On the probable and statistical choice of the arrays of representative climatic data

Currently, the successful development of the construction industry depends on the improved energy performance of buildings, structures and facilities, as well as on the quality assurance of the indoor climate. The problem of feasibly more accurate estimation of energy consumption by heating systems in buildings is a very high-priority task now because of the decrease of energy and fuel sources and because of actualization of building standards in the Russian Federation. That’s why it is very important to find simple but enough accurate dependences between the climatic parameters in the heating season of the year. The modern principles accepted in Russia and European countries for the selection of the design climate information for the design of building envelopes and systems to ensure building microclimate are considered. Shortcomings of the methods, including the concept of “typical year”, are shown and the advantages of generating climate data arrays programmatically with the use of a pseudorandom number generator are described. The comparison of the results of the calculation of non-stationary thermal regime of a ventilated room is presented using numerical modeling with daily average temperature of the external air during the month, according to climate data and the results of software generation. The principal coincidence of the statistical distribution of outdoor temperatures and the behavior of indoor air temperature on both options and the possibility of implementation of probabilistic-statistical principle of climatic data for some calculations relating to outdoor enclosures and thermal regime of the building are shown. The obtained model is easy to use in the engineering practice especially during preliminary calculations. The presentation is illustrated with numerical and graphical examples.