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ИМИТАЦИОННОЕ МОДЕЛИРОВАНИЕ ЭНЕРГОПОТРЕБЛЕНИЯ КЛАСТЕРОМ ЗДАНИЙ УНИВЕРСИТЕТСКОГО КАМПУСА
Over the past decades, the urgency of improving energy efficiency and therefore reducing the energy consumption of buildings has increased markedly for many reasons. In addition to economic considerations, an important circumstance is the provision and maintenance of comfortable conditions inside buildings. Studying the consumption of electricity by people indoors is a key to provide a comfortable environment, and this factor cannot be excluded when determining energy saving measures. To achieve this goal, this article presents a computer simulation system for predicting the electricity consumption of a cluster of buildings based on consumer behavior. The model is based on algorithms that model the energy consumption of buildings and statistical models that represent user behavior. The simulated energy consumption data can be used to train recurrent neural networks, which can then be used based on real energy consumption data to generate better electricity consumption predictions. University campuses, consisting of buildings of various types, are taken by us as a reference version of the system, as an example of an energy cluster of buildings.