Percorrer por autor "Pinto, Angelo"
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- Automated combination of bilateral energy contracts negotiation tacticsPublication . Pinto, Angelo; Pinto, Tiago; Silva, Francisco; Praça, Isabel; Vale, Zita; Corchado, Juan ManuelThis paper addresses the theme automated bilateral negotiation of energy contracts. In this work, the automatic combination between different negotiation tactics is proposed. This combination is done dynamically throughout the negotiation process, as result from the online assessment that is performed after each proposal and counter-proposal. The proposed method is integrated in a decision support system for bilateral negotiations, called Decision Support for Energy Contracts Negotiations (DECON), which in turn is integrated with the Multi-Agent Simulator of Competitive Electricity Markets (MASCEM). This integration enables testing and validating the proposed methodology in a realistic market negotiation environment. A case study is presented, demonstrating the advantages of the proposed approach.
- Classification of local energy trading negotiation profiles using artificial neural networksPublication . Pinto, Angelo; Pinto, Tiago; Praça, Isabel; Vale, ZitaElectricity markets are evolving into a local trading setting, which makes it for unexperienced players to achieve good agreements and obtain profits. One of the solutions to deal with this issue is to provide players with decision support solutions capable of identifying opponents' negotiation profiles, so that negotiation strategies can be adapted to those profiles in order to reach the best possible results from negotiations. This paper presents an approach that classifies opponents' proposals during a negotiation, to determine which is the typical negotiation profile in which the opponent most relates. The classification process is performed using an artificial neural network approach, and it is able to adapt at each new proposal during the negotiation process, by re-classifying the opponents' negotiation profile according to the most recent actions. In this way, effective decision support is provided to market players, enabling them to adapt the negotiation strategy throughout the negotiations.
- Clustering-based negotiation profiles definition for local energy transactionsPublication . Pinto, Angelo; Pinto, Tiago; Praça, Isabel; Vale, Zita; Faria, PedroElectricity markets are complex and dynamic environments, mostly due to the large scale integration of renewable energy sources in the system. Negotiation in these markets is a significant challenge, especially when considering negotiations at the local level (e.g., between buildings and distributed energy resources). It is essential for a negotiator to be able to identify the negotiation profile of the players with whom he is negotiating. If a negotiator knows these profiles, it is possible to adapt the negotiation strategy and get better results in a negotiation. In order to identify and define such negotiation profiles, a clustering process is proposed in this paper. The clustering process is performed using the kml-k-means algorithm, in which several negotiation approaches are evaluated in order to identify and define players' negotiation profiles. A case study is presented, using as input data, information from proposals made during a set of negotiations. Results show that the proposed approach is able to identify players' negotiation profiles used in bilateral negotiations in electricity markets.