机译:住宅电力负荷监测和建模 - 智能家庭和网格的艺术状态和未来趋势
College of Automotive Engineering Jilin University Changchun China;
Department of Electrical and Computer Engineering University of Kentucky KY USA;
Toshiba International Corporation TX USA;
Department of Electrical and Computer Engineering University of Kentucky KY USA;
GE Global Research NY USA;
Department of Electrical and Computer Engineering University of Kentucky KY USA;
smart home; smart grid; smart community; smart appliance; appliance scheduling; artificial intelligence (AI); residential energy data; heating; ventilation and air conditioning (HVAC); home energy management system (HEMS); smart plug; load modeling; non-intrusive load monitoring (NILM); building energy; load forecast; demand response; big data; machine learning; deep learning; artificial neural networks (ANN); long short-term memory (LSTM); edge computing; cybersecurity; internet of things (IoT); distributed renewable energy source; photo-voltaic (PV); net-zero-energy home; time of use; prosumer; transactive energy;
机译:用于智能家居和住宅建筑中非侵入式负载监控的多元事件检测方法
机译:智能房屋和住宅建筑物非侵入式负荷监测的多变量事件检测方法的勘探[能量与建筑物208(2020)109624]
机译:具有响应负载与可再生能源的最佳结合的住宅智能配电网的三目标调度
机译:智能电网中的家庭电力负荷管理和住宅负荷分类
机译:实时多重负荷监测和控制基础设施及其在改进智能电网区域稳定监测的临床中估算的应用
机译:智能配电板(Smart DB)用于负载设备设备签名识别的非侵入式负载监控(NILM)和用于电网需求管理的智能插座
机译:基于混合人工神经网络粒子群的电能管理在智能房屋中提供了综合整合的两级非侵入式负荷监测过程