An hybrid approach based on neural networks and regression Tree Models for fast dynamic security assessment

This paper presents a new hybrid automatic learningapproach, which combines artificial neural networks (ANN) andregression trees (RT), to perform on-line dynamic securityassessment of power systems. In the proposed method, the RT isfirstly used to split the vast amount of knowledge data that describesa security problem into several less spread and disjoint problems.Then, an ANN is trained for each of these new smaller problems,resulting in a tree structure with an ANN predicting functionassociated to each leaf. Moreover, the capability of the RT to performfeature subset selection before ANN training is also tested. With thisnew method, the advantages of the two techniques are exploited inorder to obtained a more accurate model without compromisingprediction time. The quality of the approach is illustrated through itsapplication to a major security problem of the power system ofMadeira Island (Portugal)

Control Room Requirements for Voltage Control in Future Power Systems

In future power grids, a large integration of renewable energy sources is foreseen, which will impose serious technical challenges to system operators. To mitigate some of the problems that renewable energy sources may bring, new voltage and frequency control strategies must be developed. Given the expected evolution of technologies and information systems, these new strategies will benefit from increasing system observability and resources controllability, enabling a more efficient grid operation. The ELECTRA IRP project addressed the new challenges that future power systems will face and developed new grid management and control functionalities to overcome the identified problems. This work, implemented in the framework of ELECTRA, presents an innovative functionality for the control room of the cell operator and its application in assistance with the voltage control designed for the Web-of-Cells. The voltage control method developed uses a proactive mode to calculate the set-points to be sent to the flexible resources, each minute, for a following 15-min period. This way, the voltage control method developed is able to mitigate voltage problems that may occur, while, at the same time, contributes to reduce the energy losses. To enable a straightforward utilization of this functionality, a user interface was created for system operators so they can observe the network state and control resources in a forthright manner accordingly.The work presented in this paper was funded by the ELECTRA IRP project (Seventh Framework Programme FP7 2007/2013) under grant agreement No. 609687

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

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

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

Flywheel sizing for the secure operation of an isolated network with a high level of variable generation

This paper presents the methodology followed for sizing a flywheel energy storage system (FESS), in order to prevent frequency stability problems in an isolated network with an increased production of renewable generation. The analyzed case study is a real isolated power system that includes diesel, wind and photovoltaic solar generation. In the proposed methodology, the flywheel sizing is obtained from performing dynamic simulations of the power system, considering foreseen wind and photovoltaic power variations, namely a severe major power loss or frequent and short-term typical fluctuations. The obtained results demonstrate that the dimensioned FESS, with a proper choice of the control parameter values, provides the necessary control action to avoid security problems in the analyzed power system. They also reveal that in order to obtain an efficient FESS operation, for different types or severity level of expected renewable disturbances, the amount of FESS stored energy and the values of the FESS control parameter must be adapted on line, by following the suggestions of intelligent control algorithms

A general approach for security monitoring and preventive control of networks with large wind power production

This paper provides a description of thedevelopment of software tools able to deal with system fastdynamic monitoring and determination of preventivecontrol procedures, for a given set of disturbances, innetworks with large integration of wind power production.Preventive control is performed through powerredispatches, involving also the on/off control of the windgenerators. The quality of the approach is illustrated herethrough its application to the system of the Madeira island

Pruning kernel regression trees for security assessment of the Crete network

This paper presents the capabilities provided by Kernel Regression Trees - a hybrid non-parametricregression technique - to on-line dynamic security assessment and monitoring of isolated power systems withhigh penetration of wind power. In the applied technique, to avoid overfitting a pruning algorithm is used toextract the security structure. This approach, which is demonstrated on the electrical power system of Creteisland, proved to extract simple, interpretable, and reliable security structures. A description of the securityproblem and the data set generation procedure are included. Comparative results regarding performances ofRegression Trees and Decision Trees are presented and discussed