Energy Planning in a Big Data Era: A Theme Study of the Residential Sector

Abstract

With a focus on planning for urban energy demand, this chapter re-conceptualizes the general planning process in the big data era based on the improvements that non-linear modeling approaches provide over mainstream traditional linear approaches. First, it demonstrates challenges of conventional linear methodologies in modeling complexities of residential energy demand. Suggesting a non-linear modeling schema to analyzing household energy demand, the paper develops its discussion around repercussions of the use of non-linear modeling in energy policy and planning. Planners and policy-makers are not often equipped with the tools needed to translate complex scientific outcomes into policies. To fill this gap, this chapter proposes modifications to the traditional planning process that will enable planning to benefit from the abundance of data and advances in analytical methodologies in the big data era. The conclusion section introduces short-term implications of the proposed process for energy planning (and planning, in general) in the big data era around three topics of: tool development, data infrastructures, and planning education.