Print Email Facebook Twitter An Agent-Based Approach for the Planning of Distribution Grids as a Socio-Technical System Title An Agent-Based Approach for the Planning of Distribution Grids as a Socio-Technical System Author Cavalcante Siebert, L. (TU Delft Interactive Intelligence) Aoki, Alexandre R (Federal University of Paraná) Lambert-Torres, Germano (Gnarus Institute) Lambert-de-Andrada, Nelson (Gnarus Institute) Paterakis, Nikolaos G. (Eindhoven University of Technology) Date 2020-09-16 Abstract Recent developments, such as smart metering, distributed energy resources, microgrids, and energy storage, have led to an exponential increase in system complexity and have emphasized the need to include customer behavior and social and cultural backgrounds in planning activities. This paper analyzes how emergent behavior in electricity consumption can affect the planning of distribution grids with a smart grid vision. For this, an agent-based model that uses insights from the field of behavioral economics to differentiate four consumer categories (high income, low income, middle class, and early adopters) was used. The model was coupled with a real distribution feeder and customer load curve data, and the results showed that heterogeneity of customer’s preferences, values, and behavior led to very distinct load growth patterns. The results emphasize the relevance of modeling customer’s behavioral aspects in planning increasingly complex power systems. Subject Agent-based simulationBehavioral economicsPlanningPower distributionSocio-technical systems To reference this document use: http://resolver.tudelft.nl/uuid:9cef66b6-08e6-4d07-800e-3cffe5c48a3b DOI https://doi.org/10.3390/en13184837 ISSN 1996-1073 Source Energies, 13 (18), 1-13 Part of collection Institutional Repository Document type journal article Rights © 2020 L. Cavalcante Siebert, Alexandre R Aoki, Germano Lambert-Torres, Nelson Lambert-de-Andrada, Nikolaos G. Paterakis Files PDF energies_13_04837.pdf 953.51 KB Close viewer /islandora/object/uuid:9cef66b6-08e6-4d07-800e-3cffe5c48a3b/datastream/OBJ/view