A photovoltaic (PV) module is a series and parallel connection of multiple PV cells; defects in any cell can cause module power to drop. Similarly, a photovoltaic system is a series and parallel connection of multiple modules, and any low-performing module in the PV system can decrease the system output power. Defects in a solar cell include, but not limited to, the presence of cracks, potential induced degradation (PID), delamination, corrosion, and solder bond degradation. State-of-the-art characterization techniques to identify the defective cells in a module and defective module in a string are i) Current-voltage (IV) curve tracing, ii) Electroluminescence (EL) imaging, and iii) Infrared (IR) imaging. Shortcomings of these techniques include i) unsafe connection and disconnection need to be made with high voltage electrical cables, and ii) labor and time intensive disconnection of the photovoltaic strings from the system.This work presents a non-contact characterization technique to address the above two shortcomings. This technique uses a non-contact electrostatic voltmeter (ESV) along with a probe sensor to measure the surface potential of individual solar cells in a commercial module and the modules in a string in both off-grid and grid-connected systems. Unlike the EL approach, the ESV setup directly measures the surface potential by sensing the electric field lines that are present on the surface of the solar cell. The off-grid testing of ESV on individual cells and multicells in crystalline silicon (c-Si) modules and on individual cells in cadmium telluride (CdTe) modules and individual modules in a CdTe string showed less than 2% difference in open circuit voltage compared to the voltmeter values. In addition, surface potential mapping of the defective cracked cells in a multicell module using ESV identified the dark, grey, and bright areas of EL images precisely at the exact locations shown by the EL characterization. The on-grid testing of ESV measured the individual module voltages at maximum power point (Vmpp) and quantitatively identified the exact PID-affected module in the entire system. In addition, the poor-performing non-PID modules of a grid-connected PV system were also identified using the ESV technique.