Published May 16, 2019 | Version 1.0
Dataset Open

uGIM: week monitorization data of a microgrid with five agents (10/04/19-16/04/19)

  • 1. GECAD, Polythecnic of Porto
  • 2. Polythecnic of Porto

Description

uGIM is a microgrid intelligent management software that can represent individual microgrid’s players using a multi-agent approach. This dataset has data regarding a week (from 10-04-2019 to 16-04-2019) of a microgrid with five players (all offices). All agents have consumption and generation data. One of the agents also has sensor data, such as temperature, movement and humidity.

In uGIM, agents are deployed in the player’s facilities using single-board computers. All the data in this dataset is read and stored in five single-board computers. Each agent integrates several resources. In this microgrid deployment, all resources use TCP/IP communication. However, uGIM supports more protocols, such as Modbus/RTU and Modbus/TCP.

uGIM related publications:
 - Gomes, L., Vale, Z., & Corchado, J. M. (2020). Microgrid management system based on a multi-agent approach: An office building pilot. Measurement: Journal of the International Measurement Confederation, 154. https://doi.org/10.1016/j.measurement.2019.107427
 - Gomes, L., Vale, Z. A., & Corchado, J. M. (2020). Multi-Agent Microgrid Management System for Single-Board Computers: A Case Study on Peer-to-Peer Energy Trading. IEEE Access, 8, 64169–64183. https://doi.org/10.1109/ACCESS.2020.2985254
 - Gomes, L. (2020). μGIM - Microgrid intelligen management system based on a multi-agent approach and the active participation of end-users [Universidad de Salamanca]. https://doi.org/10.14201/gredos.144238
 - Gomes, L., Spínola, J., Vale, Z., & Corchado, J. M. (2019). Agent-based architecture for demand side management using real-time resources’ priorities and a deterministic optimization algorithm. Journal of Cleaner Production, 241, 118154. https://doi.org/10.1016/j.jclepro.2019.118154

 

(if you used this dataset in your publications, please send us your information so we can add your publication to the list above)

 

We would be grateful if you could acknowledge the use of this dataset in your publications. Please use the Zenodo publication to cite this work.

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