Inferring Microclimate Zones from Energy Consumption Data

TL;DR

This paper demonstrates that microclimate zones in Los Angeles can be inferred from residential electricity consumption data, revealing geographically consistent regions that align with environmental microclimates and socioeconomic factors, aiding urban energy management.

Contribution

It introduces a novel data-driven method to identify microclimate zones based on energy consumption patterns, enhancing urban climate and energy policy modeling.

Findings

EC-microclimate zones resemble environmental microclimates

Microclimate zones are linked to socioeconomic variables

Energy consumption patterns can delineate microclimate boundaries

Abstract

Climate zones are an established part of urban energy management. California is divided into 16 climate zones, for example, and each zone imposes different energy-related building standards -- so for example different zones have different roofing standards. Although developed long ago, these zones continue to shape urban policy. New climate zone definitions are now emerging in urban settings. Both the County of Los Angeles and the US Department of Energy have recently adopted refined zones -- for restructuring electricity rates, and for scoring home energy efficiency. Defining new zones is difficult, however, because climates depend on variables that are difficult to map. In this paper we show that Los Angeles climate zones can be inferred from energy use data. We have studied residential electricity consumption (EC) patterns in Los Angeles data. This data permits identification of geographical zones whose EC patterns are characteristically different from surrounding regions. These regions have topographic boundaries in Los Angeles consistent with microclimates. Specifically, our key finding is that EC-microclimate zones -- regions in which block groups have similar Electricity Consumption patterns over time -- resemble environmental microclimate zones. Because they conform to microclimates, but are based directly on EC data, these zones can be useful in urban energy management. We also show how microclimates and household electricity consumption in Los Angeles are strongly linked to socioeconomic variables like income and population density. These links permit data-driven development of microclimate zones that support zone-specific modeling and improved energy policy.