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To improve the accuracy of load forecasting, a new algorithm is presented to forecast the short-term load. In the paper, short-time load sequence of the power supply system composed by different frequency signals is decomposed into the signals on different frequency bands by wavelets. Then the Radial Basis Function neural network (RBFNN) is used to forecast these signals in every scale space, and...
Short-term load forecasting is important for the economic and secure operation of power system. Taking the random disturbances, especially the meteorological factors into account are the key to improve forecasting precision. This paper presents ant colony clustering model to process the historical load days. Ants pick or drop samples decided by the similarity of it to its surroundings. After iterative...
With the development of power markets, electricity price especially the market clearing price (MCP) forecasting is becoming more and more important in such new competitive markets since the MCP forecasting is the basis of decision making for participants in electricity market. In this paper the problem of modeling market clearing price forecasting in deregulated markets is studied. And electricity...
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