Differential power processing for increased solar array energy harvest

The integration of power electronics in series-connected photovoltaics (PV) has provided a new approach to handling the well-known current mismatch problem. One such technique, known as differential power processing (DPP), has demonstrated high efficiency mismatch handling, as well as scalability, in PV applications. This thesis investigates the potential benefits of DPP in large-scale solar arrays. Mitigating mismatch is an important design parameter in the layout and orientation of solar arrays. To compare different designs, a solar simulator is developed which models annual energy production for arrays with and without DPP. Models for expected sources of loss are implemented to determine any improvement DPP offers over conventional methods. Two common and predictable sources of mismatch are self-shading and diffuse masking. Both these shading effects are influential in designing arrays. The simulation model is used to compare the impact of these two effects. Annual solar data, given in hourly measurements, is used to simulate the arrays. A test site is chosen to provide an in-depth analysis of DPP improvements. Results are then extended to sites across the United States to show the broader benefits of DPP. Analysis shows DPP improves the energy output per unit area of arrays, compared to conventional arrays. This is accomplished in two ways: array size can be reduced without sacrificing energy production, or energy production for identically sized arrays is increased. In addition to self-shading and diffuse masking, an analysis is performed on the effects of factory binning. Factory binning is assumed to be a static source of mismatch which will persist and worsen over the life of the array. Variations in panels are modeled using a bi-variate Gaussian distribution. A Monte Carlo simulation is used to quantify the impact of factory binning on an array's power output. With DPP, energy reduction due to factory binning is significantly decreased. Results indicate that arrays with DPP can handle wider ranges of binning mismatch than conventional arrays. This could ultimately decrease the installed price of installations, as both manufacturers and installers do not need to follow such stringent binning techniques

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

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