Research purpose is identification of sales problems of energy saving actions for residential sector of economy, including with use of the power service contract. The choice of the object of the study is related to the general issues on energy saving of residential facilities and increasing the number of unresolved problems. Unfortunately, the efficiency of energy consumption of housing stock is extremely low that directly leads to an increase in citizens' payments for public utilities (housing and communal services). There are many problems associated with the aging of fixed assets: it becomes especially evident in winter seasons. The level of quality of delivery, distribution and consumption of expensive heat resources that has the greatest impact on a residence comfort and sometimes human life and health, is very low. Our population faces to year overheating or freezing, to leakages through worn pipes and the subsequent disconnection of water and heat. Despite the public declaration of the of the active processes of modernization of the housing municipal economy in the Russian Federation, the implementation of the necessary energy-saving elements in the housing sector is evolving very slowly. The article presents conceptual positions, which will bring the issues related to energy saving and efficiency to a new level.
Buildings contribute 40% of global greenhouse gas emissions; therefore, strategies that can substantially reduce emissions from the building stock are key components of broader efforts to mitigate climate change and achieve sustainable development goals. Models that represent the energy use of the building stock at scale under various scenarios of technology deployment have become essential tools for the development and assessment of such strategies. Within the past decade, the capabilities of building stock energy models have improved considerably, while model transferability and sharing has increased. Given these advancements, a new scheme for classifying building stock energy models is needed to facilitate communication of modeling approaches and the handling of important model dimensions. In this article, we present a new building stock energy model classification framework that leverages international modeling expertise from the participants of the International Energy Agency's Annex 70 on Building Energy Epidemiology. Drawing from existing classification studies, we propose a multi-layer quadrant scheme that classifies modeling techniques by their design (top-down or bottom-up) and degree of transparency (black-box or white-box); hybrid techniques are also addressed. The quadrant scheme is unique from previous classification approaches in its non-hierarchical organization, coverage of and ability to incorporate emerging modeling techniques, and treatment of additional modeling dimensions. The new classification framework will be complemented by a reporting protocol and online registry of existing models as part of ongoing work in Annex 70 to increase the interpretability and utility of building stock energy models for energy policy making.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.