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Title |
Coordinated Operation of Wind Farms, Cascaded Hydro, Photo-voltaic and Pump-storage Units by WT-ANN-ICA Prediction Method for WFPG |
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Author |
Ehsan Jafari, Soodabeh Soleymani, and Babak Mozafari |
| Citation |
Vol. 25 No. 4 pp. 143-154 |
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Abstract |
In this paper, it is presented a new algorithm to reduce the uncertainty effect of wind farms power generation (WFPG) and photo-voltaic generation (PVG) in a day-ahead energy and ancillary services market. First, it is tried to predict the uncertainty of the WFPG precisely. So it has been used of the hybrid method (HM) of wavelet transform (WT) in order to reduce the fluctuations in the input historical data, of the improved artificial neural network (ANN) based on the nonlinear structure for better training and learning and of imperialist competitive algorithm (ICA) in order to find the best weights and biases for minimizing the mean square error (MSE) of prediction. Then, considering high-level penetration of wind farms (WF) on the power system cascaded hydro units (CHU) and pump-storage units (PSU) were used as coordinated operation and supplementary units for WF and photo-voltaic (PV) resources. The uncertainty of energy price, spinning and non-spinning reserve in the electricity market, WFPG, and PVG causes that this problem be a scenario-based stochastic optimization one. The aim of this problem is to increase the profit and decrease the financial risk (FR) of all of the units. The proposed method tested on WF, CHU, PV and PSU of IEEE 118-bus standard system. Studying the result of profit and FR in the coordinated operation (CO) and the independent operation (IO) confirms to increase the profit and decrease the FR in the CO and the ability of the HM of WT-ANN-ICA. |
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Keywords |
Wind farms, Expected profit, Cascaded hydro, Photo-voltaic and Pump-storage units. |
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