MATHEMATICAL MODELING OF INCREASING ENERGY EFFICIENCY OF THE UNIVERSITY IN THE ENERGY HUB KNOWLEDGE SYSTEM
Keywords:Energy Hub, energy efficiency, university, neural networks
This study attempts to address the issues of enhancing energy efficiency using mathematical modeling methods. The research findings assert that energy saving is a new challenging task of the 21st century, since thermal and electric power consumption is essential to human life and building a favourable living environment. It is observed that boosting the competitiveness, financial stability, energy and environmental security of Ukraine’s economy, as well as improving the living standards and the life quality seem hardly possible without realizing the energy saving potential and increasing energy efficiency through modernization, technological advancements and the transition towards rational and environmentally responsible utilization of energy resources. It is argued that by resolving the above objectives, Ukraine might strengthen its positions among developed economies. The following methods were used to carry out mathematical modeling to enhance the university energy efficiency in the frameworks of the energy knowledge hub: neural network technologies, mean absolute and relative error, mean absolute deviation; statistical comparison of the forecast accuracy based on the mean absolute error, as well as time series forecasting. A model to boost the University energy efficiency has been developed within the knowledge energy hub by implementing neural network patterns based on the experimental data from the Kyiv National University of Technologies and Design for the heating period 2020–2021. In particular, to optimize the operating modes of automatic power supply control for University Building 4, mathematical models with a complex algorithm structure have been employed (offering the increased resource intensity of such tasks). It is argued that making a decision on the feasibility of using an energy hub for University buildings and selecting appropriate equipment should be accomplished with due regard to the structure and the capacity of energy consumers, their types, demands for quality and reliability of electric power supply, their compliance with operating and safety standards, as well as taking into account the results of climate, wind monitoring and monitoring of solar activity. The conclusions resume that to assure the energy quality and the system sustainability, it is considered important to resolve a range of issues related to inconsistency in generation and supply of renewable energy from power plants, ensuring reliability and quality of energy supply through the use of energy storage (batteries) in particular, etc.).