$E^3$: Visual Exploration of Spatiotemporal Energy Demand

TL;DR

This paper introduces E3, a visual analytics tool that models and explores shifts in spatiotemporal energy demand, aiding experts in demand analysis and decision-making.

Contribution

The paper presents a novel unified visual analytics approach with a flow-based model for analyzing spatiotemporal energy demand shifts, validated through expert case studies.

Findings

E3 effectively supports demand hypothesis verification.

Flow-based model accurately captures demand shifts.

Experts find the tool useful for real-world data analysis.

Abstract

Understanding demand-side energy behaviour is critical for making efficiency responses for energy demand management. We worked closely with energy experts and identified the key elements of the energy demand problem including temporal and spatial demand and shifts in spatiotemporal demand. To our knowledge, no previous research has investigated the shifts in spatiotemporal demand. To fill this research gap, we propose a unified visual analytics approach to support exploratory demand analysis; we developed E3, a highly interactive tool that support users in making and verifying hypotheses through human-client-server interactions. A novel potential flow based approach was formalized to model shifts in energy demand and integrated into a server-side engine. Experts then evaluated and affirmed the usefulness of this approach through case studies of real-world electricity data. In the future, we will improve the modelling algorithm, enhance visualisation, and expand the process to support more forms of energy data.