On the Spatio-Temporal End-User Energy Demands of a Dense Urban Environment

Abstract

Buildings in major metropolitan centers face increased peak electrical load during the warm season, especially during extreme heat events. City-wide, the increased demand for space cooling can stress the grid, increasing generation costs. It is therefore imperative to better understand building energy consumption profiles at the city scale. This understanding is not only paramount for users to avoid peak demand charges but also for utilities to improve load management. This study aims to develop a city-scale energy demand forecasting tool using high resolution weather data interfaced with a single building energy model. The forecasting tool was tested in New York City (NYC) due to the availability of building morphology data. We identified 51 building archetypes, based on the building function (residential, educational, or office), the age of the building, and the land use type. The single building simulation software used is energyplus which was coupled to an urbanized weather research and forecasting (uWRF) model for weather forecast input. Individual buildings were linked to the archetypes and scaled using the building total floor area. The single building energy model is coupled to the weather model resulting in energy maps of the city. These maps provide an energy end-use profile for NYC for total and individual components including lighting, equipment and heating, ventilation, and air-conditioning (HVAC). The methodology was validated with single building energy data for a particular location, and with city-scale electric load archives, showing good agreements in both cases.