Design modeling and capacity planning for micro solar power sensor networks
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Design, Modeling, and Capacity Planning for Micro-Solar Power Sensor Networks. Jay Taneja , JaeinJeong , and David Culler Computer Science Division, UC Berkeley IPSN/SPOTS 2008 Presenter: SY. Outline. Introduction Micro-Solar Planning Model And System Design Node And Network Design

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Design, Modeling, and Capacity Planning for Micro-Solar Power Sensor Networks

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Design, Modeling, and Capacity Planning for Micro-Solar Power Sensor Networks

Jay Taneja, JaeinJeong, and David Culler

Computer Science Division, UC Berkeley

IPSN/SPOTS 2008

Presenter: SY


Outline

  • Introduction

  • Micro-Solar Planning Model And System Design

  • Node And Network Design

  • Evaluation

  • Conclusion


Motivation

  • They have a project – HydroWatch

    • Study hydrological cycles in forest watersheds

    • Sense temperature, humidity, and light

    • Forest environment

  • Want to design a device

    • Sense and transfer data

    • Solar powered

      • Infinite power lifetime


About This Paper

  • Show how they develop the micro-solar power subsystem -- systematically

    • Modeling

    • Design

    • Evaluation

  • System design experience sharing

  • Real deployment evaluation


The Challenges

  • Capacity Planning

    • Infinite power lifetime

  • Mechanical Design

    • Weatherproof with Correctly Exposed Sensors

  • Incorporating off-the-shelf and custom-built pieces


Outline

  • Introduction

  • Micro-Solar Planning Model And System Design

  • Node And Network Design

  • Evaluation

  • Conclusion


72:1

Micro-Solar Planning Model

Storage Charge-Discharge

1:1

E in : E out

All Ideal Components

48:1

240:1

120:1

Regulator Efficiencies

Half Hour of Exposure Per Day

60%

50%

2%

66%


Application Load

  • Starting point for capacity planning

  • Most time is spent sleeping (~20 uA) with short active periods (~20 mA)


Energy Storage

Straightforward charging logic


Solar Panel

  • Solar cells composition

    • In serial and parallel

  • The panel characterized by its IV curve

    • Open-circuit voltage, short-circuit current, and maximum power point


Solar Panel

  • Important parameters

    • IV and PV Curves

    • Physical Dimensions

MPP: 3.11 Volts

They choose – Silicon Solar #16530(4V-100mA)


Regulators

  • Regulators are “glue” matching primary components

  • 50-70% efficiency for typical sensornet load range

  • Input regulator

    • Regulates voltage from solar panel to battery

    • Can be obviated by matching panel directly to storage

  • Output Regulator

    • Regulates mote voltage

    • Provides stability for sensor readings

Model estimates that load requires 28 minutes of sunlight


Outline

  • Introduction

  • Micro-Solar Planning Model And System Design

  • Node And Network Design

  • Evaluation

  • Conclusion


HydroWatch Weather Node


Mechanical Considerations

  • Enclosure design is often application-driven

    • Sensor exposure

    • Waterproofing

    • Ease-of-Deployment

    • RF in forest

    • Internal mechanicals

Temp / RH Sensor

TSR, PAR Sensors


Network Architecture

Used Arch Rock Primer Pack for multi-hop network stack, database for stored readings, and web-based network health diagnosis


Forest Deployment


Outline

  • Introduction

  • Micro-Solar Planning Model And System Design

  • Node And Network Design

  • Evaluation

  • Conclusion


The Urban Neighborhood

  • 20 Nodes for 5 Days

  • Mounted on house, around trees, and on roof

  • Meant to emulate forest floor conditions

  • Important for systematic approach -- provided validation of model


Urban Neighborhood Energy Harvested

Every node received enough sunlight


Three Nodes, Three Solar Inputs


The Forest Watershed

  • 19 Nodes for over a Month

  • Mounted on 4-ft stakes throughout the area


Forest Watershed Site


Forest Watershed Energy Harvested

Watershed

Most nodes struggle to harvest sunlight


Three Nodes at the Watershed


Reflected Light

Sunny

Overcast

Overcast

Sunny

Though only minimally, a cloudy day helps a sun-starved node harvest solar energy.


Conclusion

  • Always surprises in real environment

  • Reliability is important real application

    • But difficult to achieve

  • In their work

    • Systematic approach resulted in 97% collection of an unprecedented spatiotemporal data set

    • System design experience sharing


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