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Forecasts for renewable energy and disaster management. Renate Hagedorn Scientific and Operational Management Division Deutscher Wetterdienst. ?. ?. ?. 2012: 25%. 2010: 18%. Motivation. Moving towards sustainable supply of energy based on renewables

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forecasts for renewable energy and disaster management
Forecasts for renewable energy and disaster management

Renate Hagedorn

Scientific and Operational Management Division

Deutscher Wetterdienst

motivation

?

?

?

2012: 25%

2010: 18%

Motivation
  • Moving towards sustainable supply of energy based on renewables
  • Focus on wind- and solar power production
  • Weather dependent, fluctuating power production

Contribution of Renewables [%] to

Total Power Production in Germany

a new component in the system

predictable

controllable

A new component in the system

Load + Net Transfer = RE + CE

65%

35%

Conventional Energy

Renewable Energy

Net Transfer

Energy Consumption

90%

challenge for tsos

German High-Voltage Transmission System

Challenge for TSOs
  • Ensure the balance between production and consumption at any time…
  • …under the constraint of limited grid capacity

Growing proportion of weather-dependent power production requires

new strategies for managing the power grid

role of transmission system operators tsos
Role of Transmission System Operators (TSOs)
  • Various options to guarantee stability of grid:
    • Re-dispatch of conventional power plants, transmission of surplus energy between regulatory areas, positive/negative energy reserves (pumping stations)
    • Down-regulation of renewable power plants
  • Unexpected events can jeopardise safety of grid:
    • Unexpected high production of power can cause failure of equipment (power transformation stations) with possible consequences also for neighbouring grids
    • Unexpected low production of power can cause shortages (load shedding)
hiw for pv power production
HIW for PV power production

Fog predicted, but not observed

„observed“

Difference: Day-Ahead Forecast ~ 6 GW, Intra-Day Forecast ~ 3 GW

Operating Reserve: ±4.5 GW

hiw for wind power production
HIW for wind power production

Observed wind below the level necessary for peak production

Prediction „Observation“

30.01.2013

30.01.2013

source: http://www.transparency.eex.com

(average electricity consumption: ~60 GW)

expected value of user function uf

〈UF(x)〉

=

UF (〈x〉)

〈x〉

Expected Value of user function 〈UF〉

(Theoretical) linear user function

expected value of user function uf1

UF (〈x〉)

〈UF(x)〉

〈x〉

Expected Value of user function 〈UF〉

Nonlinear user function

The expected value of the user function

is not equal to

the user function of the expected value,

but depends on the whole ensemble

so far the theory
So far the theory…
  • “In theory” the advantages of incorporating information on the level of uncertainty are acknowledged
  • R&D of TSOs actively ask for scenarios
  • Operation Managers are (partly) still reluctant to incorporate this information
  • Main concerns:
    • Accountability… “if something goes wrong we need to justify our decision”
    • Information overload… “too much information is confusing rather than helping”
  • The way forward:
    • Automatic (user-specific) systems to suggest “best decision”
    • Condensed (user-specific) presentation of information to prepare for alternative scenarios
  • Projects to explore this route just starting at DWD
new research projects
New research projects
  • Funding agency: Federal Ministry for Environment
  • Collaborative projects with partners in research and industry
  • EWeLiNE
    • Duration: 4 years, 12/2012 – 11/2016, 13 scientist positions
    • Highlight: assimilation of wind power production observations
  • ORKA
    • Duration: 3 years, 08/2012 – 08/2015, 2 scientist positions
    • Highlight: direct communication between developer and user on deficiencies in prediction system, i.e. frequent cycle of development-evaluation work
  • External advisory committee: industrial user and provider of weather- and power-prediction models, to:
    • discuss results
    • incorporate external experiences
    • insure that developments are geared towards the needs of general user
disaster management2

a broken link…

Disaster Management
  • What is GDACS?
    • GDACS is a cooperation framework under the United Nations umbrella. It includes disaster managers and disaster information systems worldwide and aims at filling the information and coordination gap in the first phase after major disasters.
    • GDACS provides real-time access to web-based disaster information systems and related coordination tools.
  • What services does GDACS provide?
    • provides alerts and impact estimations after major disasters
    • develops standards and guidelines for international information exchange in disasters
    • provides the real-time coordination platform
    • coordinates the creation and dissemination of disaster maps and satellite images
    • Detailed weather forecast are provided rapidly on demand by SARWeather
two levels of response

ECMWF EPS-FC

Noumea, New Caledonia

120 mm

08/03/2013, 12 UTC

110 mm

09/03/2013, 12 UTC

40 mm

10/03/2013, 12 UTC

50 mm

11/03/2013, 00 UTC

Two levels of response
  • An event (disaster) is detected:
    • Assessment of humanitarian impact
    • Actual response
  • An event (potential disaster) is predicted:
    • Depending on the level of (un)certainty preparations for actual response
    • Continuous update on prediction
summary
Summary
  • Growing proportion of energy supply based on renewables requires
    • new strategies to integrate meteorological information into decision-making
    • focus on reliable forecast systems
    • consideration of user defined high-impact events
  • National disaster relief organizations ask for
    • global early warnings for preparatory actions
    • frequent updates in the event of a possible disaster
    • consideration of individual vulnerability levels