ビル空調設備スマートグリッド電力抑制予測モデルの平常運転FastADR信号モジュレーション訓練法

抄録

Fast Automated Demand Response (FastADR), which controls the power consumption of customers' loads, is one of the future smart grid technologies. In this paper, a neural network modeling of the FastADR response property for the power consumption of building air-conditioners is studied. We propose an efficient training data collection method with operation condition zoning using the FastADR-like signal modulation during normal air-conditioning operation.