Battery Management System for Energy Communities Using a Cost Sensitive Rule-Based algorithm

Authors

  • Marcos Trujillo-Trujillo Departamento de Ingeniería Informática y de Sistemas, Universidad de La Laguna (ULL). Camino San Francisco de Paula, 19. 38200 La Laguna (Tenerife), Spain Author
  • Juan A. Méndez-Pérez Departamento de Ingeniería Informática y de Sistemas, Universidad de La Laguna (ULL). Camino San Francisco de Paula, 19. 38200 La Laguna (Tenerife), Spain Author
  • Santiago Torres-Álvarez Departamento de Ingeniería Informática y de Sistemas, Universidad de La Laguna (ULL). Camino San Francisco de Paula, 19. 38200 La Laguna (Tenerife), Spain Author
  • Alberto Hamilton-Castro Departamento de Ingeniería Informática y de Sistemas, Universidad de La Laguna (ULL). Camino San Francisco de Paula, 19. 38200 La Laguna (Tenerife), Spain Author
  • Jose M. Gonzalez-Cava Departamento de Ingeniería Informática y de Sistemas, Universidad de La Laguna (ULL). Camino San Francisco de Paula, 19. 38200 La Laguna (Tenerife), Spain Author
  • Iván Castilla-Rodríguez Departamento de Ingeniería Informática y de Sistemas, Universidad de La Laguna (ULL). Camino San Francisco de Paula, 19. 38200 La Laguna (Tenerife), Spain Author
  • Benjamín González-Díaz Departamento de Ingeniería Industrial, Universidad de La Laguna (ULL). Camino San Francisco de Paula, 19. 38200 La Laguna (Tenerife), Spain Author

DOI:

https://doi.org/10.52152/4594

Keywords:

Energy Community, Battery Management System, Rule-based System

Abstract

Energy Communities (ECs) drive decentralized energy production and consumption, fostering active citizen participation. Within this framework, battery systems play a crucial role in efficiency and optimization, requiring an effective Battery Management System (BMS) to optimize energy control. This paper presents a rule-based approach for effective battery energy management within an energy community. The proposed system integrates a set of predefined rules that determine battery operation by considering factors such as hourly energy prices, photovoltaic power generation, and user consumption patterns. This approach enables more efficient energy utilization, reduces dependence on the electrical grid, facilitates cost reduction, and ensures stability of the local energy network.

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Published

2025-07-25

Issue

Section

Articles