| Title |
A Study on PV Installation Forecasting Model for Strategic Distribution Planning |
| Authors |
조진태(Jintae Cho) ; 김홍주(Hongjoo Kim) ; 유호성(Hosung Ryu) ; 박래진(Rae-Jin Park) ; 손용주(Yongju Son) ; 김동섭(Dongsub Kim) |
| DOI |
https://doi.org/10.5370/KIEE.2023.72.12.1613 |
| Keywords |
Distribution planning; PV installation forecasting model; Machine learning; Land characteristic |
| Abstract |
The complexity and uncertainty of the distribution system are increasing due to the growth of distributed power generations. Despite the decrease in the load growth rate, the investment cost of distribution lines is expected to continue to increase due to the expansion of the supply of renewable energies. Therefore, a mid- to long-term strategic distribution planning that considers loads and distributed power generations prospects is needed. For this, it is necessary to forecast the location of the predicted distributed power generation capacity. This is because an efficient and economical distribution planning for the expansion of distribution lines is established in consideration of the predicted location. In this paper, the model for forecasting the installation location of PV(Photovoltatic power generation), which is the majority of the distributed power generations connected to the distribution system, was proposed. At the same time, in this paper, the annual PV installation forecasting of the target area was performed through the proposed model, and the results were analyzed to examine its effectiveness. |