FORESIGHT TOOLS TO ENHANCE ENERGY EFFICIENCY IN BUILDINGS BASED ON THE UNIVERSITY ENERGY HUB
DOI:
https://doi.org/10.30857/2786-5398.2021.5.6Keywords:
University energy hub, Foresight, automated heating stationAbstract
The article reveals the essence of the key motivation drivers to save energy and increase the energy efficiency in higher education institutions. In particular, a low level of interest of higher education institutions in the implementation of strategies to reduce energy consumption has been observed. The findings suggest that the lack of interest in energy saving is primarily affected by budget legislation since the energy cost calculation was based on the consumption norms for a particular budgetary institution and the current (planned) electricity and heat tariffs. Recently, it has been decided that from now on universities will not obtain budget funding to cover utility costs; the amount of subsidies from the Ministry of Education and Science of Ukraine for the implementation of the government objectives will comprise regulatory costs for public service provision according to the student contingent. Standard property maintenance costs will not be covered by the Ministry anymore which will impose the burden of paying the utility bills upon the University’s gross income. Hence, there is a need to take efforts to enhance energy efficiency and energy saving in higher education institutions which was implemented using a foresight methodology. Within the scope of this study, the foresight project to improve the energy efficiency of buildings in the frameworks of the University energy hub is based on the following calculations: thermal energy consumption for heating public buildings, estimated hourly heating load to ensure heating in the building, verifying the feasibility of heating standby regulation, measuring energy savings through the creation of an automated heat supply station, as well as annual savings in monetary terms. In order to save resources and boost energy efficiency based on the University energy hub using an automated heat supply station, the study offers a mathematical toolkit to justify the choice of minimum and maximum values of optimal microclimate parameters; reduce infiltration, increase the efficiency of indoor air distribution; optimal modes of local air conditioning, preheating and cooling; utilizing of "waste" and natural heat and cold; "combining" microclimate systems with other systems; improving automation devices in technical systems. It is argued that increasing the energy efficiency of heating systems in University buildings on the basis of its own energy hub will contribute to gaining significant savings in thermal energy for heating and significantly reduce carbon dioxide emissions into the environment. In addition, the study reveals that the cost of thermal energy for heating depends upon a building design, modernization quality, reconstruction and insulation, applied building materials, spatial planning solutions, the presence or absence of control and automated systems, maintenance systems and attitude of owner’s attitude to innovations. The conclusions summarize that the cost of thermal energy can vary significantly in buildings of the same type.