AI-Driven Smart Grid Solutions for Energy Justice: Integrating Technical Efficiency with Inclusive Social Welfare Policy Design

Hafize Nurgul Durmus Senyapar, Ramazan Bayindir

Abstract


This study examines the evolving role of Artificial Intelligence (AI) and Smart Grid systems in shaping policy frameworks that promote energy justice and inclusive social welfare. As Smart Grids enable real-time data exchange, decentralized energy management, and two-way communication between utilities and consumers, they provide a dynamic infrastructure for deploying AI-driven solutions. AI technologies—ranging from demand forecasting and anomaly detection to predictive maintenance—offer powerful tools for optimizing energy distribution and aligning technical efficiency with social equity goals. When integrated with Smart Grid platforms, these tools can enhance energy governance by identifying underserved regions, supporting dynamic pricing strategies, and enabling context-sensitive subsidy programs. Moreover, by incorporating data on social vulnerability and systemic inequities, AI can inform cross-sectoral policies that improve housing conditions, health outcomes, and income security. However, the adoption of AI and Smart Grid technologies in policymaking raises critical concerns about algorithmic bias, data opacity, and the exclusion of marginalized voices. This paper explores the dual role of AI-enabled Smart Grids as both enablers of equitable policies and potential sources of new barriers. Using a qualitative, exploratory approach, the study investigates how these technologies can be implemented ethically, transparently, and inclusively to support both equitable energy transitions and resilient social welfare systems.

Keywords


Smart grid, artificial intelligence, energy justice, social welfare policy, inclusive policymaking, algorithmic bias, ethical ai, equity in energy policy

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References


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DOI (PDF): https://doi.org/10.20508/ijsmartgrid.v9i3.426.g400

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