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Short-term load forecast plays a vital role in the electric power industry. In this paper, a deep belief network is proposed for short-term load forecasting. However, the Back-Propagation (BP) algorithm of deep belief network for fine tuning has some inherent drawbacks and limitations, such as slow convergence rate and easy to fall into local minimum. To overcome the drawbacks, several neural network...
Considering the electricity price's volatility and various elements which affect the price in the electricity market, the paper presents hybrid model for the day-ahead electricity market clearing price forecasting. The paper adopts autoregressive moving average (ARMAX) model to reveal the linear relationship between power load and electricity price; the generalized autoregressive conditional heteroskedasticity...
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