Synthesis of life support nanotechnologies into a replicated autonomous engineering system of an individual dwelling house

Introduction. Currently, one can witness a boom of renewable energy in foreign countries: zones with earth, coastal and even offshore wind power plants are emerging, and the roofs of houses, hotels, schools and hospitals are being "dressed" by solar batteries and by panels to generate electricity and water. At the same time, despite the fact that these installations are unreliable and rare sources, many experts and politicians begin to mistakenly consider them as the basic ones. All that poses a scientific and technical problem of determining the place of nature-like technologies in the structure of life support systems of the population. Methods, models and tools. The paper analyzes the engineering systems of multi-apartment residential buildings and individual residential buildings that deliver life support resources (electricity, gas, cold and hot water, etc.). But one should also note that the engineering systems often keep potential fire-energy and environmental harm. To resolve the mentioned problems, some nanotechnologies and Russian patents concerning autonomous electricity, water, heat supply of individual residential buildings on them were proposed. Results and discussion. Modeling has shown that the combination of "Shukhovskaya" and vortex wind turbines with domestic hydraulic panels and solar panels makes it possible to create duplicated and tripled engineering systems of individual residential buildings, which, in terms of quality, reliability and safety parameters, are several orders of magnitude higher than the existing centralized resource supply systems for the residential sector of cities and rural settlements. Conclusion. The proposed approach makes it possible to determine the place of the so-called renewable energy in the structure of the resource supply system for cities and rural settlements, and it remains to assess its effectiveness, which is supposed to be done using the Leontiev-Ford model and the retro-forecasting method.