Summary
Over the past few decades, the behavior of electricity consumption has been changing, especially because of improvements in the distributed generation segment and technological innovations presented by smart grids. The use of microgeneration and the availability of electricity pricing in real time allow consumers to control their consumption, or generation, according to market conditions. This new dynamic tends to increasingly change the price elasticity of electricity demand, by indicating the need to readjust load forecasting models. In this market environment, in addition to providing robust estimates for the planning and operation of electric power systems, load forecasting models have become fundamental in the context of demand management. Thus, this paper proposes to develop an artificial neural network and fuzzy logic for load forecasting to perform an efficiency analysis. This system is able to provide estimates of the elasticity of electricity demand behavior with more satisfactory results. To do so, improvements in the neural network with multilayer perceptron are proposed. In this case, the adaptation of parameters to correlate variations in consumption with the changes in electricity tariffs was developed. The addition of this new structure produced better results compared with the conventional neural network. Computer tests were conducted using historical data from the ISO New England Inc and PJM Interconnection. Price elasticity estimates of electricity demand showed a sharp increase of demand in relation to the elasticity behavior.
This paper exploits different computational modelling to assess long-term static and operating reserves to multi-area systems. To deal with intermittent renewable generation and other types of technologies, this paper is proposing a flexible simulation model able to capture not only technological innovation of power system components and their electric and energetic behaviors, but also operational procedures and market agreements representations to yield planning insights about the performance of the multi-area systems. Results based on two modified test systems with a variate of generation technologies and interconnections are used to show the potential of the simulation model.
A energia elétrica é um fatores mais importantes para o desenvolvimento econômico, político e social. Mas para que esta fonte continue sendo distribuída aos consumidores com segurança e qualidade, o sistema elétrico busca novos avanços fundamentados na tecnologia Smart Grid. Torna-se, portanto, de grande importância o estudo de métodos que simulem o comportamento de um sistema elétrico de potência. Neste sentido, o presente artigo tem como objetivo modelar um segmento da rede primária da concessionária municipal de energia de Ijuí – Demei. Dentre os modelos encontrados na literatura técnica, optou-se pelo modelo PI para representar a rede de distribuição de energia estudada. A escolha pelo PI justifica-se por se tratar de um modelo simples, de fácil compreensão e implementação computacional, mas que ao mesmo tempo, consegue captar as principais características de um sistema elétrico. Inicialmente definiu-se o trecho que seria modelado, denominado trecho AB e em seguida desenvolveu-se o processo experimental para a aquisição do conjunto de dados da pesquisa. Para obter estas informações, foram instalados analisadores de energia no segmento da rede da concessionária, previamente selecionado, adquirindo tensão, corrente e carga do sistema. Estas grandezas representam o sistema real e foram utilizados na implementação computacional do modelo e na sua validação. O modelo foi implementado na ferramenta computacional Matlab/Simulink. Os resultados das simulações comprovam que o modelo PI é capaz que simular com precisão o trecho analisado, uma vez que o erro médio encontrado entre o resultado da simulação computacional e os dados referente ao sistema real é inferior a 1%.
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