П.А. Головинский, Д.Н. Васенин, Н.В. Саввин, Е. Е. Прокшиц
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引用次数: 0
Abstract
Представлена система имитационного моделирования для прогнозирования потребления электроэнергии кластером зданий на основе поведения потребителей. Модель основана на алгоритмах, моделирующих энергопотребление зданий, и статистических моделях, представляющих поведение пользователей.
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.
Представлена система имитационного моделирования для прогнозирования потребления электроэнергии кластером зданий на основе поведения потребителей.Модель основана на алгоритмах, моделирующих энергопотребление зданий, и статистических моделях, представляющих поведение пользователей.在过去的几十年里,由于多种原因,提高能源效率、从而降低建筑物能耗的紧迫性明显增强。除了经济方面的考虑外,一个重要的因素是提供和维持建筑物内的舒适条件。研究人们在室内的用电量是提供舒适环境的关键,在确定节能措施时不能排除这一因素。为了实现这一目标,本文介绍了一种基于消费者行为预测建筑群耗电量的计算机模拟系统。该模型基于建筑物能耗建模算法和代表用户行为的统计模型。模拟的能源消耗数据可用于训练递归神经网络,然后根据真实的能源消耗数据来生成更好的电力消耗预测。我们将由不同类型建筑组成的大学校园作为该系统的参考版本,作为建筑物能源集群的一个实例。