Hybrid Forecasting Methodology for Wind Power-Photovoltaic-Concentrating Solar Power Generation Clustered Renewable Energy Systems

Simian Pang,Zixuan Zheng,Xianyong Xiao,Lanlan Xu,Fan Luo

doi:10.3390/su13126681

Abstract

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.

Highlights

Ahmed et al [14] summarize the recent photovoltaic power forecasting (PVF) methods including physical, statistical, artificial intelligence, ensemble and hybrid approaches, the results show that the ensembles of artificial neural network (ANN) is most suitable for short-term PVF
The results show that this method is better than support vector machine (SVM) and other methods in wind power generation (WPG) forecasting
Wind Power-Photovoltaic-Concentrating Solar Power Cluster In concentrating solar power (CSP), wind power and PV power cluster, according to the local power characteristics and climate complementation, the establishment of wind and photovoltaic power cluster can effectively realize the complementary of wind and solar energy [29]

Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. As the energy crisis intensifies, renewable energy sources such as wind and solar energy as have been widely concerned. The world’s wind power generation in 2020 reached 733 GW which increased by 17.8% over 2019. The world’s solar power generation in 2020 reached 714 GW and increased by 21.6% over last year [1]. Both wind and photovoltaic (PV) power generation are fluctuant and intermittent

Methods

Results

Conclusion