Electricity production from solar power plants is characterised by volatility, which presents a challenge in the management of electrical grids. A new approach was developed in order to improve the predictive results of the energy production of solar power plants. The latter uses a different number of included neighbouring power plants in the energy forecast of the central power plant. The dependence of the predictive results depends more on the number of neighbouring power plants included, than on the topology of the network. We performed the optimisation of the model's hyperparameters and compared the predictive results with the existing research. We found out, that not using meteorological data results in worse forecasting results.
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