Load Shifting and Demand-Side Management in Renewable Energy Communities: Simulations of Different Technological Configurations
Year: 2025
Type: article
Abstract: This research investigates the optimization potential of Renewable Energy Communities (RECs) through advanced demand-side management strategies. The study simulates a real distribution network and analyzes load profile optimization in a residential REC configuration, comparing two distinct approaches: Demand-Side Engagement (DSE) and Optimized Demand-Side Management (Opt-DSM). The methodology encompasses load-shifting strategies at the appliance level, progressing from spontaneous behavior patterns to algorithmic optimization. Starting from a baseline scenario of conventional consumption patterns, the research evaluates the effectiveness of both user-driven load shifting (DSE) and automated redistribution through genetic algorithms (Opt-DSM). The analysis framework addresses three key dimensions: economic efficiency through incentive optimization, social cohesion via collaborative engagement, and environmental sustainability through the optimal utilization of locally generated energy. Results demonstrate that enhanced generation-consumption synchronization through Opt-DSM yields superior outcomes for both distribution network performance and participant economics compared to DSE. However, successful implementation requires substantial technological infrastructure investment at individual and community levels, alongside significant modifications to established consumption patterns. This research contributes to the understanding of RECs as innovative socio-technical systems and provides figures to support the analysis related to the balance between technological optimization and user engagement in maximizing shared energy potential.
Source: Energies
DOI: 10.3390/en18040872
Authors: Antonino Rollo, Paolo Serafini, Federico Aleotti, Debora Cilio, Enrico Morandini, Diana Moneta, Marco Rossi, Matteo Zulianello, Valerio Angelucci
Institution: Ricerca sul Sistema Energetico (Italy)
Language: English
Topic: Smart Grid Energy Management
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W4407423430
