1. Build wind capacities at windy locations
Build wind capacities at windy locations? Assessment of system optimal wind locations under feed-in tariffs
Frank Obermüller
This presentation: Close the gap between meteorological side (i.e. high resolution wind data) and energy economics (i.e. market value of wind or the impact to the electricity market)
07th January 2017 | Frank Obermüller

2. Motivation Aim for market integration of renewables
IEA Report (June 2016):
„[Renewable subsidy] plans should be based on the long-term value of VRE to the power and wider energy system.“
“Next-generation approaches need to factor in the system value of electricity from wind and solar power”
Regional wind values | Jan. 07, 2017 | Frank Obermüller

3. Motivation Value of a wind turbine to the system
with:
Market value of wind production:
Hirth: “The market value of variable renewables: The effect of solar wind power variability on their relative price." Energy economics 38 (2013)
Elberg, Hagspiel: “Spatial dependencies of wind power and interrelations with spot price dynamics.” European Journal of Operational Research 241 (2015)
Hirth, Lion. "The market value of variable renewables: The effect of solar wind power variability on their relative price." Energy economics 38 (2013):
Measures on a national level
Finding: Market value of wind is decreasing with increased capacity (Bildchen is nett)
Cirtic: No inner-country differentiation with respect to regional wind speeds
Elberg, Hagspiel. “Spatial dependencies of wind power and interrelations with spot price dynamics.” European Journal of Operational Research 241 (2015):
Inner-regional market value of wind is calculated (Focus: Germany)
Approach: Copulas – Dependent Distributions of regional wind production time series and the time series of the electricity market price
Advantage: Can incorporate simultaneous effects such as cannibalization effects (much capacity at one location reduces market prices)
Finding: Regional different market values: Lower at locations with high wind capacity (Bildchen)
Critic: No grid congestions are incorporated. In situations with grid congestions, redispatch is necessary and wind in overproduction region has a negative value (since it need to be replaced with more expensive power plants)
My approach:
Not regional market value of wind but regional system value of wind
Incorporated regional market prices, regional wind production, and transmission situation.
Value = p_loc * g_loc / p_loc * 1
Extension via high resolution wind data from meteorological institute and wind turbine database
Market value
Expected market value of wind
[EUR/MWh]
Regional wind values | Jan. 07, 2017 | Frank Obermüller

4. Motivation But: Uniform pricing can be inefficient!
Market value of wind production:
with:
Several electricity markets have uniform pricing, e.g. Europe
In uniform pricing, grid situations may not be internalized sufficiently
This can lead to inefficient capacity allocations and production situations
Improvement: System value of wind production:
Hirth, Lion. "The market value of variable renewables: The effect of solar wind power variability on their relative price." Energy economics 38 (2013):
Measures on a national level
Finding: Market value of wind is decreasing with increased capacity (Bildchen is nett)
Cirtic: No inner-country differentiation with respect to regional wind speeds
Elberg, Hagspiel. “Spatial dependencies of wind power and interrelations with spot price dynamics.” European Journal of Operational Research 241 (2015):
Inner-regional market value of wind is calculated (Focus: Germany)
Approach: Copulas – Dependent Distributions of regional wind production time series and the time series of the electricity market price
Advantage: Can incorporate simultaneous effects such as cannibalization effects (much capacity at one location reduces market prices)
Finding: Regional different market values: Lower at locations with high wind capacity (Bildchen)
Critic: No grid congestions are incorporated. In situations with grid congestions, redispatch is necessary and wind in overproduction region has a negative value (since it need to be replaced with more expensive power plants)
My approach:
Not regional market value of wind but regional system value of wind
Incorporated regional market prices, regional wind production, and transmission situation.
Value = p_loc * g_loc / p_loc * 1
Extension via high resolution wind data from meteorological institute and wind turbine database
with:
Regional wind values | Jan. 07, 2017 | Frank Obermüller

5. Methodology Nodal Electricity Market Model
Minimization of total system costs
Electricity balance restriction (supply=demand)
Model and input data are open source
Website:
Some model facts:
Research Focus on Germany
Uniform pricing
regional different wind situations
high share of installed wind capacities
585 nodes
852 lines
DC-loadflow model
FIAS=Frankfurter Institute for Advanced Science, Renewable Energy Group.
Regional wind values | Jan. 07, 2017 | Frank Obermüller

6. Methodology Nodal Electricity Market Model
Additional input:
High-resolution wind data
FIAS=Frankfurter Institute for Advanced Science, Renewable Energy Group.
Regional wind values | Jan. 07, 2017 | Frank Obermüller

7. Results System value of regional wind production
Regional System Value of Wind (Nodal pricing)
Histogram
Wind value [100%]
Frequency
Regional market value of wind (based on zonal pricing, no grid situation included)
Value_loc = p*g_loc / p*1
Finding:
Differences occur
Reason: Different production profiles which are correlated differently as to the market price profile
The Regional System Value of Wind Production could have structural breaks, e.g., as in Germany
*) Note: Colormap is restricted to a minimum of 80% for comparison reasons
Regional wind values | Jan. 07, 2017 | Frank Obermüller

8. Results Comparison: System Value vs. Market Value
Regional System Value of Wind (Nodal pricing)
Regional Market Value of Wind (Uniform pricing)
Regional market value of wind (based on zonal pricing, no grid situation included)
Value_loc = p*g_loc / p*1
Finding:
Differences occur
Reason: Different production profiles which are correlated differently as to the market price profile
The regional value of wind is strongly dependent on the pricing regime (and thus on the grid situation)
Regional wind values | Jan. 07, 2017 | Frank Obermüller

9. Results Comparison: Regional market profits
Market profit under Nodal pricing
Market profit under Uniform pricing
Can be considered as efficient benchmark since grid situation is internalized to market profits
Uniform pricing may favor regions which are not system optimal and, e.g., increase grid congestions
Lot of the values are close to each other
Some values have great differences
In South: Regional value under nodal pricing is higher
In North: lower.
This is distortion between market value with and without grid side internalized.
The pricing regime (nodal vs. uniform) influences the regional market profits.
Under uniform pricing, inefficient allocations may be incentivized
Regional wind values | Jan. 07, 2017 | Frank Obermüller

10. Results Comparison: Nodal market profit vs. Fixed FiT
Market profit under Nodal pricing
Wind profit of Fixed Feed-in Tariff
(for 1 MW turbine, 1 year)
(for 1 MW turbine, 20 years)
Left: Wind profit:
Higher in the North
Lower in the South
Right: Wind value
Higher in the South
Lower in the North
Excactly opposite
A Fixed Feed-in Tariff (without a regional component) does not sufficiently consider the regional value of wind and may favor different (sub-optimal) wind locations
Regional wind values | Jan. 07, 2017 | Frank Obermüller

11. Conclusion Contribution to existing research:
Quantification of (1) regional system values, (2) regional market values, and (3) fixed feed-in remunerations for German wind production
Findings:
The Regional System Value of Wind Production could have structural breaks, e.g., as in Germany
The pricing regime (nodal vs. uniform) influences the regional market profits. Under uniform pricing, inefficient allocations may be incentivized
A Fixed Feed-in Tariff (without a regional component) does not sufficiently consider the regional value of wind and may favor different (sub-optimal) wind locations
Conclusion:
A well-designed subsidy scheme needs to incorporate the regional system value
This can be achieved, e.g., via nodal pricing and a market price component
A fixed feed-in tariff may set wrong capacity allocation incentives
Regional wind values | Jan. 07, 2017 | Frank Obermüller

12. Exploring Energy Markets – Enhancing Decisions!
Frank Obermüller
EWI – Institute of Energy Economics at the University of Cologne
ewi Energy Research & Scenarios gGmbH
Alte Wagenfabrik
Vogelsangerstraße 321
D Cologne
Regional wind values | Jan. 07, 2017 | Frank Obermüller

13. Backup / Appendix
Regional wind values | Jan. 07, 2017 | Frank Obermüller

14. Results Current reimbursements of fixed feed-in tariff
Wind profit of Fixed Feed-in Tariff 1
Modelled wind production data per turbine 2
Calculated reimbursements based on Fixed Feed-in Tariff
How calculated:
modelled wind production data per turbine
obtained from weather model
Based on 20-year wind speed data
Regional high resolution (6x6 km)
Production per turbine averaged to one production year
Calculated to eeg 2014 reimbursement
(5+x) years starting reimbursement (X.X €cent/kWh)
(15-x) base reimbursement (X.X €cent/kWh)
X is dependent on the individual wind production compared to the wind production of a reference turbine (for 5 years)
The lower the individual wind production (to reference), the longer the starting reimbursement
Of an exemplary wind turbine:
1 MW Turbine
66m Hub-Height
2380 m2 swept area
Regional wind values | Jan. 07, 2017 | Frank Obermüller