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In the electricity market, the price as the lever results in the dramatic variations, especially, the capacity or willingness of electricity consumers and then demand may be low, particularly over short time frames. Therefore demand-side management (DSM) has been put into practice, and the market supervisors become more and more focused on the price dynamics of the short-term, because of its effects...
There are some small-sample cases in economic forecast, for lacking of quantitative information, in which it happens that some given forecasting method fits well while behaves badly in forecasting, while to the contrary, the situation behaves well when we make the combination of both qualitative and quantitative methods in forecasting. The concept of risk of forecasting is defined, as well as the...
This paper proposes a method based on the recursive neural network rather than the usual BP algorithm. A three-layer BP network structure with input layer, hidden layer, and output layer is used. The inputs are resistance leak current of continuous time sequence, and the values behind are outputs; after the training and learning according to the recursive neural network algorithm, the state forecast...
There is a general consensus that the movement of electricity price is crucial for electricity market. As a practical tool to estimate the future prices, electricity price forecaster is of great importance and use for the operations of market participants. This paper presents a hybrid forecast model that integrates clustering algorithm with least square support vector machine (LS-SVM). First, clustering...
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