The article attempts to tackle the issues of enhancing the performance of university energy efficiency management systems. An emphasis is put that in modern realia, alternative and renewable energy sources are becoming increasingly important in the electric power sector, thus contributing to environmental protection and enabling active electricity consumers to have their own sources of energy generation. However, it is observed that the relationships between energy generation sources and electricity consumers are complicated by new demands for setting balancing modes due to certain volatility of energy generation by alternative sources as well as the need to connect additional energy storage facilities. To identify opportunities of using Smart Grid technologies to manage the University energy consumption, a power balance equation was used to determine an active power balance between generated power, generation sources and power consumed by electricity consumers. In addition, the indicators of the total active power loss in the electrical network associated with the technological consumption of energy for its transmission was included into this equation. The study presents the results of an in-depth critical analysis on Smart Grid methodology and provides argument for the relevance of using artificial intelligence techniques in Smart Grid management systems of the University energy efficiency hub, along with suggesting a notion of electricity generating consumer in the concept of intelligent networks with two-way flow of energy and information as subsystems of a different nature. It is argued that the developed conceptual model of the electricity generating consumer for multilevel smart grid management systems and their infrastructure within the University energy efficiency hub allows establishing relationships between its structural elements and objects of different character. The findings reveal that the specifics of the developed method in setting priorities and regulatory standards for optimal management by a generating consumer within the University energy efficiency hub is the possibility of its automatic adaptation to changes in the external environment subject to interactions between electricity generating consumers.
Data grid management systems