Potential network benefits of concentrating solar thermal generationJay Rutovitz, 24th June 2013

Project Consortium Consortium 

• Australian Solar Thermal Energy Association (AUSTELA) • Institute for Sustainable Futures (UTS)• Centre for Energy and Environmental Markets (UNSW)

Ergon Energy major project partner; other network operators provided data and collaborating on case studies (Essential, Transgrid, Electranet, SP Ausnet, Powercor, SA Power Networks)

ARENA Emerging Renewables Program – 66% of funding

Project objectivesQuantify potential economic network benefit from installing CST in grid constrained areas

Identify and map locations where CST could provide cost‐effective network support services before 2020 

Four case studies (one each state) of CST in promising locations

Engage TNSPs and DNSPs about CST as an alternative to network augmentation

Project overview

TASK 3 Map cost effective

distributed CST

TASK 1Quantify and Map network constraint

zones (ISF)

TASK 2Map of potential

firm capacityUNSW

TASK 4 1 CASE STUDY PER

STATE

Project overview

TASK 3 Map cost effective

distributed CST

TASK 1Quantify and Map network constraint

zones (ISF)

TASK 2Map of potential

firm capacityUNSW

TASK 4 1 CASE STUDY PER

STATE

Interactive on web

Why?

CST provides energy storage for dispatchable output

CST has reliability to provide network services

Network spending significant driver of rising electricity prices, CST has potential to reduce network spending

Potential to accelerate Australian CST deployment

Allows greater adoption of renewable generation by complementing intermittent resources

To answer these questions, we created  

DANCEThe Dynamic Avoidable Network Cost 

Evaluation Model

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?

TASK 1 – MAPPING NETWORK CONSTRAINTS

The mapping…

• SEE GOOGLE EARTH FILE

Task 1 – Quantifying potentially avoidable investment

** draft results for Vic * Most of SA investment for one site

  QLD NSW VIC** SA Total Total investment 2013 to 2024 $477 m $128 m $485 m $242 m $1,332 m Number of constraints 24 10  44 3 81   Proposed nvestment 2013 – 2024(locations with DNI>20) $473 m $73 m $76 m $231 m* $852 m

Number of constraints 22 6  10 2 40    

Task 2 – Indicative Firm Capacity from CST (1)

Model uses hourly DNI as key input (2009 –2011) to calculates energy flows

For each location takes the 21 highest peak events for winter afternoon, winter evening, summer afternoon, summer evening periods

For each event determines whether CST would have been generating

Indicative Firm Capacity is taken as average value of output over the 21 events

Modelling indicative firm capacity from CST (2)

Dispatch strategy: start at 12 noon and keep going flat out until storage empty (ienot optimum for meeting peak)

6 different storage configurations• 0 hr 1 hr 3 hr

5 hr 10 hr 15 hr

INDICATIVE FIRM CAPACITY – SUMMER AFTERNOON, 1 HR STORAGE

INDICATIVE FIRM CAPACITY – SUMMER AFTERNOON, 5 HR STORAGE

INDICATIVE FIRM CAPACITY – WINTER EVENING, 1 HR STORAGE

INDICATIVE FIRM CAPACITY – WINTER EVENING, 5 HR STORAGE

INDICATIVE FIRM CAPACITY – WINTER EVENING, 10 HR STORAGE

INDICATIVE FIRM CAPACITY – WINTER EVENING, 15 HR STORAGE

Indicative firm capacity

Most locations can reach 90% IFC and above by increasing storage hours

These results for crude dispatch strategy; could certainly improve to get better availability at peak times

Task 3 - Cost effectiveness

Integrate solar mapping with network constraint mapping, 

1st question: where can CSP avoid the need for network augmentation?

2nd question: what is the cost benefit LCOE – pool price – LRET – network support payment

Can CSP avoid the need for network augmentation?

QLD NSW VIC SA All states All locations  21 6 21 3 51

% of all locations   90% 75%  54%  100% 70% 

% of locations with DNI > 21  90% 

100% 100% 100% 94% 

DRAFT RESULTS

What is the cost effect?

DRAFT RESULTS

  QLD  NSW VIC  SA  All states

Positive cost benefit  29%  0%  13%  100%  25% 

Proportion where  cost benefit > ‐$20     43%  20%  13%  100%  39% 

 

Cost benefit DRAFT results – best sites

 

  Charleville ZS Emerald ZS Monash TS (new line)Proposed network investment $70.0 m $24.0 m $226.0 mCommissioning year  2022 2020 2022DNI (MJ/m2/yr)  25.1  24.1  23.4           Optimal plant   Plant size (MW)  18  70  47 storage (hours)  3  5  1 Indicative Firm Capacity 91% 84% 85%Total plant cost ($m)  $113 m $405 m $224 mAnnual Network Support Payment ($/yr)  $5.2 m  $1.8 m  $16.6 m 

 COST BENEFIT CALCULATION       LCOE  $160  $135  $164 Electricity sales   $74 $65 $108Carbon price effect  $62 $52 $83LGC $16 $28 $16NSP contribution ($/MWh) $79 $6 $143BENEFIT ($/MWh)  $70 $17 $185

Cost benefit DRAFT results – best sites

  Charleville ZS  Emerald ZS  Monash TS (incremental) Proposed network investment  $70.0 m  $24.0 m  $10 m Commissioning year  2022 2020 2022DNI (MJ/m2/yr)  25.1  24.1  23.4  Optimal plant          Plant size (MW)  18 70 47storage (hours)  3  5  1 Indicative Firm Capacity  91% 84% 85%Total plant cost ($m)  $113 m  $405 m  $224 m Annual Network Support Payment ($/yr) $5.2 m $1.8 m $0.7 m       COST BENEFIT CALCULATION  LCOE  $160  $135  $164 Electricity sales   $74 $65 $108Carbon price effect  $62  $52  $83 LGC  $16 $28 $16NSP contribution ($/MWh)  $79  $6  $6 BENEFIT ($/MWh)  $70  $17  $48  

Cost effectiveness by year (DRAFT results)

0%10%20%30%40%50%60%70%80%90%

100%

2014 2016 2018 2020 2022 2024

(excluding sites <20 MJ/m2/day)

Proportion of sites where cost benefit > ‐$20

QLD

NSW

VIC

SA

Task 4 - Case studies - approach

1 per state, in collaboration with DNSPExamine whether CST can meet the

constraintExamine business caseWorkshop with network provider

… some interesting outcomes so far re HOW to meet constraint

Type of contraints by state

0

2

4

6

8

10

12

14

16

18

Growth Voltage Reliability N‐1 SOS

Num

ber o

f con

straints 

South Australia

NSW

Queensland

THANK YOU