Abstract
The power generation potential of a solar photovoltaic (PV) power generation system is closely related to the on-site solar radiation, and sunshine conditions are an important reference index for evaluating the installation of a solar PV system. Meanwhile, the long-term operation and maintenance of a PV system needs solar radiation information as a reference for system performance evaluation. Obtaining solar radiation information through the installation of irradiation monitoring stations is often very costly, and the cost of sustaining the reliability of the monitoring system, Internet stability and subsequent operation and maintenance can often be alarming. Therefore, the establishment of a solar radiation estimation model can reduce the installation of monitoring stations and decrease the cost of obtaining solar radiation information. In this study, we use an inverse distance weighting algorithm to establish the solar radiation estimation model. The model was built by obtaining information from 20 solar radiation monitoring stations in central and southern Taiwan, and field verification was implemented at Yuan Chang Township town hall and the Tainan Liujia campus. Furthermore, a full comparison between Inverse Distance Weighting (IDW) and the Kriging method is also given in this paper. The estimation results demonstrate the performance of the IDW method. In the experiment, the performance of the IDW method is better than the Ordinary Kriging (OK) method. The Mean Absolute Percentage Error (MAPE) values of the solar radiation estimation model by IDW at the two field verifications were 4.30% and 3.71%, respectively.
Highlights
As global warming is worsening and human dependence on energy is on the rise, global growth in solar PV system development is accelerating
This paper presents a simple method for establishing a solar radiation estimation model by setting up 22 horizontal solar radiation computer monitoring systems to collect solar radiation data, and applying inverse distance weighting algorithm to 20 locations to establish the estimation model
The experiments compare the estimation results done by the Inverse Distance Weighting (IDW) and Ordinary Kriging methods
Summary
As global warming is worsening and human dependence on energy is on the rise, global growth in solar PV system development is accelerating. 2015; the annual growth rate is 43%, exceeding 30% annual growth for the second consecutive year. This figure is much higher than the original forecast, with the main difference coming from China’s installation volume of 34 GW, which is significantly higher than expected [1,2]. Jurasz and Ciapała proposed a new method of smoothing the energy exchange with the grid based on fixed volumes of energy [3]. Such a method can be applied to deal with the problem of larger-scale hydropower plants.
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