STORAGE EVALUATION IN CONGESTED GRIDS

transcript

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

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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

Storage Costs

Market Prices

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

feedback

Line Length

Thermal Limitation Voltage Limitation (+/-4%)

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

1 11 21 31 41 51 61 71 81 91

APPLICATION 1 2 3 4

Scenario Data

Optimization Model

Storage Costs Market Prices

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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

Scenario Data

Optimization Model

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

Scenario Data

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 + Storage

Storage

Storage (with curt.)

No Inv. (curt. optional)

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1. Motivation

2. Methods

3. Application

4. Conclusion

Agenda

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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

ENERGY ECONOMICS

Many thanks! –Questions?

Contact: Benjamin Böcker

E-Mail: benjamin.boecker@uni-due.de

Phone: +49 201/183-7306

ENERGY ECONOMICS

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]

STORAGE EVALUATION IN CONGESTED GRIDS

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