2026-09-19T22:28:10Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/106184 2023-07-11 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

Bose, Subhonmesh Miljkovic, Nenad Sauer, Peter Galtieri, Jason A. Krein, Philip T. Krein, Philip T. Banerjee, Arijit 2020-03-02T21:58:10Z 2020-03-02T21:58:10Z 2019-11-12 2019-12 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. Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2020-02-28 without embargo terms The student, Jason Galtieri, accepted the attached license on 2019-11-11 at 17:38. The student, Jason Galtieri, submitted this Dissertation for approval on 2019-11-11 at 17:48. This Dissertation was approved for publication on 2019-11-12 at 09:57. DSpace SAF Submission Ingestion Package generated from Vireo submission #14542 on 2020-02-28 at 17:13:28 Made available in DSpace on 2020-03-02T21:58:10Z (GMT). No. of bitstreams: 2 GALTIERI-DISSERTATION-2019.pdf: 35492971 bytes, checksum: 20e538cbf63b752efb4ed3692953cb36 (MD5) LICENSE.txt: 4211 bytes, checksum: 1030e42b567a4b5ba408293b824c735c (MD5) Previous issue date: 2019-11-12 application/pdf http://hdl.handle.net/2142/106184 en 2019 Jason A. Galtieri Solar Energy Maximum Power Point Tracking Solar Intermittency Energy Storage Systems A reliable photovoltaic setpoint tracking algorithm to extend the utility of solar arrays text text Electrical & Computer Eng Electrical & Computer Engr University of Illinois at Urbana-Champaign Dissertation Ph.D.