基于SOA-RVFL预测模型的建筑节能控制方法研究

Research on Building Energy Saving Control Method Based on the SOA-RVFL Prediction Model

为了在满足建筑室内舒适性的同时更有效地节约能耗,本文提出了一种基于海鸥算法优化的随机向量功能连接网络(SOA-RVFL)策略对建筑能耗与温度进行预测,并通过预测结果动态调节建筑内的制热/制冷系统。策略在济南某公共建筑上应用,结果与传统的基线控制相比,降低了11.9%的建筑能耗。

In order to satisfy the indoor comfort of buildings and save energy consumption more effectively at the same time,this paper proposes a seagull optimization algorithm based random vector functional link network(SOA-RVFL)strategy to predict the building energy consumption and temperature,and dynamically adjusts the heating/cooling system in the building through the prediction results.The strategy was applied to a public building in Jinan.Results indicated that the proposed method could reduce the building energy consumption by about 11.9% in comparison with the traditional base control method.