challenges for storage operation and valuation

Challenges for storage operation and

valuation

Christoph Weber

StoBeS Final Workshop, Essen, 03/17/2016

• Storage perceived as key enabling technology for integrating large amounts of renewables

• Storage offers possibility to balance demand and supply at different moments in time

Arbitrage over time

• Storage may also temporally save excess production which can not be transported due to grid

limitations

Relief to grid congestions

• Various studies to investigate the optimal use of storage in a system context based on

deterministic system models with rather high temporal and spatial resolution

Impact of stochasticity (partial impredictability) of renewable infeed

on optimal storage operation and valuation?

Methodological research at cross-roads of Energy Economics and Finance

03/17/2016StoBeS Final Workshop, Essen

Motivation

2

Introduction 1 2 3 4 5

• Key perspectives for storage operation and valuation

– System perspective vs. investor perspective

• Key drivers for storage value and investment

– Markets, prices, costs, regulations

• Key methodological challenges

– Stochasticity, degradation of storages,

• Key assessment challenges

– Future scenarios


Key issues

3

Introduction 1 2 3 4 5


Agenda

4

1. Introduction

2. Valuation perspective

3. Drivers for storage operation and value

4. Methodological and assessment challenges

5. Conclusions

Challenges for storage operation and valuation 1 2 3 4 5

Pros:

• Reflects societal need for storage

• Reflects equilibrium solution in competition with other flexibility options

• Describes optimal use of storage in a system perspective

Cons:

• True stochastic modelling difficult to implement

• Disequilibria in real world hardly reflected in models

• Impact of distorting regulations frequently not modeled in detail

• Limited validity of resulting prices & investment decisions


Valuation perspective 1: System perspective

5

Valuation Perspectives 1 2 3 4 5

Pros:

• Reflects investor willingness to invest

• Capable of describing in detail the impact of regulations on storage

• Modelling of stochasticity more easily done

Cons:

• Feedback of investments on price not included

Results only valid for small investments (price takers, first-of-a-kind)

• Challenge to model valid price scenarios


Valuation perspective 2: Investor perspective

6

Valuation Perspectives 1 2 3 4 5


Agenda

7


1. Introduction




5. Conclusions

Operation for time arbitrage

Key drivers:

Accessible Markets

Price variability

Price Predictability

Regulation


Basic principle of storage operation and value creation

8

Storage

Sell highBuy low

Value of storage = Expected future cash flows from storage operation

Drivers for storage operation and valuation 1 2 3 4 5

• Volume (Electricity Consumption)

≈ 550 TWh ≈ 63 GW * 8760 h

• Average Price currently

≈ 22 EUR/MWh

Increasing Importance: Intraday spot market

Volume at EPEXSpot ≈ 38 TWh ≈ 4 GW * 8760 h


Accessible Market I: Spot market day-ahead

9


traded


Accessible Market II: Primary Reserve

10


• Volume (including NL, CH, AT)

≈ 0.8 GW * 8760 h

• Average Price

≈ 20 EUR/MW/h

• Minimum lot size +/- 1 MW

• Activation time < 30 s

Market segment for large batteries attractive


• Activation time < 5 min


Accessible Markets III: Secondary Reserve

11


Negative Positive

blue: primary time,

orange: secondary time

• Volume ≈ 2 GW * 8760 h positive & negative

• Average Capacity Price ≈ 5.9 / 2.4 EUR/MW/h


Accessible Markets IV: Tertiary Reserve

12


colors: different products


• Activation time < 15 min

• Volume ≈ 2 GW * 8760 h positive & negative

• Average Capacity Price ≈ 0.29 / 0.09 EUR/MW/h

Negative Positive

• Currently no markets for local congestion management & local system services

• System services also procured at national level

– Valid approach for reserve power

– For reactive power local provision necessary, but so far provided mostly by conventional units

without explicit remuneration

With new electricity market law no longer obligation to build a congestion-free grid

Potential benefits of use of storage in joint grid / market applications

Cf. talk of Stefan Kippelt later


(In-)Accessible Markets V: Local congestion management

/ system services

13


Price variability:

• mainly dependent on the slope of

the merit order curve at the current demand level

Price predictability:

• strongly dependent on renewables, load and outage forecast errors

• Considerable improvements in short-term forecast accuracy over last years (up to 3 days)

• Uncertainty month-ahead and beyond remain

Impact on storage operation dependent on size of storage & existence of natural inflows


Price variabilty and Price predictability

14


Impacts of regulation on storage operation and value through different channels, inter alia

• Regulation influencing wholesale market

price levels and variability

– Renewable support mechanisms,

– Carbon pricing

• Regulations on market entry barriers

– Lot size

– Prequalification for reserve power markets

• Regulations on retail markets

– Self-consumption incentives for prosumers

– Incentives for real-time-pricing


Regulation

15


• Regulations on grid-market interface

– Unbundling

– Grid usage fees

– Congestion management mechanisms

(e.g. zonal or nodal prices)

• Regulation on direct support for storage

– Investment subsidies

– …


Agenda

16


1. Introduction




5. Conclusions

Deterministic operation and valuation approach:

Solution of a deterministic optimization model

No particular methodological challenge except:

Large storage systems (e.g. system of interconnected hydroreservoirs)

System modelling with multiple technologies, multiple countries and high temporal resolution

Stochastic modelling:

Multiple uncertain factors

Short-term uncertainties with known distributions

Long-term uncertainties without known distributions

Modelling of sequential decision making without anticipation


Key methodological challenge: Coping with uncertainty

17

Methodological and assessment challenges 1 2 3 4 5

• Given a deterministic problem with problem size k · T (= 400)

k: number of decision variables per time step (e.g. 4), T: number of time steps (100)

• Now: Consideration of f stochastic factors (1) with s possible values (8)

problem size N · k · T

problem size k · N T = k · sf·T ≈ 8 · 1090

Curse of dimensionality of stochastic programming

Solution as full stochastic problem only possible if N and/or T are chosen as small

Solution through backward induction – stochastic dynamic programming if limited number of

state variables z (2, e.g. storage filling and aging status of battery) with discretized levels l (10)

problem size (k-l) · T · sf · lz = 1.6 · 105


Stochastic modelling

18


N = sf stochastic cases per time step

• Scenario: possible future

• Describes a setting that is consistent in itsself – plausible but not necessarily probable

• Probability not readily assigned

Use of a hybrid fundamental-stochastic model to develop consistent scenarios based on

Renewable expansion scenario

Conventional generation fleet

Fuel & CO2 prices

Demand

….

Cf. further presentations


Future scenarios

19



Agenda

20


1. Introduction




5. Conclusions

Project has developed

• Novel methodologies

– For stochastic assessment of storage operation and value

– For modelling stochastic input factors

• Considered key application cases

– Market oriented storage operation

– Optimization of self-consumption

– Combined use of storage for grid and market purposes


Final remarks

21

Conclusions 1 2 3 4 5

Many Thanks

Contact: Christoph Weber

E-Mail: [email protected]

Phone.: +49 201/183-2966

mailto:[email protected]

challenges for storage operation and valuation

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