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
OVERVIEW 1. Challenges 2. Network Opportunity Maps � Information for the decentralised energy era 3. Conclusions
CHALLENGES
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 isf.uts.edu.au
CENTRALISED ELECTRICITY SUPPLY: Have we already peaked? Energy efficiency Rooftop solar PV Annual Energy Forecast for the NEM (NEFR, June 2014) isf.uts.edu.au
PEAK DEMAND – Still rising? Low load factor = higher prices Source: 2015 AEMO National Electricity Forecasting Report (NEFR) (June 2014)
ELECTRICITY NETWORKS: LOCATION, LOCATION, TIME 35 Electricity prices by state (2011/12) GST Networks comprise >50% 30 Carbon Price Cents per kilowatt-hour (AUD 2010) power bills (nationally) ESS/REES 25 GGAS /Qld Gas SRES 20 Network costs are highly LRET location & season specific 15 FiT Metering 10 Mapping can help identify Retail priority areas for non- Distribution 5 network alternatives Transmission (Decentralised Energy) 0 Generation ACT Qld NSW VIC* SA 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
Decentralised Energy Peak Load Management includes: Time of Use tariffs Ice Storage Battery Storage Interruptible loads Electric Vehicles Power factor correction Electric to Gas Hot Water Gas Chillers Fuel Cells Behaviour change Biomass Generation Small Gas Generation Efficient motors & chillers Solar Photovoltaics Cogeneration Efficient Lighting Efficient showerheads Standby Generation Efficiency Retrofits Energy Distributed Generation Efficiency isf.uts.edu.au
THE CHANGING ELECTRICITY SECTOR How to deliver a win-win for networks (NSPs) and customers? The past The future → Decentralised supply Centralised supply → Manage demand Forecast demand → Cost reflective prices Flat prices → Invest in least cost supply and demand side mix Build least cost infrastructure → Extensive engagement with customers Little engagement with (and retailers and service providers) customers (end users) Information and collaboration are key isf.uts.edu.au
NETWORK OPPORTUNITY MAPS
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 D ynamic A voidable N etwork C ost E valuation or DANCE model) isf.uts.edu.au
NETWORK OPPORTUNITY MAPS PROJECT 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 • 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 isf.uts.edu.au
PROJECT TIMELINE 1 st Full 1 st Full 2 nd Full 2 nd Full Sample Sample Maps Maps Iteration Iteration Iteration Iteration (Oct 2015) (Oct 2015) (May 2016) (May 2016) (May 2017) (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)
WHAT MAPS COME OUT? 1. Available Capacity (MVA) 2. Planned network investment ($m) 3. Value of potentially avoidable investment (‘annual deferral value; $/kVAyr) 4. Peak Day Available Capacity (% exceedance in each hour) isf.uts.edu.au
WHAT NETWORK LEVELS ARE COVERED? isf.uts.edu.au Network Opportunity Maps
THE MAPS: live online See: http://nationalmap.gov.au/renewables/
Network Opportunity Maps - Available Capacity http://cfsites1.uts.edu.au/isf/news-events/newsarchive-detail.cfm?ItemId=31169
Network Opportunity Maps - Available Capacity http://cfsites1.uts.edu.au/isf/news-events/newsarchive-detail.cfm?ItemId=31169
Network Opportunity Maps - Available Capacity
MAP 2: PROPOSED INVESTMENT [$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 ( + ) ÷
Annual Deferral Value [$/kVA/year] - 2016 http://cfsites1.uts.edu.au/isf/news-events/newsarchive-detail.cfm?ItemId=31169
Annual Deferral Value [$/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 1 st Full 1 st Full 2 nd Full 2 nd Full Sample Sample Maps Maps Iteration Iteration Iteration Iteration (Oct 2015) (Oct 2015) (May 2016) (May 2016) (May 2017) (May 2017) • Targeted User Feedback • Short user feedback survey (see project website) isf.uts.edu.au
EXPECTED PROJECT OUTCOMES “Meeting the information of needs the new decentralised energy era” • 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 isf.uts.edu.au
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 technology isf.uts.edu.au
POLICY TOOLS FOR NETWORK DM 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 isf.uts.edu.au
Conclusions • 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
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
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