IEEE Global IoT Summit 17

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1 design and implementation of an energy-neutral solar energy system for wireless sensor-actuator nodes IEEE Global IoT Summit 17 Jonathan Knapp and Paul G. Flikkema June 2017

2 Outline Introduction Hardware Design and Development Solar Energy Model Software and Firmware Design Results 1

3 introduction

4 Introduction Introduction Wireless sensor/actuator nodes/networks Energy-neutral operation Energy harvesting, forecasting, and energy-aware design Problem Statement Design and implementation of an energy-neutral solar energy system (SES) for wireless sensor/actuator nodes Objectives Extend deployment lifespan Reduce labor and maintenance Allow for more power-intensive operation 3

5 Introduction: Motivation - SEGA Southwest Experimental Garden Array (SEGA) Explore and quantify ecological/evolutionary responses to climate change Geographically-distributed array of highly-instrumented gardens Elevation gradient Each garden: networks of WiSARD wireless sensor/actuator nodes Real-Time Data Center (RTDC) Garden Sites Colo r a do River 4

6 Introduction - Power Management Energy Neutral Operation (ENO) Energy harvested by the energy source η T 0 [P s(t) P c (t)] + dt η - Scaling factor for harvester efficiency Energy consumed by the load T 0 [P c(t) P s (t)] + dt Energy lost due to leakage T 0 P leak(t)dt B min B 0 + η T [Ps(t) 0 Pc(t)]+ dt T [Pc(t) 0 Ps(t)]+ dt T 0 Pleak(t)dt Bmax 5

7 hardware design and development

8 Hardware Design and Development - Introduction Solar Charge Controller Energy Source Microcontroller Energy Harvester/ Charge Controller Storage Element Load (Wireless Sensor Node) Power ADC Communication Figure: Block diagram of the SES. Not shown are power management integrated circuits for the microcontroller and the load. 7

9 WiSARDNet (Wireless Sensor/Actuator Relay Device Network) Modular architecture and hardware implementation Self-organizing, self-healing, wireless network Design Requirements 5 V supply Source current transients up to 300 ma Minimum of three days operation with no energy generation Real-time, floating-point analytics Voltage and current measurements UART Communication 8

10 Load Energy Consumption Expected Load Energy Consumption WiSARD in typical configuration (2 soil moisture and 3 temperature sensors at 5 minute sampling) J hour hour day = 0.22 kj day Worst-case scenario (doubling of transducers, sampling rate, radio communication, losses) 0.22 kj kj = 3.52 day day 9

11 Solar Energy Generation Expected solar energy budget E harvested = I avg A panel C panel C harvester C system A panel = m 2, C panel = 0.176, C harvester = 0.8, C system = 0.95 Average daily solar insolation by month for Flagstaff, AZ kj day Jan Feb March April May June July Aug Sept Oct Nov Dec Avg Daily Insolation (kwh/m 2 day) Expected energy balance for Flagstaff, AZ using daily solar insolation averages by month Jan Feb March April May June July Aug Sept Oct Nov Dec Expected Harvested Energy (kj/day) Energy Surplus(+)/Deficit(-) (kj/day)

12 Battery Capacity Planning Battery Capacity Planning Joules to amp-hours (typical configuration) Total Daily Ah (Ah/day) = Joules to amp-hours (worst-case configuration) Total Daily Ah (Ah/day) = Minimum amp-hours 0.22 kj day day Ah = = V 3600 seconds day 3.52 day kj day Ah = V 3600 seconds day Total Daily Ah (Ah/day) Days of autonomy Temperature Multiplier Depth of Discharge Minimum amp-hours (typical configuration) = Ah = 97.1mAh 0.8 Minimum amp-hours (worst-case configuration) = 1.03Ah = 1030mAh 0.8 Comparable price for 2200 mah lithium-ion 11

13 Energy Budget Battery capacity to Joules B full = 3.7 V 2.2 Ah = 17.6 kj Lithium-ion nominal voltage = 3.7 V Depth of discharge = 0.8 Temperature effect scaling factor = 0.75 Case 1 Time to reach operational mode with a depleted battery B partial = V Ah B discharged = 3.0 V 400 mah = 4.32 kj B operational = 3.2 V 500 mah = 5.76 kj B operational = B discharged + T 0 P produced(t) dt 0 T 0 P consumed(t) dt kj 4.32 kj 5.02 kj = 0.29 days 12

14 Energy Budget Case 2 Time to fully discharge the storage element B 0 = B charged = 17.6 kj 0 = B charged + 0 T 0 P produced(t) dt T 0 P consumed(t) dt 17.6 kj = 53.3 days 0.33 kj/day Case 3 Time to fully discharge the storage element (worst-case configuration) 17.6 kj 3.52 kj/day = 5 days 13

15 Hardware Design and Development - Component Selection Block Diagram Solar Charge Controller Component Selection Microcontroller Energy Source Storage Element Load (Wireless Sensor Node) Energy Harvester/ Charge Controller Power ADC Communication Energy Harvester/Charge Controller - TI BQ25504 Energy Source - SolarMade 1.5 V 150 ma solar panel Microcontroller - TI MSP432 Storage Element - PKCell ICR mah lithium-ion Load - WiSARD 14

16 Hardware Design and Development- PCB Design PCB Layout Sections Energy harvester External IO Power conversion On-board intelligence Packaging 15

17 solar energy model

18 Solar Energy Model- Introduction Objective Predict GHI Convert to energy Estimate battery voltage Models Bird PVLIB North-American Mesoscale (NAM) National Digital Forecast Database (NDFD) 17

19 Solar Energy Model - PCB Design PVLIB vs. Bird January 7-9, GHI (W/m^2) Observed GHI Bird Model NDFD Forecast NAM Forecast /07 00:00 01/08 00:00 01/09 00:00 01/10 00:00 Timestamp (Arizona) 18

20 software and firmware design

21 Software and Firmware Design- Software Implementation SES Model Fetch battery voltages from each node and site-specific GHI for previous 3 days from SEGA data center Use GHI to identify nightfall and sunrise to estimate the load energy consumption Use PVLIB to predict GHI and convert to expected harvestable energy over the next 3 days Use battery voltage at the time of the prediction for B 0 Use estimated daily energy consumption and anticipated harvestable energy to predict battery voltage at 24,48, and 72 hour intervals from the time of the prediction RTDC Software Chain Top-level bash script runs as scheduled task Fetch observed GHI and battery voltages for each SES Run PVLIB to predict GHI over 72 hour interval Process observations and predictions, estimate battery voltage at 24, 48, and 72 hours Distribute energy estimates to each SES through the SEGA CI 20

22 results

23 Results - Energy-Neutral Operation WiSARD configurations WiSARDNet ID Garden Site Sampling Interval Configuration Description 6 Flagstaff Arboretum 5 min. Lizard Model 16 temperature sensors 3 Black Point 5 min. Soil Moisture 8 soil moisture sensors 10 Bradshaw Ranch 5 min. MicroMet 3 temperature, 2 soil moisture sensors ENO achieved if battery maintains state of charge (above 4.0 V) 22

24 Results- Energy-Neutral Operation Lizard WiSARD (16 temperature sensors) Arboretum GHI (W/m^2) Arboretum WiS 6 (V) 03/31 00:00 04/01 00:00 04/02 00:00 04/03 00:00 04/04 00:00 04/05 00:00 04/06 00:00 04/07 00:00 04/08 00:00 23

25 Results- Energy-Neutral Operation Soil Moisture WiSARD (8 soil moisture sensors) Black Point GHI (W/m^2) Black Point WiS 3 (V) 03/31 00:00 04/01 00:00 04/02 00:00 04/03 00:00 04/04 00:00 04/05 00:00 04/06 00:00 04/07 00:00 04/08 00:00 24

26 Results- Energy-Neutral Operation µmet (3 temperature, 2 soil moisture sensors) Bradshaw GHI (W/m^2) Bradshaw 10 (V) /31 00:00 04/01 00:00 04/02 00:00 04/03 00:00 04/04 00:00 04/05 00:00 04/06 00:00 04/07 00:00 04/08 00:00 25

27 Future Work Optimize SES firmware Communication protocols (RS-232, I 2 C, SPI) Use communication pin as interrupt, enter deeper sleep More robust global variable handling Enable smart task scheduling SES model software chain optimization Single language SES model implementation Discharge model using different discharge rates and temperatures Machine learning SES hardware modification Pin selectable configurations for communication and load output voltage Reduce ground plane noise Thank you! 26

28 Results- Commercial Options Off-the-shelf Solutions Seeed Studio/XBee Carrier Adafruit charge controller PCB SparkFun s Sunny Buddy PCB Issues Field-ready Communication interfaces Not low-power 27

29 Results - Model Performance Bird Model GHI (W/m 2 ) 200 Observed Bird Model 0 01/04 00:00 01/03 00:00 01/02 00:00 01/01 00:00 01/05 00:00 01/10 00:00 01/09 00:00 01/08 00:00 01/07 00:00 01/06 00:00 01/11 00:00 Timestamp (Arizona) The Bird model GHI prediction compared with observed GHI at The Arboretum at Flagstaff over a 10-day period in January, 2016 Period RMSE ( ) W m 2 MAE ( ) W m 2 MBE ( ) W m 2 Bird (Jan 1-3) Bird (Jan 4-6) Bird (Jan 7-9) Bird (Jan 1-10)

30 Results - Model Performance PVLIB vs. Bird January 1-3, GHI (W/m^w) 200 Observed GHI Bird Model NDFD Forecast NAM Forecast 0 01/01 00:00 01/02 00:00 01/03 00:00 01/04 00:00 Timestamp (Arizona) Model RMSE ( ) W m 2 MAE ( ) W m 2 MBE ( ) W m 2 Bird NDFD NAM

31 Results - Model Performance PVLIB vs. Bird January 4-6, GHI (W/m^2) 200 Observed GHI Bird Model NDFD Forecast NAM Forecast 0 01/04 00:00 01/05 00:00 01/06 00:00 01/07 00:00 Timestamp (Arizona) Model RMSE ( ) W m 2 MAE ( ) W m 2 MBE ( ) W m 2 Bird NDFD NAM

32 Results - Model Performance PVLIB vs. Bird January 7-9, GHI (W/m^2) Observed GHI Bird Model NDFD Forecast NAM Forecast /07 00:00 01/08 00:00 01/09 00:00 01/10 00:00 Timestamp (Arizona) Model RMSE ( ) W m 2 MAE ( ) W m 2 MBE ( ) W m 2 Bird NDFD NAM

33 Results- Model Performance WiSARD-SES Communication Protocol WiSARD UART Communication SES Sends command packet instructing SES to execute the ADC task Sends command packet requesting the results of the ADC task Dispatches ADC task, stores results, generates report Returns the generated report containing the results of the ADC task to the WiSARD 32

34 Results- Model Performance Quantifying model performance Typical operating range: V (750 mv) Acceptable error: ±37.5 mv Date Predicted Voltage (V) Observed Voltage (V) Error (mv) 02/17/ /18/ /19/ /20/ /21/ /22/ /23/ /24/

35 Results Open Air SCC Enclosure 20 WiSARD Enclosure Temperature (C) 10 WiSARD Enclosure SCC Enclosure Open Air /20 00:00 10/19 21:00 10/19 18:00 10/19 15:00 10/19 12:00 10/19 09:00 10/19 06:00 10/19 03:00 10/19 00:00 10/18 21:00 10/18 18:00 10/18 15:00 10/18 12:00 10/18 09:00 10/18 06:00 10/18 03:00 10/18 00:00 Sample Timestamp (Arizona) 34

36 Results - Introduction Real-Time Data Center (RTDC) Collects observed GHI and battery voltage for each SES Runs GHI prediction model Distributes battery voltage predictions to each SES SES Firmware MSP432 Task execution UART communication with WiSARD 35

37 Results- Model Performance SES Firmware Written with Code Composer Studio (TI) in embedded C UART communication Command, data request, interrogate, HID ADC readings for battery voltage and solar panel voltage, current Error reporting Parsing model results (unimplemented) 36

Good Vibrations for Energy Harvesting

Good Vibrations for Energy Harvesting By Tony Armstrong Director of Product Marketing Power Products Linear Technology Corporation tarmstrong@linear.com Background A wide range of low-power industrial