Big-Data Analytics Based Energy Analysis and Monitoring for Multi-storey Hospital Buildings: Case Study

Abstract

Big-Data analytics based energy analysis and monitoring for multistory buildings plays an important role in proper management and control of operation of the hospital. In this study, hospitals of 16 time zones of three construction categories (Pre-1980 construction, Post-1980 construction, and new construction categories) have been analyzed, which includes hospital summary (details about form, fabric, and HVAC), hospital's zone summary (details about area, volume, lighting, and occupants), and location summary (details about utility costs, energy end use, and peak energy demand). The energy consumption in hospital has been analyzed as per the HVAC consumption, utility costs, energy end uses and intensities, monthly peak energy demand, sources of energy, water consumption, and emissions of gases. Emissions of gases analysis deal with the occupancy analysis in the hospital. Energy end uses and intensities based analysis and monitoring deals with the analysis of consumed electricity energy (kWh) (in heating, cooling, interior and exterior lighting, interior and exterior equipment, fan, pump, heat rejection, humidification, heat recovery, water system, refrigeration, generators, and total end uses) analysis, gas analysis (MJ), and purchase cooling and heating (MJ) analysis. Presented energy analysis and monitoring provides the better management compatibility of the hospital under perturbing operating condition as well.