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Absrraa -Electric energy demand forecasting represents a fundamental information to plan the activities of the companies that generate and distribute it. So a good prediction of its demand will provide an invaluable tool to plan the production and purchase policies of both generation and distribution or reseller companies. This demand may be seen as a temporal series when its data are conveniently arranged. In this way the prediction of a future value may be performed stud,ying the past ones. Neural networks have proved to be a very powerful tool to do this. They are mathematical structures thalt mimic that of the nervous system of living beings and are used extensively for system identification and prediction of their future evolution. In this work a neural network is presented1 to predict the evolution of the monthly demand of electric consumption. A Feedforward Multilayer Perceptron (MLP) has been used as neural model with Backpropagation as learning strategy. The network has three hidden layers with a 8-4-8 distribution. It takes twelve past values to predict the following one. Errors smaller than 5% have been obtained in most of the predictions.

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Abstract. Photovoltaic (PV) systems are increasingly present in the electrical distribution systems due to the governments incentives and low production costs of a developed PV technology. This paper summarizes the measurements on power quality (PQ) parameters carried out in a radial distribution network in two periods of time, before and after connecting a PV plant to the grid, and also shows the same parameters measured in the point of common coupling (PCC) of the grid and PV plant in order to discuss about how the impedance of the grid and ratio between injected power and power demanded by the load may influence changes on the PQ of the distribution system. Some measured values are compared with the limits set in the international standards. This paper assesses the impact of PV generation on the distribution system and important issues such as reverse power flow and harmonic distortion are analyzed.

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