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Forecasting of large-scale renewable energy clusters composed of wind power generation, photovoltaic and concentrating solar power (CSP) generation encounters complex uncertainties due to spatial scale dispersion and time scale random fluctuation. In response to this, a short-term forecasting method is proposed to improve the hybrid forecasting accuracy of multiple generation types in the same region. It is formed through training the long short-term memory (LSTM) network using spatial panel data. Historical power data and meteorological data for CSP plant, wind farm and photovoltaic (PV) plant are included in the dataset. Based on the data set, the correlation between these three types of power generation is proved by Pearson coefficient, and the feasibility of improving the forecasting ability through the hybrid renewable energy clusters is analyzed. Moreover, cases study indicates that the uncertainty of renewable energy cluster power tends to weaken due to partial controllability of CSP generation. Compared with the traditional prediction method, the hybrid prediction method has better prediction accuracy in the real case of renewable energy cluster in Northwest China.

Values of site factors in numerical simulation can have profound effects on the calculation accuracy. In order to fully understand the performance of rigid-pile composite foundation in tall buildings, this article set up an overall FEA model of a 25-storey frame-tube structure by considering the interaction of superstructure, foundation and ground. Thereafter, a detailed parametric study was performed by changing values of different key site factors. These parameters include: Ground soil range, distance of neighboring buildings and deformation modulus of cushion. The results show that 1) Ground soil range has a great influence on the stress and settlement of raft, the effective influence range is 2-3 times of the raft dimension; 2) Influence of neighboring buildings on the stress and settlement of the raft can be neglected; 3) With the increase of cushion modulus, the raft stress increases while the settlement decreases, an optimal cushion modulus is recommended to be 20-40MPa.

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This paper adopts the finite element method (FEM)