The power of assumptions: A literature review on how algorithmic design influences energy justice in electrical distribution grids

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Authors: Eva de Winkel, Zofia Lukszo, Mark Neerincx, Roel Dobbe
Cited by: 3
References: 43

Abstract

Recent energy justice scholarship has argued for the need to reflect more explicitly on the normative assumptions that underpin claims to justice in energy systems. While such reflections increasingly inform energy policy, less attention has been paid to how these assumptions shape the design of algorithmic systems central to energy system planning and operations. This paper explores how normative assumptions in the design of algorithmic systems used to request flexibility from electricity consumers and producers to manage grid congestion may influence distributive justice outcomes. By systematically reviewing the scientific literature presenting such systems, we define two categories of assumptions: (1) scope assumptions , which set the boundaries of the justice analysis by determining which burdens and benefits, scale, subjects, and timeframe are considered relevant; and (2) design assumptions , which specify how these considerations are translated into the structure of algorithmic systems, such as allocation principles, technical problem framing, data availability and evaluation metrics. We find that the particular assumptions adopted within each category determine the distributive outcomes of these algorithmic systems. Recognizing their normative character, we propose that scope assumptions should be informed by context-specific risks of injustice identified by policymakers, while engineers should reflect on and validate their design assumptions in relation to these risks. • Algorithmic systems are increasingly used to manage congestion in distribution grids. • Normative assumptions in the design of these systems shape distributive justice. • Scope assumptions define the conceptual and analytical frame for justice. • Design assumptions determine how this frame is translated into algorithmic systems. • Highlights the need to align algorithmic design with policy on energy justice.

Fields of Study & Subjects

Sustainability and Climate Change Governance Smart Grid Energy Management Optimal Power Flow Distribution

Publication details

Journal / source
Energy Research & Social Science
Publisher
Elsevier BV
Volume
133
Pages
104605–104605
Publication date
17 February 2026
Language
EN