Autors: Ekonomou, L., Christodoulou, C.A., Mladenov, V. M.
Title: A short-term load forecasting method using artificial neural networks and wavelet analysis
Keywords: Artificial neural networks; Back-propagation algorithm; Deno

Abstract: Load forecasting is an issue of great importance for the reliable operation of the electric power system grids. Various forecasting methodologies have been proposed in the international research bibliography, following different models and mathematical approaches. A precise electric load forecasting results in cost saving and secure operational conditions. Moreover, it can also be helpful in power supply strategy, market research and financing planning. In the current work a methodology based on artificial neural networks methods reinforced by an appropriate wavelet denoising algorithm is implemented, in order to obtain shortterm load forecasting. Real recoded data obtained from the Bulgarian power system grid was used in the analysis. The extracted outcomes indicate the effectiveness of the proposed method, reducing the relative error between real and theoretical data.

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    International Journal of Power Systems, issue 1, pp. 64-68, 2016, France, IARAS, ISBN ISSN: 2367-8976

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