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

Metalearner Based on Dynamic Neural Network for Strategic Bi...

引用

International Workshop on Database and Expert Systems Applications

作者： Tiago Pinto Tiago M. Sousa Elisa Barreira Isabel Praça Zita Vale GECAD-Knowledge Engineering and Decision Support Research Center (ISEP IPP) Polytechnic of Porto Porto Portugal

The restructuring of electricity markets, conducted to increase the competition in this sector, and decrease the electricity prices, brought with it an enormous increase in the complexity of the considered mechanisms. The electricity market became a complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. Software tools became, therefore, essential to provide simulation and decision support capabilities, in order to potentiate the involved players' actions. This paper presents the development of a metalearner, applied to the decision support of electricity markets' negotiation entities. The proposed metalearner executes a dynamic artificial neural network to create its own output, taking advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that provides decision support to electricity markets' players. The proposed metalearner considers different weights for each strategy, depending on its individual quality of performance. The results of the proposed method are studied and analyzed in scenarios based on real electricity markets' data, using MASCEM - a multi-agent electricity market simulator that simulates market players' operation in the market.

关键词： Artificial neural networks Electricity supply industry Learning (artificial intelligence) Heuristic algorithms Proposals Adaptive systems Training

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Multi-Agent Based Smart Grid Management and Simulation: Situation Awareness and Learning in a Test Bed with Simulated and Real Installations and Players

Multi-Agent Based Smart Grid Management and Simulation: Situ...

引用

IEEE Power and Energy Society General Meeting

作者： Hugo Morais Zita Vale Tiago Pinto Luis Gomes Filipe Fernandes Pedro Oliveira Carlos Ramos GECAD - Knowledge Engineering and Decision Support Research Center IPP - Polytechnic Institute of Porto Porto Portugal

ISBN: (纸本)9781479913022

The rising usage of distributed energy resources has been creating several problems in power systems operation. Virtual Power Players arise as a solution for the management of such resources. Additionally, approaching the main network as a series of subsystems gives birth to the concepts of smart grid and micro grid. Simulation, particularly based on multi-agent technology is suitable to model all these new and evolving concepts. MASGriP (Multi-Agent Smart Grid simulation Platform) is a system that was developed to allow deep studies of the mentioned concepts. This paper focuses on a laboratorial test bed which represents a house managed by a MASGriP player. This player is able to control a real installation, responding to requests sent by the system operators and reacting to observed events depending on the context.

关键词： Curtailment Service Providers Microgrids Multi-Agent Systems Smart grids Virtual Power Players Smart grids Multi-agent systems simulating Players test bed MICRO-GRID distributed energy resources Installations

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Intelligent remuneration and tariffs for virtual power players

Intelligent remuneration and tariffs for virtual power playe...

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Power Tech Conference

作者： Catarina Ribeiro Tiago Pinto Hugo Morais Zita Vale Gabriel Santos GECAD - Knowledge Engineering and Decision Support Research Center IPP - Polytechnic Institute of Porto Porto Portugal

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.

关键词： Remuneration Electricity supply industry Contracts Analytical models Distributed power generation Power systems Context

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Demand response programs definition using demand price elasticity to define consumers aggregation for an improved remuneration structure

Demand response programs definition using demand price elast...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Pedro Faria Zita Vale GECAD - Knowledge Engineering and Decision Support Research Center IPP - Polytechnic Institute of Porto Porto Portugal

ISBN: (纸本)9781479929856

The positioning of the consumers in the power systems operation has been changed in the recent years, namely due to the implementation of competitive electricity markets. Demand response is an opportunity for the consumers' participation in electricity markets. Smart grids can give an important support for the integration of demand response. The methodology proposed in the present paper aims to create an improved demand response program definition and remuneration scheme for aggregated resources. The consumers are aggregated in a certain number of clusters, each one corresponding to a distinct demand response program, according to the economic impact of the resulting remuneration tariff. The knowledge about the consumers is obtained from its demand price elasticity values. The illustrative case study included in the paper is based on a 218 consumers' scenario.

关键词： Remuneration Elasticity Electricity Load management Optimization Smart grids Clustering algorithms

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Modified discrete PSO to increase the delivered energy probability in distribution energy systems

Modified discrete PSO to increase the delivered energy proba...

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IEEE Symposium on Computational Intelligence Applications In Smart Grid (CIASG)

作者： Bruno Canizes João Soares Hugo Morais Zita Vale GECAD-Knowledge Engineering and Decision-Support Research Centre ISEP Polytechnic of Porto Porto Portugal

This paper proposes a PSO based approach to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The statistical failure and repair data of distribution components is the main basis of the proposed methodology that uses a fuzzy-probabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A Modified Discrete PSO optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

关键词： Maintenance engineering Investment Optimization Equations Mathematical model Load modeling Reliability

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Adapting meeting tools to agent decision

Adapting meeting tools to agent decision

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IEEE Workshop on Evolving and Adaptive Intelligent Systems (EAIS)

作者： João Barreto Isabel Praça Tiago Pinto Tiago M. Sousa Zita Vale GECAD-Knowledge Engineering and Decision Support Research Center Institute of Engineering ISEP IPP Polytechnic Institute of Porto Porto Portugal

Electricity markets are complex environments comprising several negotiation mechanisms. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. ALBidS (Adaptive Learning Strategic Bidding System) is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM it considers several different methodologies based on very distinct approaches. The Six Thinking Hats is a powerful technique used to look at decisions from different perspectives. This paper aims to complement ALBidS strategies usage by MASCEM players, providing, through the Six Thinking Hats group decision technique, a means to combine them and take advantages from their different perspectives. The combination of the different proposals resulting from ALBidS' strategies is performed through the application of a Genetic Algorithm, resulting in an evolutionary learning approach.

关键词： Genetic algorithms Companies Electricity supply industry Electricity Multi-agent systems Sociology

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Application of Fuzzy Fractional PD+I Controllers Tuned by a Genetic Algorithm

Application of Fuzzy Fractional PD+I Controllers Tuned by a ...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Isabel S. Jesus Ramiro S. Barbosa GECAD - Knowledge Engineering and Decision Support Research Center Institute of Engineering/Polytechnic of Porto (ISEP/IPP) Dept. of Electrical Engineering

ISBN: (纸本)9781479902255

The fractional order concepts are a useful tool to describe several physical phenomena, and nowadays widely used in the field of automatic control. In this paper we consider the development of an optimal fuzzy fractional PD+I controller in which the parameters are tuned by a Genetic Algorithm (GA). The performance of the proposed fuzzy fractional control is illustrated through two application examples.

关键词： Approximation methods Zirconium PD control Genetic algorithms Fuzzy logic Optimization

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Comparative Study of Fuzzy Integer and Fractional PID Controller

Comparative Study of Fuzzy Integer and Fractional PID Contro...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Ramiro S. Barbosa Isabel S. Jesus GECAD - Knowledge Engineering and Decision Support Research Center Dept. of Electrical Engineering ISEP/IPP - School of Engineering Polytechnic Institute of Porto

ISBN: (纸本)9781479902255

This paper makes a comparative study between fuzzy integer and fractional PID controllers. A novel fuzzy fractional PID is proposed. A methodology for tuning the fuzzy controllers is also presented. The effectiveness and robustness of the proposed approach is illustrated through its application on the control of a fractional-order plant.

关键词： PD control Iron Robustness Tuning Equations Fuzzy logic

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Increase of the delivered power probability in distribution networks using Pareto DC programming

Increase of the delivered power probability in distribution ...

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IEEE General Meeting Power& Energy Society

作者： Bruno Canizes João Soares Zita Vale Cristina Lobo GECAD - Knowledge Engineering and Decision-Support Research Centre Polytechnic of Porto (ISEP/IPP) Porto Portugal

A methodology to increase the probability of delivering power to any load point through the identification of new investments in distribution network components is proposed in this paper. The method minimizes the investment cost as well as the cost of energy not supplied in the network. A DC optimization model based on mixed integer non-linear programming is developed considering the Pareto front technique in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power for any customer in the distribution system at the minimum possible cost for the system operator, while minimizing the energy not supplied cost. Thus, a multi-objective problem is formulated. To illustrate the application of the proposed methodology, the paper includes a case study which considers a 180 bus distribution network.

关键词： Reliability Maintenance engineering Investment Power system reliability Optimization Power cables

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Multi-objective parallel particle swarm optimization for day-ahead Vehicle-to-Grid scheduling

Multi-objective parallel particle swarm optimization for day...

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IEEE Symposium on Computational Intelligence Applications In Smart Grid (CIASG)

作者： João Soares Zita Vale Bruno Canizes Hugo Morais GECAD-Knowledge Engineering and Decision-Support Research Center (ISEP IPP) Polytechnic of Porto Porto Portugal Danmarks Tekniske Universitet Lyngby DK

This paper presents a methodology for multi-objective day-ahead energy resource scheduling for smart grids considering intensive use of distributed generation and Vehicle-To-Grid (V2G). The main focus is the application of weighted Pareto to a multi-objective parallel particle swarm approach aiming to solve the dual-objective V2G scheduling: minimizing total operation costs and maximizing V2G income. A realistic mathematical formulation, considering the network constraints and V2G charging and discharging efficiencies is presented and parallel computing is applied to the Pareto weights. AC power flow calculation is included in the metaheuristics approach to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance of the proposed method.

关键词： Vehicles Discharges (electric) Partial discharges Batteries Load flow Distributed power generation Mathematical model

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