Introduction to Electricity Network Modelling
Introduction to Electricity Network Modelling
PhD Winterschool, Oppdal March 2011
Daniel Huppmann & Friedrich Kunz
Agenda 1. Introduction to Electricity Markets 2. The Electricity Market Model (ELMOD)
3. Congestion Management 4. Exercise: 3-Node Network
5. Introducing Wind Power 6. Exercise: Stochastic Multi-Period European Network
7. Outlook and further developments Literature
-2-
Electricity •
Non storable
•
Grid-bound
•
High fix cost ratio
•
Economies of scale in generation and transmission
•
Daily and seasonal demand patterns
•
Power flows according to physical laws (Kirchhoff)
Value added chain 1. Generation 2. Transmission/Distribution 3. Supply
-3-
Electricity Generation
Source: ENTSO-E -4-
Electricity Generation Capacities hydro
nuclear
fossil_fuels
regen
140 120
80 60 40 20
SK
SI
RS
RO
PT
PL
NL
MK
ME
LU
IT
HU
HR
GR
FR
ES
DK_W
DE
CZ
CH
BG
BE
0
BA
capacity [GW]
100
Source: ENTSO-E -5-
Plant Capacity and Peak Load in Germany 2006 Sufficient capacity to supply Germany and still export: 140
120 Renewable
Power [GW]
100
80
thereof 23,8
non available capacity
6,4 7,9
outages and revision reserve capacities
PSP. Oil Gas
has to be covered 60
Coal
available capacity
86,2
40 Nuclear
77,8
20 Lignite
0
Hydro
Planttype
Power Banlance
Peak Load
At time of peak load an export surplus of 2.1GW occured Source: VDN 2006 -6-
The Merit-Order Cost Curve and Pricing under Competition Price [€/MWh]
Demand
Merit Order
Competiton
Quantity [MWh] Competiton -7-
European High Voltage Network
Source: ENTSO-E -8-
4 Voltage Levels • German network operators maintain 1.6 mio km of lines and 500 000 transformer stations •Transmission
•Voltage Level
•Coverage
•Consumer
Extra High Voltage
220 … 380 kV
national
Regional suppliers, large industry, imports/exports
•Distribution
•Voltage Level
•Coverage
•Consumer
High Voltage
36 … 110 kV
regional
Local suppliers, industry
380-kV 220-kV
Medium Voltage
1 … 36 kV
regional
Industry, large commercial
DC Cable Sub station
Low Voltage
0,4 … 1 kV
local
Households, Agriculture, Commercial Source: VDN -9-
Physical Electricity Exchange
Source: ENTSO-E - 10 -
Electricity Demand
Source: ENTSO-E - 11 -
Agenda 1. Introduction to Electricity Markets 2. The Electricity Market Model (ELMOD)
3. Congestion Management 4. Exercise: 3-Node Network
5. Introducing Wind Power 6. Exercise: Stochastic Multi-Period European Network
7. Outlook and further developments Literature
- 12 -
Introduction • Electricity markets are in a process of restructuring • Economic modeling of electricity markets not possible without accounting for technical constraints
• Model-based research of electricity markets very common, e.g. in the US (Hogan, Hobbs, UC Berkeley, ...) • Economic-engineering model-based research for Germany and Europe available rather limited
• Development of ELMOD: Engineering-Economic Approach
- 13 -
Scope of the Model Physical model (included countries): ENTSO-E Portugal, Spain, France, Netherlands, Belgium, Luxembourg, Denmark, Germany, Switzerland, Austria, Italy, Poland, Hungary, Czech Republic, Slovenia and Slovakia … Nodes:
2120
(substations)
Lines: thereof:
3143 106 1887 1150
150kV 220kV 380kV
- 14 -
Market Assumptions and Data • Market: - No strategic players Perfect competition - Perfect market bidding (marginal cost bids, no market power) - Independent SO optimizes generation dispatch and network usage simultaneously
• Node demand: - Linear inverse demand function constructed using - a reference demand, - a reference price, and - a point demand elasticity - Reference demands are based on ENTSO-E data and distributed to system nodes according to regional population and/or gross domestic product - Reference prices are based on the spot prices of the national energy exchange
• Wind input: - Given as external parameter based on wind distributions derived from historic data
• Reference: Leuthold et al. (2010)
- 15 -
Model Formulation
- 16 -
Model Formulation Objective Function and Constraints Given:
generation capacities, network, demand function, wind
Decide about: generation, demand
max (Social Welfare) subject to: demand
=
generation + netinput
generation
PhD Winterschool, Oppdal March 2011
Daniel Huppmann & Friedrich Kunz
Agenda 1. Introduction to Electricity Markets 2. The Electricity Market Model (ELMOD)
3. Congestion Management 4. Exercise: 3-Node Network
5. Introducing Wind Power 6. Exercise: Stochastic Multi-Period European Network
7. Outlook and further developments Literature
-2-
Electricity •
Non storable
•
Grid-bound
•
High fix cost ratio
•
Economies of scale in generation and transmission
•
Daily and seasonal demand patterns
•
Power flows according to physical laws (Kirchhoff)
Value added chain 1. Generation 2. Transmission/Distribution 3. Supply
-3-
Electricity Generation
Source: ENTSO-E -4-
Electricity Generation Capacities hydro
nuclear
fossil_fuels
regen
140 120
80 60 40 20
SK
SI
RS
RO
PT
PL
NL
MK
ME
LU
IT
HU
HR
GR
FR
ES
DK_W
DE
CZ
CH
BG
BE
0
BA
capacity [GW]
100
Source: ENTSO-E -5-
Plant Capacity and Peak Load in Germany 2006 Sufficient capacity to supply Germany and still export: 140
120 Renewable
Power [GW]
100
80
thereof 23,8
non available capacity
6,4 7,9
outages and revision reserve capacities
PSP. Oil Gas
has to be covered 60
Coal
available capacity
86,2
40 Nuclear
77,8
20 Lignite
0
Hydro
Planttype
Power Banlance
Peak Load
At time of peak load an export surplus of 2.1GW occured Source: VDN 2006 -6-
The Merit-Order Cost Curve and Pricing under Competition Price [€/MWh]
Demand
Merit Order
Competiton
Quantity [MWh] Competiton -7-
European High Voltage Network
Source: ENTSO-E -8-
4 Voltage Levels • German network operators maintain 1.6 mio km of lines and 500 000 transformer stations •Transmission
•Voltage Level
•Coverage
•Consumer
Extra High Voltage
220 … 380 kV
national
Regional suppliers, large industry, imports/exports
•Distribution
•Voltage Level
•Coverage
•Consumer
High Voltage
36 … 110 kV
regional
Local suppliers, industry
380-kV 220-kV
Medium Voltage
1 … 36 kV
regional
Industry, large commercial
DC Cable Sub station
Low Voltage
0,4 … 1 kV
local
Households, Agriculture, Commercial Source: VDN -9-
Physical Electricity Exchange
Source: ENTSO-E - 10 -
Electricity Demand
Source: ENTSO-E - 11 -
Agenda 1. Introduction to Electricity Markets 2. The Electricity Market Model (ELMOD)
3. Congestion Management 4. Exercise: 3-Node Network
5. Introducing Wind Power 6. Exercise: Stochastic Multi-Period European Network
7. Outlook and further developments Literature
- 12 -
Introduction • Electricity markets are in a process of restructuring • Economic modeling of electricity markets not possible without accounting for technical constraints
• Model-based research of electricity markets very common, e.g. in the US (Hogan, Hobbs, UC Berkeley, ...) • Economic-engineering model-based research for Germany and Europe available rather limited
• Development of ELMOD: Engineering-Economic Approach
- 13 -
Scope of the Model Physical model (included countries): ENTSO-E Portugal, Spain, France, Netherlands, Belgium, Luxembourg, Denmark, Germany, Switzerland, Austria, Italy, Poland, Hungary, Czech Republic, Slovenia and Slovakia … Nodes:
2120
(substations)
Lines: thereof:
3143 106 1887 1150
150kV 220kV 380kV
- 14 -
Market Assumptions and Data • Market: - No strategic players Perfect competition - Perfect market bidding (marginal cost bids, no market power) - Independent SO optimizes generation dispatch and network usage simultaneously
• Node demand: - Linear inverse demand function constructed using - a reference demand, - a reference price, and - a point demand elasticity - Reference demands are based on ENTSO-E data and distributed to system nodes according to regional population and/or gross domestic product - Reference prices are based on the spot prices of the national energy exchange
• Wind input: - Given as external parameter based on wind distributions derived from historic data
• Reference: Leuthold et al. (2010)
- 15 -
Model Formulation
- 16 -
Model Formulation Objective Function and Constraints Given:
generation capacities, network, demand function, wind
Decide about: generation, demand
max (Social Welfare) subject to: demand
=
generation + netinput
generation
