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Publicações

Publicações por HumanISE

2019

Model Proposal to Evaluate the Quality of a Production Planning and Control Software in an Industrial Context

Autores
Goncalves, RMP; Varela, MLR; Madureira, AM; Putnik, GD; Machado, J;

Publicação
ADVANCES IN MANUFACTURING II, VOL 1 - SOLUTIONS FOR INDUSTRY 4.0

Abstract
The domain of Production Planning and Control, or in a broader sence Production Management has been deserving a special and increasing attention by the companies, which intend to continuously achieve better results through continuous improvement, which also fits in the context of Industry 4.0. Companies tend to implement management systems with the purpose of achieving greater competitiveness and, consequently, greater sustainability in their sector. The selection of the appropriate production management system is a serious problem for the companies. The main objective of this study is to support companies in the correct choice of a Decision Support System. The method used to achieve the proposed objective consists on formulating a model for comparing functionalities and specifications, where selection of criteria were also defined and analyzed. Based on a large Company scenario, the model is applied to three production execution systems: SAP PP (Systems Applications and Products - Production Planning), Prodsmart and GenSYS.

2019

Dynamic electricity tariff definition based on market price, consumption and renewable generation patterns

Autores
Ribeiro, C; Pinto, T; Faria, P; Ramos, S; Vale, Z; Baptista, J; Soares, J; Navarro Caceres, M; Corchado, JM;

Publicação
Clemson University Power Systems Conference, PSC 2018

Abstract
The increasing use of renewable energy sources and distributed generation brought deep changes in power systems, namely with the operation of competitive electricity markets. With the eminent implementation of micro grids and smart grids, new business models able to cope with the new opportunities are being developed. Virtual Power Players are a new type of player, which allows aggregating a diversity of entities, e.g. generation, storage, electric vehicles, and consumers, to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players' benefits. In order to achieve this objective, it is necessary to define tariff structures that benefit or penalize agents according to their behavior. In this paper a method for determining the tariff structures has been proposed, optimized for different load regimes. Daily dynamic tariff structures were defined and proposed, on an hourly basis, 24 hours day-Ahead from the characterization of the typical load profile, the value of the electricity market price and considering the renewable energy production. © 2018 IEEE.

2019

Adaptive entropy-based learning with dynamic artificial neural network

Autores
Pinto, T; Morais, H; Corchado, JM;

Publicação
Neurocomputing

Abstract

2019

Hybrid approach based on particle swarm optimization for electricity markets participation

Autores
Faia, R; Pinto, T; Vale, ZA; Corchado, JM;

Publicação
Energy Inform.

Abstract

2019

Identifying Most Probable Negotiation Scenario in Bilateral Contracts with Reinforcement Learning

Autores
Silva, F; Pinto, T; Praça, I; Vale, ZA;

Publicação
New Knowledge in Information Systems and Technologies - Volume 1, World Conference on Information Systems and Technologies, WorldCIST 2019, Galicia, Spain, 16-19 April, 2019

Abstract

2019

Collaborative Reinforcement Learning of Energy Contracts Negotiation Strategies

Autores
Pinto, T; Praça, I; Vale, ZA; Santos, C;

Publicação
Highlights of Practical Applications of Survivable Agents and Multi-Agent Systems. The PAAMS Collection - International Workshops of PAAMS 2019, Ávila, Spain, June 26-28, 2019, Proceedings

Abstract

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