Publications

Publications by HumanISE

2018

Demonstration of Tools Control Center for Multi-agent Energy Systems Simulation

Authors
Teixeira, B; Silva, F; Pinto, T; Santos, G; Praça, I; Vale, ZA;

Publication
Advances in Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection - 16th International Conference, PAAMS 2018, Toledo, Spain, June 20-22, 2018, Proceedings

Abstract

2018

Multi-agent Systems Society for Power and Energy Systems Simulation

Authors
Santos, G; Pinto, T; Vale, ZA;

Publication
Multi-Agent-Based Simulation XIX - 19th International Workshop, MABS 2018, Stockholm, Sweden, July 14, 2018, Revised Selected Papers

Abstract

2018

Electricity Price Forecast for Futures Contracts with Artificial Neural Network and Spearman Data Correlation

Authors
Nascimento, J; Pinto, T; Vale, ZA;

Publication
Distributed Computing and Artificial Intelligence, 15th International Conference, DCAI 2018, Toledo, Spain, 20-22 June 2018, Special Sessions I.

Abstract

2018

UCB1 Based Reinforcement Learning Model for Adaptive Energy Management in Buildings

Authors
Andrade, R; Pinto, T; Praça, I; Vale, ZA;

Publication
Distributed Computing and Artificial Intelligence, 15th International Conference, DCAI 2018, Toledo, Spain, 20-22 June 2018, Special Sessions I.

Abstract

2018

A New Hybrid-Adaptive Differential Evolution for a Smart Grid Application Under Uncertainty

Authors
Lezama, F; Soares, JP; Faia, R; Pinto, T; Vale, ZA;

Publication
2018 IEEE Congress on Evolutionary Computation, CEC 2018, Rio de Janeiro, Brazil, July 8-13, 2018

Abstract

2018

Decision Support for Negotiations among Microgrids Using a Multiagent Architecture

Authors
Pinto, T; Ghazvini, MAF; Soares, J; Faia, R; Corchado, JM; Castro, R; Vale, Z;

Publication
ENERGIES

Abstract
This paper presents a decision support model for negotiation portfolio optimization considering the participation of players in local markets (at the microgrid level) and in external markets, namely in regional markets, wholesale negotiations and negotiations of bilateral agreements. A local internal market model for microgrids is defined, and the connection between interconnected microgrids is based on nodal pricing to enable negotiations between nearby microgrids. The market environment considering the local market setting and the interaction between integrated microgrids is modeled using a multi-agent approach. Several multi-agent systems are used to model the electricity market environment, the interaction between small players at a microgrid scale, and to accommodate the decision support features. The integration of the proposed models in this multi-agent society and interaction between these distinct specific multi-agent systems enables modeling the system as a whole and thus testing and validating the impact of the method in the outcomes of the involved players. Results show that considering the several negotiation opportunities as complementary and making use of the most appropriate markets depending on the expected prices at each moment allows players to achieve more profitable results.

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