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Publicações

Publicações por HumanISE

2013

Metalearner Based on Dynamic Neural Network for Strategic Bidding in Electricity Markets

Autores
Pinto, T; Sousa, TM; Barreira, E; Praça, I; Vale, ZA;

Publicação
DEXA Workshops

Abstract

2013

Electricity Markets Portfolio Optimization Using a Particle Swarm Approach

Autores
Guedes, N; Pinto, T; Vale, ZA; Sousa, TM; Sousa, T;

Publicação
DEXA Workshops

Abstract

2013

Upper Ontology for Multi-Agent Energy Systems' Applications

Autores
Santos, G; Pinto, T; Vale, ZA; Morais, H; Praça, I;

Publicação
DCAI

Abstract

2013

Adaptive Learning in Games: Defining Profiles of Competitor Players

Autores
Pinto, T; Vale, ZA;

Publicação
DCAI

Abstract

2013

Strategic bidding in electricity markets: An agent-based simulator with game theory for scenario analysis

Autores
Pinto, T; Praça, I; Vale, Z; Morais, H; Sousa, TM;

Publicação
INTEGRATED COMPUTER-AIDED ENGINEERING

Abstract
Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players' actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

2013

Intelligent remuneration and tariffs for virtual power players

Autores
Ribeiro, C; Pinto, T; Morais, H; Vale, Z; Santos, G;

Publicação
2013 IEEE Grenoble Conference PowerTech, POWERTECH 2013

Abstract
Power systems have been through deep changes in recent years, namely due to the operation of competitive electricity markets in the scope the increasingly intensive use of renewable energy sources and distributed generation. This requires new business models able to cope with the new opportunities that have emerged. Virtual Power Players (VPPs) are a new type of player that allows aggregating a diversity of players (Distributed Generation (DG), Storage Agents (SA), Electrical Vehicles (V2G) 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. A major task of VPPs is the remuneration of generation and services (maintenance, market operation costs and energy reserves), as well as charging energy consumption. This paper proposes a model to implement fair and strategic remuneration and tariff methodologies, able to allow efficient VPP operation and VPP goals accomplishment in the scope of electricity markets. © 2013 IEEE.

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