Tariff Design and Assessment Tool Workshop 3 Dec 2018, UNSW Sydney, - - PowerPoint PPT Presentation

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Tariff Design and Assessment Tool Workshop 3 Dec 2018, UNSW Sydney, - - PowerPoint PPT Presentation

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Tariff Design and Assessment Tool Workshop 3 Dec 2018, UNSW Sydney, Asia-Pacific Solar Research Conference (APSRC 2018) Welcome from the SPREE/CEEM Distributed Energy Modelling and Analysis Team Anna Bruce (a.bruce@unsw.edu.au) Jose Bilbao

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3 Dec 2018, UNSW Sydney, Asia-Pacific Solar Research Conference (APSRC 2018)

Tariff Design and Assessment Tool Workshop

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www.ceem.unsw.edu.au

facebook.com/ceem.unsw/ twitter.com/ceem_unsw linkedin.com/company/ceem.unsw/ github.com/unsw-ceem

Anna Bruce (a.bruce@unsw.edu.au) Jose Bilbao (j.bilbao@unsw.edu.au) Jessie Copper (j.copper@unsw.edu.au) Nicholas Gorman (n.Gorman@unsw.edu.au) Emi Gui (emi.gui@unsw.edu.au Navid Haghdadi n.haghdadi@unsw.edu.au Iain MacGill (i.macgill@unsw.edu.au) Luke Marshall (luke.marshall@unsw.edu.au) Rob Passey (r.passey@unsw.edu.au) Mike Roberts (m.roberts@unsw.edu.au) Alistair Sproul (a.sproul@unsw.edu.au) Naomi Stringer (n.stringer@unsw.edu.au) Sharon Young (Sharon.young@unsw.edu.au) Katelyn Purnell (k.purnell@unsw.edu.au)

Welcome from the SPREE/CEEM Distributed Energy Modelling and Analysis Team

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Electricity emissions intensity comparison

(shrink that footprint)

The challenge –

  • ur failure to serve the long-

term interests of consumers

3 Integrating demand response and energy efficiency into energy markets (ACCC, 2017) Australian residential energy prices index

(Australian Energy Statistics Update 2017)

International retail electricity price comparison

(ACCC Retail Price Competition Inquiry, 2017)

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The opportunity - a greater role for energy-users in our energy future

  • A growing appreciation of our diverse energy users and contexts
  • Citizens, consumers, customers…. now increasingly possible partners, competitors,

communities, collectives

  • Contexts – housing types, vulnerable consumers…
  • New opportunities for energy users to engage
  • PV, Storage, demand-side participation,

energy efficiency

  • Improving regulatory, market and policy efforts

to appropriately facilitate end-user engagement engage end users

  • From assumptions of rational, utility maximising

individual customers driven by prices… to a more complex appreciation of energy decision making, individual yet also collective goals and actions, and hence coordination, sharing

  • New ways to explore these challenges &
  • pportunities; learn, disseminate and broaden

the conversation

4 Integrating demand response and energy efficiency into energy markets

Australia’s residential PV penetration (Finkel Review into NEM Security, 2017)

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Open data, tools … and processes

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The Day

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Our collective task

  • Updating you on progress
  • Panel contributions from some

key stakeholders

  • Discussion
  • Your ideas, guidance, comments

and suggestions on how we can improve our analysis and tools and impact

7 UNSW CEEM / SPREE Dx Network Tariff Tool Workshop - Melbourne, December 2017

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Tariff Design and Assessment Tool: Progress and Next Steps

  • 10:15 – 11am Tool Introduction and plans for new functionality

Navid Haghdadi

  • 11:00 – 12pm Stakeholder Panel

Bob Telford, AER Craig Chambers, ARENA

Q&A and Discussion

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  • Introduction to the TDA tool
  • Aim
  • Quick tour
  • Status report
  • Development
  • Moving to Python
  • Moving to API
  • Adding new functionalities
  • Plans for improvement
  • Retail price and analysis
  • Distributed energy analysis
  • Demand response analysis
  • Feedback and Questions

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Agenda

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Tariff Design and Analysis tool

The open source TDA tool aims to assist stakeholders to investigate how different tariff structures impact on the expected bills of different types of residential consumers, while also estimating how well the tariffs align these customer bills with their impact on longer-term and wider electricity industry costs.

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Tariff Design and Assessment (TDA) tool

Where to find it?

https://github.com/UNSW-CEEM/TDA_Matlab http://ceem.unsw.edu.au/open-source-tools https://www.researchgate.net/project/Tariff-Design-and-Analysis-TDA-Tool

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Tariff Design and Assessment (TDA) tool

How to install it?

https://github.com/UNSW-CEEM/TDA_Matlab/releases

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Tariff Design and Assessment (TDA) tool

How to find more information about it?

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Tariff Design and Assessment (TDA) tool

What does the previous version do?

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Tariff Design and Assessment (TDA) tool

Select load from a range of existing load profiles, or upload your own set of loads!

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Tariff Design and Assessment (TDA) tool

Filer the load profiles by the demographic information

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Tariff Design and Assessment (TDA) tool

Get quick analysis of the set of selected loads

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Tariff Design and Assessment (TDA) tool

Add a network tariff (and some limited retail tariffs) and optionally change any parameters

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Tariff Design and Assessment (TDA) tool

Visualize the results of the analysis by a range of different graphing options

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Tariff Design and Assessment (TDA) tool

Add up to 10 analysis case and compare the results

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Tariff Design and Assessment (TDA) tool

Add tariffs, loads and projects; exports the results to excel, and change the preferences in the context menu

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Use case example: Comparison of tariffs

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Use case example: Comparison of tariffs

Excluding summer peaks

Coincident peak User’s peak

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Unitised Standard Demand Charge vs Average Demand at Time of Eight Highest network Peaks. Unitised Demand Charge (applied to customer demand at time of 12 monthly network peaks) vs Average Demand at Time of Eight Highest Network Peaks.

Passey, R., Haghdadi, N., Bruce, A., & MacGill, I. (2017). Designing more cost reflective electricity network tariffs with demand charges. Energy Policy, 109, 642-649.

Use case example: Assessing tariffs

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  • Moving to Python
  • More Analyses and Visualisation features
  • Retail Tariffs (and Categorising them)
  • Network, Wholesale, Retail Tariff Combined Analysis
  • Distributed Resources/Response:
  • PV
  • Battery
  • Appliances
  • Demand response
  • Energy Efficiency
  • Load Clustering

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New Developments

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New Development: Converting to Python

  • Even more open source!
  • Easier collaboration in non-academic environment
  • Reduced size

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  • 800
  • 600
  • 400
  • 200

200 400 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 80% 84% 89% 94% 99%

Difference in bill ($) Customers

Difference ($)

  • 40%
  • 30%
  • 20%
  • 10%

0% 10% 20% 30% 40% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 51% 56% 61% 66% 71% 76% 81% 86% 91% 96%

Difference in bill (%) Customers

Difference (%)

New Developments: Comparison of tariffs

Going from Ausgrid Flat rate tariff (2017/18) to Time of use (2017/18)

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New Developments: Distributed resources

PV and battery impact on peak and other users

Preliminary results, using SAPN network tariffs for SGSC homes, 15% of customers having PV and battery

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WS price and SGSC load profile are for 2013, but retail tariff is for 2018

New Development: Comparison of the network, wholesale and retail revenue

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WS price and SGSC load profile are for 2013, but retail tariff is for 2018

$- $20 $40 $60 $80 $100 $120 $140 $160 $- $100 $200 $300 $400 $500 $600 $700 $800 $900 Network Market Retailer 15% Retailer 20% Retailer 25%

Per MWh

Per Customer per year

Benefit ($)

New Development: How about different discount levels?

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WS price and SGSC load profile are for 2013, but retail tariff is for 2018

New Development: How about different discount levels?

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Distribution of bills Annual Bill ($) Annual Bill ($/MWh)

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0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% 6% 11% 17% 22% 28% 33% 39% 45% 50% 56% 61% 67% 72% 78% 84% 89% 95% Energy Charge % % of customers

Energy share of Bill (%)

0% 10% 20% 30% 40% 50% 60% 0% 10% 20% 30% 40% 'Real' discount Energy discount Bill discount Retailer revenue loss

New Development: Bill Discount, Energy Discount, Retailer Discount?

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30% Energy Discount means 23% Bill discount, but 45% less revenue for retailer!

8% 38% 31% 14% 9%

54% of customers have more than 30% of their bill from fixed charge

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New Development: Clustering load profiles

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Generating groups of load profile based on daily pattern More load profiles are [very] welcome!

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New Development: Financial calculation of RE

Data: 300 solar homes Ausgrid, 6 retail tariffs in NSW, PV cost retrieved from SolarChoice

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Annual saving of putting PV categorised by different size range

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New Development: Financial calculation of RE

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Data: 300 solar homes Ausgrid, 6 retail tariffs in NSW, PV cost retrieved from SolarChoice

Payback period (years) of putting PV categorised by different size range

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1 2 3 4 5 6 7 8 Net PV Net PV Scaled Net PV Net PV Scaled Net PV Net PV Scaled 2010-11 2011-12 2012-13 FR TOU

New Development: Financial calculation of RE

Data: 300 solar homes Ausgrid, 6 retail tariffs in NSW, PV cost retrieved from SolarChoice

Payback period based on different years data and for scaling PV to 4 kW for flat rate and TOU tariffs

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New Development: Financial calculation of RE

Data: 300 solar homes Ausgrid, 6 retail tariffs in NSW 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 2 4 6 8 10 12 Annaul Export (% of PV Generation) PV Capacity (kW) 2010-11 2011-12 2012-13

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Percentage of export (100% - self consumption %) for different PV and load profiles

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New Development: Online list of tariffs with continues update

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Q&A

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Join the discussion group at: https://groups.google.com/forum/#!forum/ceem-tda Take the online survey here: https://www.surveymonkey.com/r/J5HH277