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 02-03-2020 to 08-03-2020) of a microgrid with five players (all offices). All agents have consumption and generation data and are able to participate in peer-to-peer transactions using an auction model. The dataset presents the data regarding: energy values (consumption and generation); energy forecasting (consumption and generation); auction participations; and peer-to-peer transactions. The transactions are analysed and classified by type: best choice; wrong sale; wrong purchase; sold too much; and bought too much. All five agents are able to sell energy from the peer-to-peer auction. However, only four can buy energy: L.1; L.2; L.3; and R.2. Agent Z.0 is configured only to sell energy. All agents have photovoltaic generation where L.1, L.2, L.3; and R.2 have 1 kW each and Z.0 has 6 kW. 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.