Simulator for Optimum Land Use in a Concentrating Photovoltaic System
Background
Concentrating photovoltaic (CPV) solar power plants using dual-axis trackers are increasing in demand. The levelized cost of energy (LCOE) is widely used to compare the cost of energy generation across technologies. In a utility-scale photovoltaic system, spacing dual-axis trackers must be balanced with total energy harvested from modules to minimize LCOE.
There is a tradeoff between capacity factor (CF) and ground coverage ratio (GCR) for lowering LCOE. While optimizing the CF, one needs to consider array density, configuration of array, self-shading loss, and direct normal irradiance (DNI), etc. However, current modeling of the system defines location specific (DNI) ineffectively, misses the electrical model for power optimization and conversion, and fails to optimize tracker array configuration.
Description
Researchers at UC Merced have developed a comprehensive simulation model for CPV arrays with dual-axis trackers. The computational time of the algorithm is independent of the scale of a CPV system, and the algorithm has been verified with various DNI methods.
A cost function is defined by using tracker spacing related parameters, capacity factor (CF) and ground coverage ratio (GCR), to minimize the LCOE by controlling the spacing in between trackers.
The novel simulation speed by only simulating some of the trackers and mapping them into a larger array. Therefore, for the optimum solution, simulation run time will be constant regardless of the expanded array of trackers.
Applications
The invention is widely applicable by the solar industry in optimizing utility-scale photovoltaic system.
Advantages
The advanced simulator enables the selection of an optimum scheme for land use in a given CPV system, including:
- optimal spacing of a tracker array for minimized LCOE
- enhanced constant computational time for any m-by-n tracker array size
Patent Status
Patent Pending
Inventor
Kim, Yong Sin Winston, Roland
