Digital technologies for managing anthropogenic risks in electric power industry

Abstract

The article examines the information and analytical technology implemented during the operation of electrical networks, based on the capabilities of multi-agent monitoring of the somatic and mental condition of the staff of power grid companies and predictive analysis of anthropogenic risks of energy production within the framework of a risk-based approach to human resource management. The analysis includes instrumental monitoring, assessment of indicators (using objective data) characterizing the condition of operational managers, operational and maintenance staff involved in real technological and business processes for servicing equipment of network companies using optimization theory methods, fuzzy sets, index analysis, provision of integral information to operational managers and management of energy companies, the formation of proposals on the areas of investment in the development of their human resources based on solving the optimization problem of minimizing damage due to wrong actions, inaction and violation of safety requirements for energy production. It is proposed to use a system of dimensionless index indicators for assessing the condition of staff, predictive analysis of the success of their professional activities and the formation of its ontological model in order to manage anthropogenic risks to ensure reliable and safe functioning of energy production with the possibility of developing measures and scenarios of impacts on staff within the production process. The article presents approaches to the formation of monitoring technology, which ensures the construction of unified systems for recording the condition of staff operating electric power facilities, statistics of failures due to staff's fault to determine the optimal type, composition and cost of impact on staff, improving their health based on multi-agent analysis of monitoring data, allowing to direct the flow of events in accordance with the conditions set by the availability of funds for these purposes. The authors have developed a mathematical apparatus, proposed devices and software, with the help of which an automated analysis of the indices of the condition of staff of each category, servicing equipment units (assemblies) and the formation of scenarios of impacts on it (agent-based modeling of condition-controlled behavior) has been carried out.