A reliable photovoltaic setpoint tracking algorithm to extend the utility of solar arrays

Intermittency from renewable generation, such as wind and solar, proposes new challenges to grid operation. Solar arrays, in particular, impose large power ramps onto the grid, as arrays become shaded and unshaded. The frequency and duration of these transients stress conventional grid operations. Maximum point power tracking (MPPT) exacerbates variability by directly following the sun output. As such, large and expensive energy storage systems are typically proposed to offset the power transients expected in MPPT arrays. In this thesis, a control strategy is proposed to mitigate variability in solar arrays. We show that arrays which can reliably operate at setpoints away from their maximum power point (MPP) will reduce the need for large and expensive storage components. However, moving off MPPT introduces several challenges into the setpoint tracker. The converter must approximately know where the MPP is, in order to operate reliably with a controllable headroom. Additionally, the MPP checking process cannot impose its own power transient onto the grid. A fast limited power point tracking (LPPT) algorithm is proposed which builds on existing ripple correlation control (RCC) algorithms. The LPPT shows 1-5 ms response to irradiance transients and setpoint updates. Yearlong hybrid PV-ESS simulations demonstrate the added utility of LPPT over MPPT arrays in mitigating transients in arrays. The LPPT RCC algorithm is implemented in a boost converter and tested with a 185 W commercial panel. Tests are performed indoors with a PV emulator, as well as outdoors under real world conditions. In both scenarios the converter can track a desired setpoint throughout sunlight hours. A total of 128 hours of indoors tests were performed and subjected the converter to a wide range of irradiance profiles. Additionally, around 60 hours of outdoor data were collected in order to verify the PV emulator and simulation results.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2020

Author dc:creator

• Galtieri, Jason A.

Contributors dc:contributor

• Bose, Subhonmesh
• Miljkovic, Nenad
• Sauer, Peter
• Krein, Philip T.
• Banerjee, Arijit

• Solar Energy
• Maximum Power Point Tracking
• Solar Intermittency
• Energy Storage Systems

Statement dc:rights

• 2019 Jason A. Galtieri

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/106184

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/106184