Utilização de árvores de regressão híbridas na monitorização da segurança dinâmica de redes isoladas com grande produção eólica

Neste artigo descreve-se de forma sintética a metodologia adoptada para definir estruturasde avaliação rápida da segurança dinâmica de redes isoladas com elevados níveis deintegração de produção eólica. Estas metodologia recorre a árvores de regressão híbridas,permitindo quantificar o grau de robustez ligado ao comportamento dinâmico destas redesatravés da emulação do desvio mínimo de frequência que o sistema experimentará quandosujeito a uma perturbação pré-definida. Apresentam-se ainda novos procedimentos degeração automática de dados, explorados posteriormente na construção e medição dedesempenho das estruturas de avaliação. O caso teste aqui descrito corresponde a umcenário de funcionamento da rede da ilha Terceira no arquipélago dos Açores

ANN design for fast security evaluation of interconnected systems with large wind power production

This paper presents the performed steps to design an Artificial Neural Network (ANN) tool, able to evaluate, within the framework of on-line security assessment, the dynamic security of interconnected power systems having an increased penetration of wind power production. This approach exploits functional knowledge generated off-line, the Linear Regression (LR) variable selection stepwise method to perform automatic Feature Subset Selection (FSS) and ANN to provide a way for fast evaluation of the system security degree. In order to choose the best input/output set of variables for the ANN tool, a comparative analysis is performed, regarding the obtained predicting error, by performing a statistical hypothesis test. The reduced error results confirm the feasibility and quality of the derived security structures

On-line functions for security operation of interconnected systems having large wind power production

This paper presents a methodology for the implementation of new EMS tools aiming to assist, in real time, transmission system operators to avoid dynamic security problems, after short-circuits that may lead to large wind power losses. In order to overcome high computational efforts, that are required by conventional dynamic simulation tools, the proposed methodology was developed using automatic learning techniques. The quality of this approach is demonstrated by the results that were provided to solve a security problem of an interconnected test system

Security evaluation of interconnected systems with large wind power production using artificial intelligence systems

This paper presents a new methodology to evaluate, within the framework of on-line security assessment, the dynamic behavior of interconnected power systems having an increased penetration of wind power production. This approach exploits functional knowledge generated off-line, the Regression Tree (RT) automatic learning method to perform Feature Subset Selection (FSS) and Artificial Neural Networks (ANN) to provide a way for fast evaluation of the security degree

Security assessment of interconnected systems having large wind power production

This paper presents a new methodology to assess security of interconnectedsystems that have a large penetration of wind power production, through the evaluation of theimpacts in the transmission lines of one control area following a sudden loss of wind powerproduction. This approach exploits functional knowledge generated off-line and artificialneural networks to provide a way for fast evaluation of the security degree

Estudos de impacto eléctrico da integração de produção eólica adicional nas redes eléctricas da República de Cabo Verde : caso de Santiago

Neste artigo descreve-se de forma sintética a metodologia adoptada para a realização de umconjunto de estudos de comportamento estacionário e dinâmico com o objectivo de avaliar oimpacto, nas redes eléctricas das ilhas de S. Vincente, Santiago e Sal decorrente do aumento dacapacidade de produção eólica, para um cenário de exploração correspondente ao ano de 1998. Oaumento considerado traduziu-se na expansão dos parques eólicos existentes em exploraçãodesde 1994. O caso de estudo descrito corresponde ao da ilha de Santiago. Relativamente a estarede, apresentam-se ainda os principais resultados obtidos

Projecto e exploração de parques eólicos com geradores assíncronos na sequência da aplicação da nova legislação

Neste artigo descreve-se sucintamente o tipo deproblemas de exploração que os parques eólicos,dotados de geradores assíncronos, passam a enfrentarna sequência da aplicação da nova legislação relativaaos produtores independentes. Tal situação implica aadopção de uma cuidada metodologia de análise eprojecto para proceder ao dimensionamento de bateriasde condensadores suplementares, a colocar em serviçona instalação de produção. Este dimensionamento deveser acompanhado de um conjunto de medidas decarácter técnico que se descrevem neste artigo

Dynamic security assessment by fuzzy inference

This paper reports an experience on the application of fuzzy reasoning to the fast assessment of the dynamicsecurity of an isolated power system with high wind power penetration. The inference method is a TakagiSugenotype system with a small number of rules, optimized for each specific learning set by a standard methodincluded in the MATLAB Fuzzy Logic Toolbox. The methodology is demonstrated in a contingency study in thenetwork of Crete that showed good results in the test set. The paper discusses some implementation issues andpossible future developments of the approach

The future of power systems: Challenges, trends, and upcoming paradigms

The decarbonization of the economy, for which the contribution of power systems is significant, is a growing trend in Europe and in the world. In order to achieve the Paris Agreement's ambitious environmental goals, a substantial increase in the contribution of renewable sources to the energy generation mix is required. This trend brings about relevant challenges as the integration of this type of sources increases, namely in terms of the distribution system operation. In this paper, the challenges foreseen for future power systems are identified and the most effective approaches to deal with them are reviewed. The strategies include the development of Smart Grid technologies (meters, sensors, and actuators) coupled with computational intelligence that act as new sources of data, as well as the connection of distributed energy resources to distribution grids, encompassing the deployment of distributed generation and storage systems and the dissemination of electric vehicles. The impact of these changes in the distribution system as a whole is evaluated from a technical and environmental perspective. In addition, a review of management and control architectures designed for distribution systems is conducted. This article is categorized under: Energy Infrastructure > Systems and Infrastructure Energy Infrastructure > Economics and Policy.ERDF - European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme, and by National Funds through the Portuguese funding agency, FCT - Fundacao para a Ciencia e a Tecnologia, Grant/Award Number: SAICTPAC/0004/2015-POCI-01-0145-FEDER-01643

On-line dynamic security assessment of isolated networks integrating large wind power production

The paper describes the on-line dynamic security assessment functions developed within the European Union, DGXII programme, CARE. These functions are based exclusively on the application of machine learning techniques. A description of the problem and the data set generation procedure for the Crete island power system are included. Comparative results regarding performances of Decision Trees, Kernel Regression Trees and Neural Networks are presented and discussed.The paper describes the on-line dynamic security assessment functions developed within the European Union, DGXII programme, CARE. These functions are based exclusively on the application of machine learning techniques. A description of the problem and the data set generation procedure for the Crete island power system are included. Comparative results regarding performances of Decision Trees, Kernel Regression Trees and Neural Networks are presented and discussed