P14421: Smart PV Panel Bobby Jones: Team Leader Sean Kitko Alicia Oswald Danielle Howe Chris Torbitt

AGENDA Project Overview Heat Analysis Electrical Design System Layout Test Plans BOM MSD II Schedule

Project Overview

Project Overview Advance Power Systems Jasper Ball Atlanta, GA Snow reduces power output of PV panels Develop method to prevent snow from accumulating in the first place Apply current to conductive, heating ink Keep temperature of panel surface above freezing Sense presence of snow

Heat Analysis

Heat Analysis Process 1 How much power is produced by the panel if there was no snow Uses TMY3 data which is the most average months weather in Rochester Calculates solar beam angles on panel based on time of day and day of year and angle of panel tilt Calculate how much energy panel produces from TMY3 data, solar beam angle, efficiency of panel (19%) and area of panel (0.024m)

Heat Analysis Process con’t 2 Find energy required to heat the panel in between ink traces to 5°C Length and spacing determined by cell size. Limited to where bus bars on cells were Coefficient of convection (h) ranges from 5 to 28 Modeled sections of cell using fin analysis Was able to calculate m, to get temperature at ink and qfin

Cell

Heat Analysis Process con’t 3 Calculate total energy qfin values already calculated Calculate qmelt based on an average snowfalls rate over 4 hours Uses ice properties (h=33400J/kg) Assumes density of snow=60 kg/m2 Calculated qrad Uses glass properties and surrounding temperature Total qgen is the sum of these in each section

Heat Analysis Process con’t 4 Compare different ink configurations based on qgen calculation qgen was calculated based on sections of a cell Calculations for configs based on an entire panel, not just one cell Conclusion: Configuration 2 is the more efficient in all cases

Configuration 1 16 Sections 8-0.013 Sections 8-0.052 sections

Configuration 2 8 Sections 8-0.039 Sections

Configuration 3 4 Sections 4 0.078 Sections

Configuration 4 10 Sections 4-0.031 Sections 4-0.052 Sections

Heat Analysis Process con’t 5 calculated specific convection coefficient for each hour of the day it snows Uses TMY3 data Does not take into account the direction of wind or the angle of panel Temperatures all rounded to nearest degree Conclusions: All Reynolds's numbers were <5*105 therefore all used laminar model

Heat Analysis Process con’t 6 calculated energy required for snow prevention on panel Uses h that was calculated Uses same process as qgen calculation but uses data for that specific day Snow data could not be found on hour basis, so assumed snows for four hours when most energy could be generated

Heat Analysis Process con’t 7 find how much light gets to the panel when snow is left to accumulate Uses equation found on next slide Equation used when there is snow accumulation. As time moves forward, the snow accumulates Snow is assumed to be left on panel for the rest of the day Each day it is assumed there is not snow starting on the panel

Percentage of Light vs. Snow Depth

Heat Analysis Process con’t 8 Graphically compare results Took the amount of energy required to melt snow over four hours (when there was snow) and subtracted that from how much energy the panel would produce with no snow Took the calculated amount of light that would get through the snow and graphed that

January 2

February 10

March 5

Energy Conclusion: Total energy for one year if snow is prevented: -7.5*107J (-20,823Wh) Total energy for one year if panel was left alone: about 3,300,000J (916.5Wh) Snow prevention is not the best way to get rid of snow from an energy standpoint Suggest seeing energy consumption if snow is allowed to accumulate then heated up to slide off. Only found through testing.

ANSYS – Heat Transfer

Electrical Design

Sensors

Sensors

Sensors

Sensors

Sensors

Simulations

Simulations

Simulations

Power Electronics

Power Usage Don’t want the battery to go below 40% Capacity Power Management Item Current (A) Voltage (V) Time (Hrs) Power (W) Amp Hrs Ink 10 8 4 82 40 MicroController 0.0002 3.3 24 0.00066 0.0048 Charge Controller 0.01 12 0.12 0.24 OPIC Light Sensor 0.0005 0.00165 0.012 LM35 Temp sensor 0.00005 5 0.00025 0.0012 Thermocoupler amplifier 0.001 Totals 82.12356 40.2628 Needed Battery Capacity Efficiency in Cold Choose battery 64.42048 60% 103.072768 Don’t want the battery to go below 40% Capacity Takes into account Efficiency in Cold Temperatures

Power Electronics Schem

Solid State Relay

Regulators BP5275 Series MAX1681

Battery and Controller Trojan 31-AGM Battery Getting a free AGM battery from a contact at Renewable Rochester Morningstar SS-20L 20 Amp PWM Solar Charge Controllers w/LVD ($78)

POC CONTROL SYSTEM •32K of program space Atmel's ATMega328P 8-Bit Processor in 28 pin DIP package with in system programmable flash Features: •32K of program space •23 programmable I/O lines 6 of which are channels for the 10-bit ADC. •Runs up to 20MHz with external crystal. •Package can be programmed in circuit. •1.8V to 5V operating voltage •External and Internal Interrupt Sources •Temperature Range: -40C to 85C •Power Consumption at 1MHz, 1.8V, 25C –Active Mode: 0.2mA –Power-down Mode: 0.1μA –Power-save Mode: 0.75μA (Including 32kHz RTC)

POC CONTROL SYSTEM Con’t

POC CONTROL SYSTEM Con’t

POC CONTROL SYSTEM Con’t

POC SENSOR RESEARCH

Enclosure

Enclosure and Layout

BILL OF MATERIALS

Risk Assessment and Mitigations

TEST PLAN OUTLINE Heat Transfer Test Explores how heat propagates through glass from electrified trace Apply a DC voltage to ink trace Use thermocouples to measure temperature of glass at various locations Multiple applied voltages, multiple ink trace resistances Steady state and transient

TEST PLAN OUTLINE Heat Transfer Test Diagram

TEST PLAN OUTLINE Switch Simulation Test Explores functionality of heater system with simulated sensor inputs Using switches, apply various combinations of sensor inputs Verify that microcontroller wakes up when appropriate (interrupt test) With simulated inputs, verify that microcontroller can make decisions to melt.

TEST PLAN OUTLINE Integrated System Test Explores full functionality of system in expected environment Install system in a realistic environment Verify sensor functionality Verify microcontroller interrupts when appropriate Verify microcontroller accurately reads values Verify heater functionality Either with simulated or actual sensor inputs, verify that the system can melt snow efficiently.

MSD II SCHEDULE P14421 MSD II – Tentative Schedule Weeks 1-3:   Weeks 1-3: MSD I issues summarized. Mitigation strategies implemented (Jan 28th) Comprehensive and detailed Test Plan completed (Jan 28th) Test and Prototype components and systems Create preliminary C-Code for systems controller Begin construction and customization of enclosure Weeks 4 and on: Detailed/Finalized Testing Iterative testing and refinement of system and subsystems Technical paper and poster Confirm deliverables have been met