Optimal PV system capacity ratio and power limit value selection based on a novel fast calculation method of IGBT junction temperature and IGBT annual damage analysis
Abstrak
In order to solve the problem of long calculation time of insulated gate bipolar transistor (IGBT) junction temperature, the XGBoost machine learning algorithm is used to calculate IGBT junction temperature in the annual damage assessment process. The XGBoost machine learning algorithm can greatly reduce the calculation time of IGBT junction temperature while ensuring the accuracy, which provides conditions for finding the optimal PV system capacity ratio and power limit value by heuristic algorithm such as differential evolution algorithm later. For PV system capacity ratio and power limit, it is necessary to consider the annual damage of the PV inverter, the increase of power generation due to capacity ratio and the power generation loss due to power limit. This paper proposes an optimization goal that considers the above factors, and uses the differential evolution algorithm to obtain the optimal PV system capacity ratio and power limit value.
Topik & Kata Kunci
Penulis (5)
Bo Zhang
Yuan Gao
Tiecheng Li
Xuekai Hu
Enze Yang
Akses Cepat
- Tahun Terbit
- 2022
- Sumber Database
- DOAJ
- DOI
- 10.1016/j.egyr.2022.08.141
- Akses
- Open Access ✓