IEEE VIS 2024 Content: Operator-Centered Design of a Nodal Loadability Network Visualization

Operator-Centered Design of a Nodal Loadability Network Visualization

David Marino - Hitachi Energy Research, Montreal, Canada

Maxwell Keleher - Carleton University, Ottawa, Canada

Krzysztof Chmielowiec - Hitachi Energy Research, Krakow, Poland

Antony Hilliard - Hitachi Energy Research, Montreal, Canada

Pawel Dawidowski - Hitachi Energy Research, Krakow, Poland

Room: Bayshore VI

2024-10-14T16:00:00ZGMT-0600Change your timezone on the schedule page
2024-10-14T16:00:00Z
Exemplar figure, described by caption below
Abstract

Transmission System Operators (TSO) often need to integrate multiple sources of information to make decisions in real time.In cases where a single power line goes offline, due to a natural event or scheduled outage, there typically will be a contingency plan that the TSO may utilize to mitigate the situation. In cases where two or more power lines go offline, this contingency plan is no longer valid, and they must re-prepare and reason about the network in real time. A key network property that must be balanced is loadability--the range of permissible voltage levels for a specific bus (or node), understood as a function of power and its active (P) and reactive (Q) components. Loadability provides information of how much more demand a specific node can handle, before system became unstable. To increase loadability, the TSO can potentially make control actions that raise or lower P or Q, which results in change the voltage levels required to be within permissible limits. While many methods exist to calculate loadability and represent loadability to end users, there has been little focus on tailoring loadability visualizations to the unique needs of TSOs. In this paper we involve operations domain experts in a human centered design process to prototype two new loadability visualizations for TSOs. We contribute a design paper that yields: (1) a working model of the operator's decision making process, (2) example artifacts of the two data visualization techniques, and (3) a critical qualitative expert review of our designs.