Abstract
Recent development and cost down of PV(Photovoltaic) technology drive change of power system structure. The participation of PV generation is increasing, and the size of each PV farm is getting larger. In order to integrate large PV farms into the main grid, substation for interconnection needs to be sized properly. Unlike substations for load and conventional generators, PV farm substation has an uneven utilization ratio due to characteristics of solar radiation. With proper sizing method for the capacity of the substation can reduce the building cost of facilities. A combination of an energy storage system can further reduce the capacity of the substation. Battery energy storage system (BESS) can shift the peak production of PV during the daytime to midnight. According to market circumstances, BESS can reduce further construction costs by producing profit based on time difference of electric cost. For proper sizing of substation capacity, several factors must be considered including environmental factors, market structure and BESS in the system. In this article, a series of assessment methodology is introduced to calculate the optimized capacity of substation and BESS for PV farm interconnection. The long-term solar radiation data is analyzed for a given site of the PV farm. Based on market structure, the operation of BESS is optimized to make maximum profit during operation. The iterative calculation of each step results in the calculation of the optimized capacity of BESS and substation for given PV farm size.
Original language | English |
---|---|
Article number | 9272275 |
Pages (from-to) | 214577-214585 |
Number of pages | 9 |
Journal | IEEE Access |
Volume | 8 |
DOIs | |
State | Published - 2020 |
Keywords
- BESS
- BESS sizing
- hosting capacity
- machine learning classifier
- neural network fitting
- PV
- REC
- SMP
- solar pattern
- substation