in Power Systems

The article proposes the models of rational resource allocation for the implementation of measures to prevent industrial accidents in energy supply systems. They allow maximizing the integral effect of preventing these accidents, as well as eliminating their consequences in the event of restrictions on the resources allocated. As a unified measure of the volume of resources, the cost of implementing these measures has been adopted. The integral effect of financing events is estimated by an indicator formed by various options for combining private indicators of the effect of their financing. Analytical relationships have been obtained for a number of options for representing the integral effect of financing measures to prevent industrial accidents in power supply systems. They cover a fairly wide range of interesting practical problems that allow assessing various types of synergistic effect due to the distribution of available resources for financing the activities under consideration. This makes the proposed models useful for energy management at the micro and macro levels. Their practical application in the interests of energy management is associated with the choice of one or several models reflecting the specifics of measures to prevent technological accidents in power supply systems and the specification of the constant parameters of these models taking into account the specifics of these measures

Justification of Financing of Measures to Prevent Accidents in Power Systems

The article proposes the models of rational resource allocation for the implementation of measures to prevent industrial accidents in energy supply systems. They allow maximizing the integral effect of preventing these accidents, as well as eliminating their consequences in the event of restrictions on the resources allocated. As a unified measure of the volume of resources, the cost of implementing these measures has been adopted. The integral effect of financing events is estimated by an indicator formed by various options for combining private indicators of the effect of their financing. Analytical relationships have been obtained for a number of options for representing the integral effect of financing measures to prevent industrial accidents in power supply systems. They cover a fairly wide range of interesting practical problems that allow assessing various types of synergistic effect due to the distribution of available resources for financing the activities under consideration. This makes the proposed models useful for energy management at the micro and macro levels. Their practical application in the interests of energy management is associated with the choice of one or several models reflecting the specifics of measures to prevent technological accidents in power supply systems and the specification of the constant parameters of these models taking into account the specifics of these measures. © 2019, Springer Nature Switzerland AG

Models for predicting damage due to accidents at energy objects and in energy systems of enterprises

Achieving energy security by preventing and timely eliminating the consequences of accidents at energy facilities and in energy supply systems of enterprises is one of the important tasks of energy management. The basis for planning appropriate energy security measures is the prediction of damage from these accidents. The purpose of forecasting is to assess the possibility of an accident occurring at some point in time and leading to a particular damage, and to assess the magnitude of this damage. The article proposed methodological approaches to the construction of mathematical models of such prediction. In this case, as an indicator of damage, the economic losses caused by these accidents are taken. The simulation is based on the representation of this indicator in the form of a step change function of the magnitude of losses in the event of an accident. Depending on the amount of information available in the period prior to forecasting, the mathematical representation of the forecasting problem is reduced to the construction of conditionally determined or stochastic models. Conditionally determined models allow obtaining acceptable damage estimates with a short period of retrospection and small amounts of information, and stochastic models with significantly large amounts. At the same time, the principle of "maximum uncertainty" formalized in the form of maximum entropy is the basis for removing uncertainty in the construction of both conditionally determined and stochastic models. Its use has allowed increasing the objectivity of forecasts by minimizing the subjective information used in modeling. The proposed approaches to the construction of mathematical models for predicting accidents at energy facilities and power supply systems of enterprises are the basis for creating specific techniques for solving relevant energy management tasks both at the micro level at the scale of individual enterprises and at the macro level at the scale of industries, regions and the state as a whole. © The Authors, published by EDP Sciences, 2019