Document Name Solar Analytics - Rooftop PV energy analytics - PowerPoint PPT Presentation

Document Name Solar Analytics - Rooftop PV energy analytics PREPARED BY: Your Name, Your Title and fault diagnosis DATE: 6 TH MARCH 2015 Jonathon Dore Head of Data Analytics Solar Analytics 1

Outline • About Solar Analytics • Faults and case studies • Research projects 2

Outline • About Solar Analytics • Faults and case studies • Research projects 3

Our Purpose Our Purpose To maximise the To maximise the value customers value customers receive from their receive from their solar energy system solar energy system 4

Coal is not good for humanity Coal is not good for humanity … … Pollutes atmosphere Degrades land Expensive Doctors report that “coal is a health hazard from start to finish” 5

6 … solar energy is the saviour … … solar energy is the saviour …

... distributed solar is already ... distributed solar is already colonising our homes … colonising our homes … Cleaner Simpler Cheaper 7

8 …but there’s a problem …but there’s a problem

19% CAGR but industry has focussed on large 19% CAGR but industry has focussed on large scale monitoring scale monitoring Leading monitoring providers by revenue Global monitoring penetration % of sites 100 Company Focus Monitored Skytron Energy Utility 80 InAccess Utility 60 MeteoControl Utility/Commercial Not FirstSolar Utility 40 monitored GreenPower Utility 20 SolarLog Utility/Commercial 0 Source: GTM research, 2013 Utility Commercial Residential 9

Current residential monitoring products Current residential monitoring products are inadequate are inadequate Features Residential Commercial Utility Production Data Performance Analysis Fault Diagnosis Readily available Available with Solar Analytics Not available 10

Solar Analytics is already providing Solar Analytics is already providing the solution the solution Works with any hardware …. or even none 11

Providing useful information Providing useful information How to fix your system When to install batteries How to save energy 12

13 Providing detailed information Providing detailed information

14 Distributed via solar retailers Distributed via solar retailers

15 Current Status: 506 Monitored Sites

People People • Stefan Jarnason , Co-founder and Managing Director • Valantis Vais , Co-founder and Board Member • Dr Renate Egan , Co-founder and Commercial Director • Dr John Laird , Co-founder and Software Development Manager • Dr Jonathon Dore , Head of Data Strategy & Analytics + 10 (software dev, design, sales, service, ops & analysis) + Co-op 16

17 Envais Solar (Valantis) History History

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Outline • About Solar Analytics • Faults and case studies • Research projects 19

Breakdown of PV system failure Solar Analytics Data • 26% systems underperforming • 12.1% annual fault rate 20

Breakdown of PV system underperformance • Earth leakage • Soiling • DC or AC Isolator • Wiring or connectors • Intermittent inverter issue • Microcracks • Hot spot • Potential Induced Degradation Performance lessons from the real world, SunWiz 2012 21

Case Study 1 • 10kW system in Tasmania • 7.5kW @ 32° NW and 2.5 kW @ 122 ° SW Intermittent string loss 22

Case Study 2 Daily Energy 40 35 30 Energy (kWh) 25 20 15 10 5 0 Inverter 1 Inverter 2 Measured Production 23

Case Study 2 Daily Energy 40 35 30 Energy (kWh) 25 20 15 10 5 0 Inverter 1 Inverter 2 Expected Producction Measured Production 24

Case Study 2 Power (kW) 0 1 2 3 4 5 6 5:00 AM 6:00 AM 7:00 AM Inverter 2 Inverter 1 Average Power (1 hour resolution) 8:00 AM 9:00 AM 10:00 AM 11:00 AM 12:00 PM 1:00 PM 2:00 PM 3:00 PM 4:00 PM 5:00 PM 6:00 PM 7:00 PM 25

Case Study 2 Power (kW) 0 1 2 3 4 5 6 5:00 AM 6:00 AM 7:00 AM Inverter 2 Inverter 1 Average Power (5 min resolution) 8:00 AM 9:00 AM 10:00 AM 11:00 AM 12:00 PM 1:00 PM 2:00 PM 3:00 PM 4:00 PM 5:00 PM 6:00 PM 7:00 PM 26

Case Study 2 Power and Voltage (5 sec ressolution) 6 270 Power (kW) Voltage (V) 5 266 4 262 Power (kW) Voltage (V) 3 258 2 254 1 250 0 246 10:00:00 AM 10:10:00 AM 10:20:00 AM 10:30:00 AM 10:40:00 AM 10:50:00 AM 11:00:00 AM 27

Case Study 3 10000 9000 8000 7000 6000 Power (W) 5000 Sum of Measured 4000 Sum of Expected 3000 Sum of Shaded 2000 1000 0 0 4 8 12 16 20 0 4 8 12 16 20 0 4 8 12 16 20 0 4 8 12 16 20 29 29 29 29 9 10 11 12 2014 28

Case Study 3 10000 9000 8000 7000 Energy (Wh) 6000 5000 Shaded 4000 Hourly Measured 3000 2000 1000 0 6 7 8 9 10 11 12 13 14 15 16 17 18 Hour 29

Case Study 3 10000 9000 8000 7000 6000 Power (W) 5000 Sum of Measured 4000 Sum of Expected 3000 Sum of Shaded 2000 1000 0 0 4 8 12 16 20 0 4 8 12 16 20 0 4 8 12 16 20 0 4 8 12 16 20 29 29 29 29 9 10 11 12 2014 30

31 Case Study 3

Outline • About Solar Analytics • Faults and case studies • Research projects 33

Research Projects • Load disaggregation (Lachlan McDermid, UNSW) 34

Research Projects • PV generation forecasting (Johnathan Lee & Rachel Oh, UNSW) 35

Research Projects • PV generation forecasting (Bibek Joshi, UNSW) • Household consumption forecasting (Baran Yildiz, UNSW) 36

Proposed Project • Hardware development • Home energy management • Battery monitoring and optimisation 37

Future Projects • ARC Linkage? • Solar Hot Water? • Machine Learning? • Grid Management? 38

Our Purpose Our Purpose To maximise the To maximise the value customers value customers receive from their receive from their solar energy system solar energy system 39