Next Article in Journal
Fault Detection of High-Speed Train Traction System Based on Probability-Related Slow Feature Analysis
Previous Article in Journal
Evaluating the Costs of Integrated Solar Hydrogen Systems: Exploring the Effect of Scale, Intermittency, and Energy Storage
Previous Article in Special Issue
Expansion Planning of Electrical Distribution Systems Considering Voltage Quality and Reliability Criteria
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Energies
Volume 18
Issue 22
10.3390/en18226072
energies-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Distributed EMS Coordination Via Price-Signal Control for Renewable Energy Communities

by
Lorenzo Becchi
,
Marco Bindi
*,
Francesco Grasso
,
Matteo Intravaia
,
Gabriele Maria Lozito
and
Antonio Luchetta
Department of Information Engineering, Università degli Studi di Firenze, Via di Santa Marta 3, 50139 Firenze, Italy
*
Author to whom correspondence should be addressed.
Energies 2025, 18(22), 6072; https://doi.org/10.3390/en18226072 (registering DOI)
Submission received: 20 October 2025 / Revised: 7 November 2025 / Accepted: 14 November 2025 / Published: 20 November 2025
(This article belongs to the Special Issue Approaches and Experiences of Monitoring and Control of Electrical Distribution Grids)
Versions Notes

Abstract

This work presents a two-level Energy Management System (EMS) for Renewable Energy Communities (RECs) combining rule-based local control with Particle Swarm Optimization (PSO) coordination. A central Energy Management Hub (CEMH) uses digital twins of each Home EMS to optimize community performance through price-signal adjustments rather than direct control. The method achieves near-optimal self-consumption and incentive gains, largely within 10% of an MILP benchmark, while reducing computational time by about threefold. The approach ensures scalability, resilience, and fairness through a transparent incentive redistribution mechanism, enabling real-time and socially accepted REC coordination.
Keywords: Renewable Energy Communities; Energy Management System; Particle Swarm Optimization; digital twin; edge computing; economic benefit allocation; fairness Renewable Energy Communities; Energy Management System; Particle Swarm Optimization; digital twin; edge computing; economic benefit allocation; fairness

Share and Cite

MDPI and ACS Style

Becchi, L.; Bindi, M.; Grasso, F.; Intravaia, M.; Lozito, G.M.; Luchetta, A. Distributed EMS Coordination Via Price-Signal Control for Renewable Energy Communities. Energies 2025, 18, 6072. https://doi.org/10.3390/en18226072

AMA Style

Becchi L, Bindi M, Grasso F, Intravaia M, Lozito GM, Luchetta A. Distributed EMS Coordination Via Price-Signal Control for Renewable Energy Communities. Energies. 2025; 18(22):6072. https://doi.org/10.3390/en18226072

Chicago/Turabian Style

Becchi, Lorenzo, Marco Bindi, Francesco Grasso, Matteo Intravaia, Gabriele Maria Lozito, and Antonio Luchetta. 2025. "Distributed EMS Coordination Via Price-Signal Control for Renewable Energy Communities" Energies 18, no. 22: 6072. https://doi.org/10.3390/en18226072

APA Style

Becchi, L., Bindi, M., Grasso, F., Intravaia, M., Lozito, G. M., & Luchetta, A. (2025). Distributed EMS Coordination Via Price-Signal Control for Renewable Energy Communities. Energies, 18(22), 6072. https://doi.org/10.3390/en18226072

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop