Dissemination

Publications

Journal Articles

» Ensemble learning for electricity consumption forecasting in office buildings

Tiago Pinto, Isabel Praça, Zita Vale, Jose Silva, Ensemble learning for electricity consumption forecasting in office buildings, Neurocomputing, 2020, ISSN 0925-2312.

DOI: https://doi.org/10.1016/j.neucom.2020.02.124

» The Impact of Attacks in LEM and Prevention Measures Based on Forecasting and Trust Models

Andrade, R.; Praça, I.; Wannous, S.; Ramos, S. The Impact of Attacks in LEM and Prevention Measures Based on Forecasting and Trust Models. Processes 2021, 9, 314.

DOI: https://doi.org/10.3390/pr9020314

» Design of a Secure Energy Trading Model Based on a Blockchain

Ko, H.; Praça, I. Design of a Secure Energy Trading Model Based on a Blockchain. Sustainability 2021, 13, 1634.

DOI: https://doi.org/10.3390/su13041634

» Influence of Features on Accuracy of Anomaly Detection for an Energy Trading System

Ko, H.; Rim, K.; Praça, I. Influence of Features on Accuracy of Anomaly Detection for an Energy Trading System. Sensors 2021, 21, 4237.

DOI: https://doi.org/10.3390/s21124237

» Extending a Trust model for Energy Trading with Cyber-Attack Detection

Andrade, R.; Wannous, S.; Pinto, T.; Praça, I. Extending a Trust model for Energy Trading with Cyber-Attack Detection. Electronics 2021, 10, 1975.

DOI: https://doi.org/10.3390/electronics10161975

Book Chapters

» Identifying Most Probable Negotiation Scenario in Bilateral Contracts with Reinforcement Learning

Silva F., Pinto T., Praça I., Vale Z. (2019) Identifying Most Probable Negotiation Scenario in Bilateral Contracts with Reinforcement Learning. In: Rocha Á., Adeli H., Reis L., Costanzo S. (eds) New Knowledge in Information Systems and Technologies. WorldCIST’19 2019. Advances in Intelligent Systems and Computing, vol 930. Springer, Cham.

DOI: https://doi.org/10.1007/978-3-030-16181-1_53

» Energy Consumption Forecasting using Ensemble Learning Algorithms

Silva J., Praça I., Pinto T., Vale Z. (2020) Energy Consumption Forecasting Using Ensemble Learning Algorithms. In: Herrera-Viedma E., Vale Z., Nielsen P., Martin Del Rey A., Casado Vara R. (eds) Distributed Computing and Artificial Intelligence, 16th International Conference, Special Sessions. DCAI 2019. Advances in Intelligent Systems and Computing, vol 1004. Springer, Cham.

DOI: https://doi.org/10.1007/978-3-030-23946-6_1

» Trust Model for a Multi-Agent based simulation of Local Energy Markets

Andrade R., Pinto T., Praça I. (2020) Trust Model for a Multi-agent Based Simulation of Local Energy Markets. In: De La Prieta F. et al. (eds) Highlights in Practical Applications of Agents, Multi-Agent Systems, and Trust-worthiness. The PAAMS Collection. PAAMS 2020. Communications in Computer and Information Science, vol 1233. Springer, Cham.

DOI: https://doi.org/10.1007/978-3-030-51999-5_15
Electronics MDPI Best papers (check awards below)

» A two tier architecture for Local Energy Market Simulation and Control

Andrade R., Garcia-Rodriguez S., Praca I., Vale Z. (2020) A Two Tier Architecture for Local Energy Market Simulation and Control. In: De La Prieta F. et al. (eds) Highlights in Practical Applications of Agents, Multi-Agent Systems, and Trust-worthiness. The PAAMS Collection. PAAMS 2020. Communications in Computer and Information Science, vol 1233. Springer, Cham.

DOI: https://doi.org/10.1007/978-3-030-51999-5_25

» Intelligence as a Service: A Tool for Energy Forecasting and Security Awareness

Wannous S., Praça I., Andrade R. (2021) Intelligence as a Service: A Tool for Energy Forecasting and Security Awareness. In: De La Prieta F., El Bolock A., Durães D., Carneiro J., Lopes F., Julian V. (eds) Highlights in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Collection. PAAMS Workshops 2021. Communications in Computer and Information Science, vol 1472. Springer, Cham.

DOI: https://doi.org/10.1007/978-3-030-85710-3_15

Conference Papers

» Analysis and Simulation of Local Energy Markets

I. Praça, S. Ramos, R. Andrade, A. S. d. Silva and E. T. Sica, “Analysis and Simulation of Local Energy Markets,” 2019 16th International Conference on the European Energy Market (EEM), Ljubljana, Slovenia, 2019, pp. 1-5.

DOI: https://doi.org/10.1109/EEM.2019.8916524

» Classification of local energy trading negotiation profiles using artificial neural networks

A. Pinto, T. Pinto, I. Praça and Z. Vale, “Classification of local energy trading negotiation profiles using artificial neural networks,” 2019 IEEE Power & Energy Society General Meeting (PESGM), Atlanta, GA, USA, 2019, pp. 1-5.

DOI: https://doi.org/10.1109/PESGM40551.2019.8973600

» A MAS Simulation Model for Trusted Local Energy Markets

R. Andrade, T. Pinto, I. Praça, “A MAS Simulation Model for Trusted Local Energy Markets” 19th EPIA Conference on Artificial Intelligence, EPIA 2019, Vila Real, Portugal, September 3–6 (Poster presentation).

URL: https://epia2019.utad.pt/images/papers-baai/paper266.pdf

» LEMMAS: a secured and trusted Local Energy Market simulation system

Rui Andrade, João Vitorino, Sinan Wannous, Eva Maia & Isabel Praça, 18th International Conference on the European Energy Market (EEM), Ljubljana, Slovenia, 2022 (ACCEPTED).

URL: N/A

» Photovoltaic Generation Forecasting – A Case Study

S. Wannous, I. Praça, R. Andrade, S. Ramos, "ENERGY 2022, The Twelfth International Conference on Smart Grids, Green Communications, and IT Energy-aware Technologies", Venice, Italy, 2022, pp.36 – 41.

LINK: https://www.thinkmind.org/index.php?view=article&articleid=energy_2022_1_80_30043

Other

» A Multi-Agent System Simulation Model for Trusted Local Energy Markets

R. Andrade, T. Pinto, I. Praça, “A Multi-Agent System Simulation Model for Trusted Local Energy Markets” ISEP, Porto, Portugal, November 12, 2019 (Master Thesis).

URL: https://recipp.ipp.pt/handle/10400.22/15684

Awards

Electronics MDPI Best papers

Electronics MDPI

19th International Conference on Practical Applications of Agents and Multi-Agent Systems, Salamanca (Spain)
6th-8th October, 2021
https://www.paams.net
Trust Model for a Multi-Agent based simulation of Local Energy Markets. Rui Andrade, Tiago Pinto and Isabel Praça
More details here.

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