long term challenges in reflecting network costs of... · 2015-12-14  · long term challenges in...

Long term challenges in reflecting network costs: Pricing and other solutions to manage network challenges.(feat. Network Opportunity Maps)

Chris Dunstan (Research Director, ISF)

AER Tariff Structure Statement Forum

14 December, 2015

1. Challenges

2. Network Opportunity Maps

� Information for the decentralised energy era

3. Conclusions

OVERVIEW

CHALLENGES

isf.uts.edu.au

CHALLENGES FOR COST REFLECTIVE NETWORK PRICING

• Locational specificity

• Time responsiveness: by hour, day, month, year

• It’s not just about peak demand

� Low voltage network; voltage management; power factor;

ramp rates; fault current, reliability, asset replacement,

reliability and forecast unserved energy (USE)

• New technology: Solar PV, Electric Vehicles, Batteries, energy

management, hydrogen & fuel cells

CENTRALISED ELECTRICITY SUPPLY:Have we already peaked?

isf.uts.edu.au

Rooftop solar PVEnergy efficiency

Annual Energy Forecast for the NEM (NEFR, June 2014)

PEAK DEMAND – Still rising?

Source: 2015 AEMO National Electricity Forecasting Report

(NEFR) (June 2014)

Low load factor = higher prices

isf.uts.edu.au

ELECTRICITY NETWORKS: LOCATION, LOCATION, TIME

Networks comprise >50% power bills (nationally)

Network costs are highly location & season specific

Mapping can help identify priority areas for non-network alternatives(Decentralised Energy)0

5

10

15

20

25

30

35

ACT Qld NSW VIC* SA

Cen

ts p

er k

ilow

att-

hour

(A

UD

201

0)

GST

Carbon Price

ESS/REES

GGAS /Qld Gas

SRES

LRET

FiT

Metering

Retail

Distribution

Transmission

Generation

Electricity prices by state (2011/12)

Source: AEMC , Future Possible Retail Electricity Price Movements, 2011; Treasury modelling (*Vic = 2012)

isf.uts.edu.au

New Technology: This is just the beginning

isf.uts.edu.au

Distributed Generation

Cogeneration

Standby Generation

Biomass Generation

Small Gas Generation

Solar Photovoltaics

Energy Efficiency

Efficient motors & chillers

Efficient Lighting

Efficient showerheads

Efficiency Retrofits

Behaviour change

Peak Load Management

Interruptible loads

Power factor correction

Gas Chillers

Ice Storage

Electric to Gas Hot Water

Time of Use tariffs

Fuel Cells

Battery Storage

Electric Vehicles

Decentralised Energyincludes:

isf.uts.edu.au

THE CHANGING ELECTRICITY SECTOR

The past

Centralised supply

Forecast demand

Flat prices

Build least cost infrastructure

Little engagement with customers (end users)

The future

→ Decentralised supply

→ Manage demand

→ Cost reflective prices

→ Invest in least cost supply and demand side mix

→ Extensive engagement with customers(and retailers and service providers)

How to deliver a win-win for networks (NSPs) and customers?

Information and collaboration are key

NETWORKOPPORTUNITY MAPS

isf.uts.edu.au

Where within the electricity network do the most

cost-effective DE opportunities exist?

How much could DE be worth at these locations?

When are the key years and times of constraint?

To answer these questions, ISF created

Network Opportunity Maps(AKA….the Dynamic Avoidable Network Cost Evaluation or DANCE model)

A resource to show where/when to target Renewable Energy and DE technologies & services:• Annually updated through streamlined process• Consistently applied in every (NEM) jurisdiction • Freely available on online platform• Woven into Networks’ Demand Side Engagement

Strategies

isf.uts.edu.au

NETWORK OPPORTUNITY MAPS PROJECT

isf.uts.edu.au

NETWORK OPPORTUNITY MAPS PROJECT

• Three year project, Sept 2014 – Sept 2017• Funded by ARENA, UTS, NSW Govt, and Ergon Energy• Formal network business partners: Ergon Energy,

Electranet, TransGrid• Data provision and collaboration with all NSPs in the NEM• Produced on NICTA’s new Australian Renewable Energy

Mapping Infrastructure (AREMI) portal• http://nationalmap.gov.au/renewables/

• This is first public release of Sample Maps

PROJECT TIMELINE

Sample Maps

(Oct 2015)

Sample Maps

(Oct 2015)

1st Full Iteration

(May 2016)

1st Full Iteration

(May 2016)

2nd Full Iteration

(May 2017)

2nd Full Iteration

(May 2017)

isf.uts.edu.au

WHAT DATA GOES IN?

• All data comes from Network Service Providers

• For Sample Maps: generally as published in 2014 Distribution Annual Planning Reports, and 2015 Transmission Annual Planning Reports)

• Proposed network investments (augmentation, replacement, other)

• Cost of capital (WACC), depreciation

• NSP demand forecasts for each network asset

• Current capacity of lines and substations

• Zone substation region boundaries (+ how different assets connect)

• Hourly load data (load profiles)

isf.uts.edu.au

WHAT MAPS COME OUT?

1. Available Capacity (MVA)

2. Planned network investment ($m)

3. Value of potentially avoidable investment (‘annual deferral value; $/kVAyr)

4. Peak Day Available Capacity (% exceedance in each hour)

isf.uts.edu.au

WHAT NETWORK LEVELS ARE COVERED?

Network Opportunity Maps

THE MAPS: live onlineSee:http ://nationalmap.gov.au/renewables/

http://cfsites1.uts.edu.au/isf/news-events/newsarchive-detail.cfm?ItemId=31169

Network Opportunity Maps - Available Capacity

http://cfsites1.uts.edu.au/isf/news-events/newsarchive-detail.cfm?ItemId=31169

Network Opportunity Maps - Available Capacity

Network Opportunity Maps - Available Capacity

MAP 2: PROPOSED INVESTMENT[$MILLION BY YEAR]

See AREMI platform:

http://nationalmap.gov.au/renewables/

MAP 2: PROPOSED INVESTMENT [$m]

Map 2: Proposed Investment [$m]

Map 2: Proposed Investment [$m] ( c.f. NSW)

Note: Each zone has detailed clickable data

÷÷

ANNUAL DEFERRAL VALUE [$/KVA/YEAR]

x ( + )

http://cfsites1.uts.edu.au/isf/news-events/newsarchive-detail.cfm?ItemId=31169

Annual Deferral Value [$/kVA/year] - 2016

Annual Deferral Value [$/kVA/year] - 2017

Annual Deferral Value [$/kVA/year] - 2018

Annual Deferral Value [$/kVA/year] - 2019

Annual Deferral Value [$/kVA/year] - 2020

Annual Deferral Value [$/kVA/year] - 2021

MAP 4: HOURLY AVAILABLE CAPACITY(PEAK DAY- % OF FIRM CAPACITY)

• Compares forecast hourly demand to firm local network capacity

• BUT generally only provided where load is forecast to exceed capacity.

• Shown for peak day only (in relevant peak season). • Shows Transmission, Sub-transm’n & Distrib’n Zone capacity.

• Note that this map has changed from hourly deferral value in previous network opportunity map versions.

Hourly available capacity- Summer Peak Day, 1pm

PEAK DAY (HOURLY) AVAILABLE CAPACITY MAP

isf.uts.edu.au

PROJECT TIMELINE

Sample Maps

(Oct 2015)

Sample Maps

(Oct 2015)

1st Full Iteration

(May 2016)

1st Full Iteration

(May 2016)

2nd Full Iteration

(May 2017)

2nd Full Iteration

(May 2017)

isf.uts.edu.au

• Targeted User Feedback• Short user feedback survey (see project website)

isf.uts.edu.au

EXPECTED PROJECT OUTCOMES

• Develop a more diverse market of non-network service providers

• Enhance service offers and choice for customers

• Develop new business for NSPs in decentralised energy

• Demonstrate effective collaboration to deliver win-win outcomes for NSPs and customers

“Meeting the information of needs the new decentralised energy era”

Victoria is well placed to lead on CRNP and DE• Lower network investment in recent years• Less surplus capacity• Higher load at risk• Tradition of probabilistic network planning• Smart meter rollout means:

• Better understanding of network conditions

• More data on voltage excursions and other code noncompliance• More capacity for smarter control

• Network businesses looking for opportunities• Government desire to lead on new and clean technolo gy

isf.uts.edu.au

POLICY TOOLS FOR NETWORK DM

isf.uts.edu.au

Committed

1: Decoupling (via Revenue Cap)

2: Capital Savings Incentive (CESS)

3: Contestable Metering

4: Cost reflective network pricing

5: Customer Information

Proposed (DM Incentive Scheme)

6: Least cost objective

7: DM Incentive Payments

Potential

8: Voluntary DM targets

9. Performance Reporting

• Cost reflective pricing is crucial but not sufficient

• Clear accessible information is key to this more decentralised energy market

• The future needs more competition and more collaboration

• The future is in flux - flexibility is crucial

• Customers need better incentives - and so do utilities

Conclusions

QUESTIONS?

View the maps: http://nationalmap.gov.au/renewables/[click ‘Electricity Infrastructure’, ‘Network Opportunities – ISF’]

Chris Dunstan, chris.dunstan@uts.edu.au(02) 9514 4882

Ed Langham, edward.langham@uts.edu.au(02) 9514 4971