| Title |
Estimation of PV Capacity and Generation Through Weather-Based Demand Reconstruction Analysis |
| Authors |
노재구(Jae-Koo Noh) ; 김영일(Young-Il Kim) ; 신진호(Jin-Ho Shin) ; 이효철(Hyo-Chul Lee) ; 이종욱(Jong-Uk Lee) |
| DOI |
https://doi.org/10.5370/KIEE.2025.74.11.1944 |
| Keywords |
PV Capacity; PV Generation; Demand Reconstruction Analysis; Temperature sensitivity |
| Abstract |
As the share of solar photovoltaic (PV) generation increases within the power system, visibility of the grid has declined, leading to distortions in actual electricity demand. This paper proposes a method for estimating solar PV capacity by reconstructing total electricity demand based on its temperature sensitivity. By incrementally adding estimated solar generation to the market load, the method reconstructing gross electricity demand, and identifies the point at which temperature sensitivity is maximized as the basis for estimating total installed PV capacity. The proposed approach was applied to 2021 data to estimate solar PV capacity by transaction type, providing a quantitative basis for assessing the scale of unmetered behind-the-meter (BTM) resources. Additionally, Comparative analysis shows that including more comprehensive PV data significantly improves demand-reconstruction accuracy. This method offers a practical solution for improving the visibility of solar resources in the power grid and enhancing the accuracy of demand forecasting. |