CHAIR FOR MANAGEMENT SCIENCE AND
ENERGY ECONOMICS
PROF. DR. CHRISTOPH WEBER
STORAGE EVALUATION IN
CONGESTED GRIDSBenjamin Böcker, Stefan Kippelt
Christian Rehtanz, Christoph Weber
Essen, 25.03.2015
Introduction
• Grid expansion primarily driven by
– Developing renewable energy sources (mainly photovoltaics and wind)
– Increasing decentralization of feed-in
• Storage operation primarily driven by
– Taking advantage of price differences between charging and discharging the storage
(Spot market, intraday market, increasing own consumption of pv feed-in)
– Provide reserve power and grid services to compensate forecasting errors of demand
and supply and intermittent infeed
Key questions:
– Is storage operation for grid purposes efficient?
– How should these storage operations been compensated?
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MOTIVATION 1 2 3 4
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• Regulatory framework
– Laws and regulations
– Planning rules and principles
• Markets
– Structure of prices
– Minimum requirements
(prequalification)
• Location and operation
– Distributed energy sources, loads
• Grids
– Current and future load necessary grid expansion
Key Drivers
Regulatory Framework
Markets
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MOTIVATION 1 2 3 4
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1. Motivation
2. Methods
3. Application
4. Conclusion
Agenda
STORAGE EVALUATION IN CONGESTED GRIDS 1 2 3 4
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• Competitive market
similar results as system optimization with perfect information
• System optimization
– Description of an overall perfect decision
– No direct evaluation of the additional value of storages by operation for grid purposes
– Ex-post analysis of possible sharing of cost savings
Set up of an optimization model
Economic Theory
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METHODS 1 2 3 4
DemandSupply
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Optimization Model – System Boundaries
Physical energy flows
Financial flows Grid
Storage
Markets
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METHODS 1 2 3 4
System Boundary
Analysis: Ex post
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• Minimizing cost for grid and storage operator
– Investment costs for the grid and storage
▪ Grid expansion (binary decision)
▪ Storage investment (Capacity and Volume)
– Compensation (Curtailment and non-served demand)
– Additional revenues on spot
Optimization Model – Objective Function / Overview
𝑚𝑖𝑛 𝐶𝑖𝑛𝑣𝑒𝑠𝑡𝑚𝑒𝑛𝑡 + 𝐶𝑐𝑜𝑚𝑝𝑒𝑛𝑠𝑎𝑡𝑖𝑜𝑛 − 𝑅𝑚𝑎𝑟𝑘𝑒𝑡
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METHODS 1 2 3 4
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• Storage operation under grid constraints
• Storage
– Level:
– Capacity:
Optimization Model – Main Restrictions
𝑐ℎ𝑎𝑟𝑔𝑖𝑛𝑔: 𝑦𝑆,𝐶 𝑡 ≤ 𝑅𝐶 𝑡 + 𝑏𝑔𝑟𝑖𝑑 ∙ 𝑅𝑎𝑑
𝑅𝐿,𝑆 𝑡 . . 𝐿𝑆 𝑡 + 1, 𝑢𝑆 = 𝐿𝑆 𝑡, 𝑢𝑆 + 𝑦𝑆,𝐶 𝑡, 𝑢𝑆 ∙ 𝜂𝑆 𝑢𝑆 − 𝑦𝑆,𝐷 𝑡, 𝑢𝑆
𝑅𝐾,𝐷 𝑡, 𝑢𝑆 . . 𝑦𝑆,𝐷 𝑡, 𝑢𝑆 ≤ 𝐾𝑆 𝑢𝑆
𝑅𝐾,𝐶 𝑡, 𝑢𝑆 . . 𝑦𝑆,𝐶 𝑡, 𝑢𝑆 ≤ 𝐾𝑆 𝑢𝑆
𝑅𝑉,𝑆 𝑡 . . 𝐿𝑆 𝑡, 𝑢𝑆 ≤ 𝑉𝑆 𝑢𝑆
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METHODS 1 2 3 4
𝑑𝑖𝑠𝑐ℎ𝑎𝑟𝑔𝑖𝑛𝑔: 𝑦𝑆,𝐷 𝑡 ≤ 𝑅𝐷 𝑡 + 𝑏𝑔𝑟𝑖𝑑−𝑒𝑥𝑝. ∙ 𝑅𝑎𝑑𝑑−𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 + 𝑦𝑐𝑢𝑟,𝑆 𝑡
Optimization Model
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Optimization Model – Overview
Grid Expansion Costs
Willingness to pay to the storage operator
Storage Costs
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METHODS 1 2 3 4
Scenario Data
Grid Data (local Feed-In)
Market Prices
Optimal storage investment and operationTrade-Off: Grid investment, storage investment and curtailment
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1. Motivation
2. Methods
3. Application
4. Conclusion
Agenda
STORAGE EVALUATION IN CONGESTED GRIDS 1 2 3 4
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• Based on NEP 2013, Second Draft (Reference year 2011)
scaled up according to 2023B
• Demand profiles: ENTSO-E, Renewable feed-in: EEX and local
weather data (adjusted for changed full load hours)
• Possibility of curtailment (especially PV)
• Compensation payments for curtailment
– Current average infeed tariff (33 €ct/kWh)
• Unbundling and contract law
• Financial framework (interest rate)
Scenario Data – Base Case
Optimization Model
Grid Expansion Costs
Willingness to pay to the storage operator
Storage Costs
Grid Data (local Feed-In)
Market Prices
Optimal storage investment and operationTrade-Off: Grid investment, storage investment and curtailment
Scenario Data
APPLICATION 1 2 3 4
Grid Data –Power Flow Calculation
• Limiting Curve Analysis
– Due to the unmeshed character of the chosen
grid configurations, a simplified power flow
calculation approach can be applied
– For a given line length, this approach calculates
limits for load and feedback under consideration of
thermal limits and the acceptable voltage range
– A demand for storage operation arises, when the
residual load exceeds the lines load and feedback
limits
• Conventional grid expansion
– Grid expansions are assumed as additional parallel
cables which split the installed RES in equal shares
– The cost for conventional line expansions are estimated
based on installed line length and feeder costs
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maximum load
maximum feedback
load
feedback
Line Length
Thermal Limitation Voltage Limitation (+/-4%)
Ac
tive
Po
we
r
APPLICATION 1 2 3 4
Grid Data –
Grid configuration and generation of local time series
• Low Voltage Stub Line
– Simulation of a classic stub line configuration
(the most frequent low voltage grid structure)
– Assumed cable cross-section is 150mm²
(the most frequent value in German low voltage grids)
– Assumed line length is 0.3 km
(the median value observed in the dena distr. grid study)
– Simulation of loads by use of a stochastic load
model based on smart metering data
• Simulation of local RES time series
– Simulation of RES time series by use of historic
weather model data in 7kmx7km resolution
– RES times series are scaled to 130% of line capacity
in order to provoke need for action of DSO
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~ ~ ~ ~
NAYY 4x150
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
1 11 21 31 41 51 61 71 81 91
Win
d [
%]
APPLICATION 1 2 3 4
Scenario Data
Optimization Model
Grid Expansion Costs
Willingness to pay to the storage operator
Storage Costs Market Prices
Optimal storage investment and operationTrade-Off: Grid investment, storage investment and curtailment
Grid Data (local Feed-In)
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• Storage Investment:
– (100€/kW, 200€/kWh, 20 years, 5.7%, 2% fixed o&m) 95% Efficiency
• Grid investment:
– 80 T€/km (dena distr. grid study) (40 years, 6.4%)
• Market
– Spot Price Simulation: Hybrid-Model (EWL)
▪ Two Step Simulation
– Fundamental price and additional stochastics
▪ According scenario data
– Mean Price: 42.6€/MWh (51.1 €/MWh in 2011)
– Number of neg. prices 233h (16h in 2011)
Costs and Market – Base Case
Grid Data (local Feed-In)
Scenario Data
Optimization Model
Willingness to pay to the storage operator
Optimal storage investment and operationTrade-Off: Grid investment, storage investment and curtailment
Grid Expansion CostsStorage Costs Market Prices
APPLICATION 1 2 3 4
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• One year, hourly (8760 timesteps)
• MIP solving in GAMS
• Connected with Matlab for sensitivities
Optimization Model
Grid Expansion CostsStorage Costs Market Prices
Grid Data (local Feed-In)
Scenario Data
Willingness to pay to the storage operator
Optimal storage investment and operationTrade-Off: Grid investment, storage investment and curtailment
Optimization Model
APPLICATION 1 2 3 4
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Key Input Parameters: 0.3 km, 30% Excess Feed-In PV, Compensation ø infeed tariff)
Result – Base Case
economically optimal avoid grid expansion and curtailment
Volume 38 kWh 88 MWh
Capacity 38 kW 55 MW
Load duration 1.0 h 1.6 h
full load cycles 1,297 ---
APPLICATION 1 2 3 4
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• Length of lines (low voltage grid)
– 0.1 km up to 1.6 km, Median: 0.3 km // 95% Quantile: 1,1 km // 99% Quantile: 1,6 km
• Excess Feed-In PV (in comparison to avoid curtailment)
– 10% to 150%
• Market (Sensitivity I):
– only grid purposes
– grid purposes and spot market
• Compensation Payments (Sensitivity II):
– Current average 33€ ct/kWh feed-in tariff – Current 13 €ct/kWh feed-in tariff
– Spot price – No curtailment
– No compensation
Sensitivities – Data
APPLICATION 1 2 3 4
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Optimal Decision – Market Sensitivity
Grid Grid + Storage Storage Storage (with curt.) No Inv. (curt. optional)
Only grid purposes spot market / grid purposes
APPLICATION 1 2 3 4
Optimal Investments:
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Optimal Decision – Compensation Sensitivity
Current average Current
Spot-Price No curtailment No compensation
APPLICATION 1 2 3 4
Grid
Grid + Storage
Storage
Storage (with curt.)
No Inv. (curt. optional)
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1. Motivation
2. Methods
3. Application
4. Conclusion
Agenda
STORAGE EVALUATION IN CONGESTED GRIDS 1 2 3 4
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• Optimal investment decision
– Highly dependent on:
▪ grid length and excess feed-in of PV
▪ Regulatory framework (unbundling, compensation payments)
• Value of storages:
– Storage investment only for grid purposes
Only in limited cases (Long length >700m, excess feed-In PV 1.5 to 2.3)
– Storage investment for grid purposes and restrictive operation on spot-market
Average grid-length: only with moderate excess feed-In
Grid-length above average: efficient in many cases
Summary (I/II)
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CONCLUSION 1 2 3 4
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• Advantage of storages:
– Mobility
– Application for short grid overload
– Possible to avoid or shift grid investment
– Possibility to optimize curtailment payments (grid perspective)
• Implementation of Reserve Market see upcoming paper
• More sensitivities:
– Voltage control
– storage investment costs
Summary (II/II)
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CONCLUSION 1 2 3 4
CHAIR FOR MANAGEMENT SCIENCE AND
ENERGY ECONOMICS
PROF. DR. CHRISTOPH WEBER
Many thanks! –Questions?
Contact: Benjamin Böcker
E-Mail: [email protected]
Phone: +49 201/183-7306
CHAIR FOR MANAGEMENT SCIENCE AND
ENERGY ECONOMICS
PROF. DR. CHRISTOPH WEBER
Backup Slides
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Optimal Decision – Market Sensitivity
(with voltages control)
Grid Voltage Control Storage Storage (with curt.) No Inv. (cur. optional)
Only grid pursoses spot market / grid purposes
APPLICATION 1 2 3 4
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Optimal Decision – Li-Ion Costs
Grid Grid + Storage Storage Storage (with curt.) No Inv. (curt. optional)
Low: 100 [€/kW], 200 [€/kWh]
APPLICATION 1 2 3 4
High: 120 [€/kW], 500 [€/kWh]
