The use of occupancy space electrical power demand in building cooling load prediction

Energy and Buildings

Volumn 55, Issue , 2012, Pages 151-163

  Leung, M C ^a   Tse, Norman C F ^a   Lai, L L ^a   Chow, T T ^a  

^a CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Artificial neural network; Building cooling load prediction; Occupants' activities

Indexed keywords

ADVANCED METERING INFRASTRUCTURES; ARTIFICIAL NEURAL NETWORK MODELS; BUILDING COOLING LOAD; BUILDING COOLING SYSTEMS; CLIMATIC DATA; COEFFICIENT OF CORRELATION; COEFFICIENT OF VARIATION; ELECTRICAL POWER DEMAND; HONG-KONG; IN-BUILDINGS; INPUT PARAMETER; KEY FEATURE; LEVENBERG-MARQUARDT ALGORITHM; MEAN ABSOLUTE PERCENTAGE ERROR; MODEL INPUTS; OCCUPANTS' ACTIVITIES; PEAK COOLING LOAD; PERFORMANCE INDICES; POWER MONITORING; PREDICTION ACCURACY; PREDICTION PERFORMANCE; SIMULATION STUDIES; SMART GRID; SUMMER SEASON;

COLLEGE BUILDINGS; NEURAL NETWORKS; RAIN;

FORECASTING;

EID: 84870589898     PISSN: 03787788     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.enbuild.2012.08.032     Document Type: Article

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