INNOVATIVE GRID-IMPACTING TECHNOLOGIES
ENABLING A CLEAN, EFFICIENT AND SECURE ELECTRICITY SYSTEM IN EUROPE
The sole responsibility for the content of this presentation lies with the authors. It does not necessarily reflect the opinion of the European Union. Neither the EACI nor the European Commission are responsible for any use that may be made of the information contained therein.
Bettina Burgholzer Energy Economics Group (EEG) Vienna University of Technology
14th IAEE European Energy Conference Rome, 31 October 2014
Cost/Benefit Analysis of further Expansion of the Austrian
Transmission Grid to enable further RES-E Integration
Overview
About the project
Methodology of bottom-up model
Austrian Case description
Selected results of scenarios
2020: without/with expansion of Salzburg Transmission Power Line
2050: implementation of FACTS & DLR
Conclusions
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About the project
GridTech is a project co-funded by the European Commission under the Intelligent Energy Europe Programme.
GridTech’s main goal:
Conduct a fully integrated assessment of new grid-impacting technologies and their implementation into the European electricity system.
Contract number:
IEE/11/017 / SI2.616364
Full title:
Impact Assessment of New Technologies to Foster RES-Electricity Integration into the European Transmission System
Duration:
May 2012 - April 2015
Budget:
EUR 1,958,528
EC contribution:
EUR 1,468,896
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Pan-European study (top-down approach)
Regional case studies (bottom-up approach)
Results and recommendations
Innovative technologies
screening
Cost-benefit methodology
RES integration: market issues
Transmission expansion:
non-technical barriers
Project objectives & structure Assess the non-technical barriers for transmission expansion and market compatible renewable electricity integration in Europe
Develop a robust cost-benefit analysis methodology on investments
Apply and verify the cost-benefit analysis methodology for investments in the transmission grid
Achieve a common understanding among key actors and target groups on best practise criteria
Deliver tailor-made recommendations and action plans
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Pan-European study
EU30+ zonal model Top-down approach:
Target countries (bottom-up modelling)
• Used tool: MTSIM, developed and analyses done by Ricerca sul Sistema Energetico - RSE S.p.A. Milano
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Bottom-up methodology: Input/Output and Optimisation EDisOn (Electricity Dispatch Optimization): Linear Optimisation Problem (LOP) formulated in MATLAB® and solved by Gurobi-Solver! (cp. (Burger et al., 2007), (Shahidehpour et al., 2002))
Target function: Minimisation of the total system costs
Constraints: • Demand • Capacity • Ramping Limits • Reservoirs balance • Spill of hydro and RES-E
generation technologies • DC power flow
(PTDF-Matrix, cp. (Van den Bergh et al., 2014))
Input
•hourly based: Demand, Wind, PV, RoR and PHES inflow
•power plant data
•primary energy prices, CO2 certificate prices and specific CO2 emissions
•WP4: Exchanges and Prices
Market Model
•Linear Optimisation Problem (LOP)
•minimisation of the total generation costs
•s.t. technical constraints
Solving Model with
Gurobi-Solver
Output
hourly based RoR, PHS and thermal
production, Exchanges, Flows, Storage level, wholesale electricity
prices, etc.
CBA
Calculation of benefits
(welfare, CR, changes in fossil fuel needs and CO2 emissions)
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Economic outputs How to model? How to measure?
Flexibility
FACTS Sensitivity analyses Increase of the overall welfare
DLR NTC=f(Temperature) Increase of the overall welfare
HVDC Point to point Increase of the overall welfare
Should we combine flexibility and controllability to one economic output?
Security of supply Not Supplied Energy (NSE) NSE (VoLL=Value of Lost Load)
How to model security of supply / not supplied energy? And how to measure?
Controllability FACTS, HVDC NSE, Spillage, …
Congestion rent (Price differences between the nodes of a
transmission line) x (load flow) Million € per year
Congestion losses Redispatch costs Redispatch costs
Social welfare producer and consumer surplus
Price, demand, production costs Million € per year
Fossil fuel need Calculation of the need of fossil fuel Primary energy demand of the different
kinds of thermal power plants (generation/(lowercalorificvalue*eff))
CO2-Emission Calculation of the total CO2 emission of each
country and per node
CO2-emissions per year
(Million tons of CO2)
RES curtailment Energy in excess Energy remunerated
(e.g. at market prices / feed-in tariff)
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Modelling FACTS & DLR
• Parameters: • DLR ∈ ℝ𝐻
• 𝛼𝑚𝑎𝑥 = 30°
• Decision Variable: 𝛼𝑙𝑝𝑠𝑡,ℎ
• Constraints:
8
0 1000 2000 3000 4000 5000 6000 7000 80000
20
405060
80
100
120
140
hours
%
DLR Wind
Wind Util
< 0.5 100 %
< 0.8 105 %
< 1 115 %
with
Temperature
Source: presentation at RWTH Aachen
(Puffer, 2010).
Source: dena-Netzstudie II,
2010.
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Incidence Complex conductance
phase angle
Austrian Case description 24 nodes: 17 correlate with
the main substations within Austria and 7 neighbouring ones
35 transmission power lines (TPL): All parallel transmission power lines between the nodes are taken together to one representative transmission power line.
Grid Technology Focus
2020 HVAC line Salzburg
2030 HVAC line Carinthia DLR and FACTS
2050 HVDC line (e.g. Brenner) DLR and FACTS Storage (PHS)
TIR_w TIR_eSBG_s
SBG_n
OOE_e
NOE
NOE_n
W
NOE_s
STMK_s
KTN_e
KTN_w
OTIR
STMK_w
STMK
OOE_w
VBG
DE1
DE2
CZ
HU
SI
IT
CH
380 kV220 kV
110 kV
Germany
Czech Republic
Hungary
Slovenia
Italy
Switzerland
4028
1030
2600
1900
3500
2518
1866
2685
428
1700
1700
3092
3092
518
492
518
518
518
2300
400
2417
518
2573
2148
298
550
1321
389
104
1296
2573
5400
5400
777
5400
*
*
*
*
*
*
* interaction with Pan-European study by RSE
2030
2020
Source: Austrian Power Grid,
Masterplan 2030.
Source: own illustration.
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Selected results: wo/w TPL expansion 2020
(2020A) without expansion
(2020B) with expansion
CO2 certificate price
10 EUR/ton CO2
Total demand: 73.67 TWh
Total installed Capacity: 31 GW, of which are …
Wind: 3.2 GW
PV: 1.2 GW
RoR: 5.6 GW
PHS: 10.2 GW
wo/w Salzburg expansion:
Not Supplied Energy (NSE): 0 MWh
0,02
0,01
0,33
0,30
- 0,05 0,10 0,15 0,20 0,25 0,30 0,35
(2020A)
(2020B)
RES curtailment (GWh)
10
0
10
20
30
40
50
60
1 501 1001 1501 2001
EUR
/MW
h
time (hours)
mean (2020A): 34,97 / mean (2020B): 34,88
(2020A) (2020B)
Peak Price duration curve
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6686
0
0 5000 10000 15000 20000 25000
(2020A)
(2020B)
(cumulated number of hours)
Load factor of TPLs > 70 % Salzburg TPL
Selected results: wo/w TPL expansion 2020
(2020A) without expansion
(2020B) with expansion
CO2 certificate price
10 EUR/ton CO2
Total demand: 73.67 TWh
Total installed Capacity: 31 GW, of which are …
Wind: 3.2 GW
PV: 1.2 GW
RoR: 5.6 GW
PHS: 10.2 GW
wo/w Salzburg expansion:
Not Supplied Energy (NSE): 0 MWh
Load factor of TPL Salzburg vs. Export/Import AT-DE
Load factor of TPL Salzburg vs. PHS
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(2020A) (2020B)
Export from AT Export from AT Import to AT Import to AT
0 1000 2000 3000 4000 5000 6000 7000 80000
0.5
1
1.5
2
2.5
3
3.5
Congestion R
ent
(1.0
00 E
UR
)
annual CR: 11758 EUR
0 1000 2000 3000 4000 5000 6000 7000 80000
20
40
60
Nodal P
rices (
EU
R/M
Wh)
mean price: SBGn 34.67 EUR/MWh, SBG
s 34.67 EUR/MWh
SBGn
SBGs
0 1000 2000 3000 4000 5000 6000 7000 8000
-2
0
2
hours
utilization of TPL
GW
h/h
𝑁𝑃𝑉 𝐶𝑅 = 1+ 𝑖 −𝑡 ⋅ 𝐶𝑅𝑡
𝑇
𝑡=1
,
𝐶𝐵𝐴: 𝑁𝑃𝑉(𝐶𝑅)
𝐼𝑛𝑣𝑒𝑠𝑡𝑚𝑒𝑛𝑡𝐶𝑜𝑠𝑡> 1
A nodal pricing approach within a control zone would not give enough incentives to invest in extending the TPL in Salzburg.
regulated grid tariffs are still necessary
0 1000 2000 3000 4000 5000 6000 7000 80000
0.5
1
1.5
2
2.5
3
3.5
Congestion R
ent
(1.0
00 E
UR
)
annual CR: 234735 EUR
0 1000 2000 3000 4000 5000 6000 7000 80000
20
40
60
Nodal P
rices (
EU
R/M
Wh)
mean price: SBGn 34.93 EUR/MWh, SBG
s 34.65 EUR/MWh
SBGn
SBGs
0 1000 2000 3000 4000 5000 6000 7000 8000
-2
0
2
hours
utilization of TPL
GW
h/h
Selected results: wo/w TPL expansion 2020
12
Wit
ho
ut
Sa
lzb
urg
ex
pan
sio
n
Wit
h S
alz
bu
rg e
xp
an
sio
n
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Selected results: with FACTS & DLR in 2050
• Total generation costs for Austria can be reduced by 28% (663 Mio. EUR)
• CO2 emissions can be reduced by 3% (127 kt CO2)
(2050A) reference scenario (2050B) with FACTS & DLR
Assumptions:
• Every TPL can be adjusted by phase shifters (| |≤ 30°)
• Dynamic Line Rating (DLR) based on wind intensity and temperature
CO2 certificate price: 100 EUR/ton CO2
Total demand: 90.7 TWh
Total installed Capacity: 53 GW, of which are …
Wind: 7 GW
PV: 18 GW
RoR: 6.7 GW
PHS: 14 GW
44
5
57
24
116
45
- 50 100 150 200
(2050A)
(2050B)
RES curtailment (GWh)
Wind curtailment PV curtailment RoR curtailment
∑ RES generation
hydrogeneration
turbgeneration
pumpconsumption
thermalgeneration
Difference B-A 1% 0% 2% 8% -2%
1%
0%
2%
8%
-2%
-4%
-2%
0%
2%
4%
6%
8%
• Curtailment: Wind -89%, PV -58%, RoR -61%
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Conclusions
… for the time horizon 2020 & 2030 • TPL expansion (from 220kV to 380kV) in Salzburg and in Carinthia is very
important for closing the Austrian 380 kV circle
• Significant for national and European RES integration (connection of wind in the east and PHS in the west)
… for the time horizon 2050 • FACTS and DLR can reduce RES curtailment significantly
… for Cost/Benefit Analysis • Congestion Rent (CR) as a revenue for CBA approach only makes sense if
it is an expansion of a cross-border connection
• regulated grid tariffs are still necessary in the future, especially within a control zone
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Thank you!
For more information about the project, please visit:
www.gridtech.eu
Photo credits: ABB, Siemens, Verbund, TenneT, OE, WIP
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http://www.gridtech.eu/
References • M. Burger, B. Graeber, and G. Schindlmayr, Managing energy risk: An integrated view on power and other
energy markets. Chichester, England, Hoboken, NJ: John Wiley & Sons, 2007.
• M. Shahidehpour, H. Yamin, and Z. Li, Market operations in electric power systems: Forecasting, scheduling, and risk management. [New York]: Institute of Electrical and Electronics Engineers, Wiley-Interscience, 2002.
• K. Van den Bergh, E. Delarue, and W. D'haeseleer, DC power flow in unit commitment models. TME Working Paper - Energy and Environment, 2014.
• R. Puffer, www.forum-netzintegration.de/uploads/media/DUH_Puffer_WS1_06052010.pdf, 2010.
• dena-Netzstudie II, Integration erneuerbarer Energien in die deutsche Stromversorgung im Zeitraum 2015 – 2020 mit Ausblick 2025, http://www.dena.de/publikationen/energiesysteme/dena-netzstudie-ii.html, 2010.
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http://www.forum-netzintegration.de/uploads/media/DUH_Puffer_WS1_06052010.pdfhttp://www.forum-netzintegration.de/uploads/media/DUH_Puffer_WS1_06052010.pdfhttp://www.forum-netzintegration.de/uploads/media/DUH_Puffer_WS1_06052010.pdfhttp://www.dena.de/publikationen/energiesysteme/dena-netzstudie-ii.htmlhttp://www.dena.de/publikationen/energiesysteme/dena-netzstudie-ii.htmlhttp://www.dena.de/publikationen/energiesysteme/dena-netzstudie-ii.htmlhttp://www.dena.de/publikationen/energiesysteme/dena-netzstudie-ii.htmlhttp://www.dena.de/publikationen/energiesysteme/dena-netzstudie-ii.htmlhttp://www.dena.de/publikationen/energiesysteme/dena-netzstudie-ii.html
Appendix: Grid-impacting technologies
• Onshore and offshore wind energy
• Large-scale solar technologies: Concentrated Solar Power (CSP) and Photovoltaic (PV)
Electricity generation technologies, with a focus on variable RES-E
• Pumped Hydro Energy Storage
• Compressed Air Energy Storage
Bulk energy storage technologies
• HVDC - High Voltage Direct Current, both VSC (Voltage Source Converter)-based and CSC (Current Source Converter)-based
• FACTS - Flexible Alternating Current Transmission System
• PST - Phase Shifting Transformers
• WAMS - Wide Area Monitoring System
• DLR/RTTR - Dynamic Line Rating/Real-Time Thermal Rating-based devices
Transmission technologies directed at improvements in network control and flexible electricity system operation
Demand Response Technologies/ Measures and electric vehicles
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