It can be found that the volatility index of Wind-PV co-generation power output is generally around 10%.
Open image in new window Fig. 9 Comparison of volatility It can be found that the volatility index of Wind-PV co-generation power output is generally around 10%.
j, t, k, s are the indices of wind farms, time points, battery energy storage, scenarios, respectively.
Probability densities of specific grid points are obtained by inverse discrete cosine transformation and are further used to calculate assessment indices of wind resources.
Fig. 9 draws the volatility index α of Wind-PV-ES co-generation power output before and after smoothing.
The scenarios, intervals, and risk index for the descriptions of wind power forecast errors were introduced in [9], and it is argued that forecast errors are inevitable and not negligible because of the stochastic nature of wind speed and the parameter uncertainties in the practical wind power curve.
In another word, the wind power density estimation was not a perfect index for wind power production, since it merely rely on the average wind speed and was not able to account for the features of the wind turbines.
Table 3 The advantages and corresponding indexes of the optimization method Advantages Stabilize the output of thermal units Shave the peak load Reduce the curtailment of wind power Indexes The Start-Stop times of thermal units The difference between Peak and Valley The wind curtailment.
To provide an index of the strength of wind forcing in the days prior to hydrographic sampling, we calculated time series of the 4-d cumulative mean daily wind stress (CWS).
