Application of Urban Solar Power Prediction on Controlling a Stand-alone PV-Battery Hybrid System

摘要

With the proliferation of small-scale solar PV installations, global horizontal irradiance (GHI) and power predictions are becoming critical elements in the integration of PV generation into the grid. This thesis considers short-term prediction, from minutes to hours, based on historical meteorological measurement data from weather and power monitoring stations located in the Canberra (Australia) region. The specific objective of this study is to produce accurate forecasts for (a generic) target station using a minimal amount of observations from nearby stations. Thus, although a large number of weather and power variables were collected and used for developing and testing the prediction algorithms, the ultimate aim is to rely on a few predictors, mainly meteorologically based. This will allow the identification of critical instruments which would need to be installed in order to provide satisfactory PV power predictions while limiting capital and operating costs of monitoring. Relative mean absolute error (rMAE) is used to indicate prediction performance. Three statistical methods are tested for two different seasons, winter and summer. The relative importance of predictors and stations is assessed. A conversion from GHI to global irradiance on tilted surfaces, by means of simple geometry arguments and notion of irradiance components at a nearby site, is also introduced and tested. Finally, the prediction accuracy is categorised according to different clear-sky indecs. Results show that when the clear-sky index exceeds 0.9 (near-to-cloudless conditions), the prediction performance is distinctly better than at lower clear sky indices which are under 0.9, by at least 0.05 and 0.2 in terms of rMAE in summer and winter, respectively. The second contribution of this thesis is a standalone PV-Battery hybrid system and the solar irradiance anticipation is used as simulation input to PV panels. There are two converters in the hybrid model. The unidirectional DC-DC converter, which is linked between PV panels and DC bus for power supply, works under maximum power point tracking (MPPT) mode, while the other, the bidirectional DC-DC converter located between battery banks and DC bus, operates under a model predictive control (MPC) algorithm. By charging and discharging the battery, the voltage of the DC bus can be kept in a certain range to meet the load requirement.