solar and wind power forecasting

Jan Schmelter

Euro Arab Training Course:

SMART GRID AND INTEGRATION OF RENEWABLE ENERGY

Granada, Spain

28th April 2016

>>>Solar and wind power forecasting

>>>Company profile

Integration of renewables into grids and markets Service provider for energy meteorology since 2004 Areas of business

– Wind and solar power predictions worldwide

– Predictions for grid operators and traders

– Software for Virtual power plants and demand side management

– Development

• Industry projects

• National and international research projects

70 people

>>>Choice of international customers

PJM Interconnection

BPABonneville Power Administration

Tennessee Valley Authority

>>>Areas with operational forecasting experience

about 80GW wind power 48GW solar power

>>>Central Questions

Why are power predictions necessary?



Who needs wind and solar power predictions?




What are the recommendations to implement forecasts?





How does a power prediction work?






Why is a power prediction difficult?


Why are power predictions necessary? Who needs wind and solar power predictions?




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Grid load without wind power


wind and solar power depends on meteorological conditions

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Residual load due to renewable production




>>>lo

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Residual load due to renewable production




contribution of wind and solar must be known in advance

power forecasts provide schedule of expected generation

>>>How does a wind power prediction look like?

Schedule containing 24 or 96 values per day

Single plants or aggregate

Optional confidence bands

>>>How does a solar power prediction look like?

Schedule containing 24 or 96 values per day

Single plants or aggregate

Optional confidence bands



Who needs wind and solar power

predictions? What are the recommendations to implement forecasts?



>>>Who needs wind and solar power forecasts?

grid operators (TSOs, DSOs)– balancing– dispatch / re-dispatch– load flow calculations– congestion management



energy traders– trading wind and solar power on energy markets– influence of renewable energy on spot market price



energy traders– trading wind and solar power on energy markets– influence of renewable energy on spot market price

wind farm / solar plant operators– schedule maintenance– send schedule to grid operator


Time scale of forecast Stakeholder Area of application

Shortest-term(0 – 6 h)

Traders Trading on intraday energy marketControl of curtailment due to negative market price

Grid operatorsload dispatch centerssystem operators

Balancing Unit re-dispatchCurtailment of power plants

Speculators Influence of renewable production on market price

Short-term(6 – 48 h)

Traders Trading on day-ahead energy marketParticipation in regulation marketInfluence of reneables on market price


Unit dispatchLoad flow calculationsDA congestion forecast

Plant operators Day-ahead planning of maintenance

Medium-term(2 – 10 days)

Traders Trading on long-term markets


2DA congestions forecastWeek-ahead planning

Plant operators Medium-term planning of maintenance




What are the recommendations to implement

forecasts? How does a power prediction work?


>>>Integration of forecasting right from the beginning

>>>National register of wind and solar plants

Register should contain following standing data of new installations for every unit:

unique identifier for each unit technology of the generator (i.e. wind, pv, csp) installed capacity of each generator geographical location of each generator according to the World

Geodetic System 1984 as a degree in decimals associated grid connection point for wind turbines: hub height and rotor diameter for PV modules: inclination angle and orientation date of initial operation and date of decommissioning if the generated power is used on location or only fed in to the grid

>>>The plant register for renewables in Germany

Forecaster

plant register


Forecaster

plant register

Federal NetworkAgency


Forecaster

plant register


TSO


Forecaster

plant register


TSO No 4

TSO No 3

TSO No 2

TSO No 1


Forecaster

plant register


TSO No 4

TSO No 3

TSO No 2

TSO No 1

~ 20

directmarketers


Forecaster

plant register


TSO No 4

TSO No 3

TSO No 2

TSO No 1

~ 20

directmarketers DSOs

~ 880

>>>

~ 20

directmarketers

The plant register for renewables in Germany

Forecaster

plant register


TSO No 4

TSO No 3

TSO No 2

TSO No 1

DSOs

~ 880


Forecaster

plant register


TSO No 4

TSO No 3

TSO No 2

TSO No 1

DSOs

Wind farmowners

~ 20.000

~ 880~ 20

directmarketers


Forecaster

plant register


TSO No 4

TSO No 3

TSO No 2

TSO No 1

DSOs

Wind farmowners

~ 20.000

~ 880~ 20

directmarketers

Solar plantowners

~ 3.000.000


Forecaster

plant register


TSO No 4

TSO No 3

TSO No 2

TSO No 1

DSOs

Wind farmowners

~ 20.000

~ 880~ 20

directmarketers

Solar plantowners

~ 3.000.000

some othercompanies


Forecaster

plant register


TSO No 4

TSO No 3

TSO No 2

TSO No 1

DSOs

Wind farmowners

~ 20.000

~ 880~ 20

directmarketers

Solar plantowners

~ 3.000.000

some othercompanies

TRANSPARENCY?

>>>The plant register for renewables: the transparent way

Forecaster

plant register

Federal NetworkAgency / TSO

Wind farmowners

Solar plantowners

>>>Grid code requirements

The grid code should contain the following data for every unit:

power output (real power output) available active power (power output due to meteorological conditions) Information on scheduled availability of wind farms and solar plants in

terms of effective installed power to cover e.g. scheduled maintenance, known outages of machines

Information on current availability of units Information on scheduled curtailment, i.e. limits to power output Information on currently activated curtailment by grid operators or

dispatch centres Meteorological data that measure the available resource

Wind farms: wind speed and direction close to hub height Solar plants: solar irradiation (direct and diffuse separately if possible)





How does a power prediction work? Why is a power prediction difficult?

>>>

Goal is power conversion:

transfer meteorological variables into power output of wind or solar plants

Basic approaches to wind and solar power prediction

>>>

Goal is power conversion:

transfer meteorological variables into power output of wind or solar plants

state of the art: use of numerical weather prediction models (NWP)

Basic approaches to wind and solar power prediction

>>>State of the art: prediction systems

physical model

statisticalpost processing

different NWPs

standing dataof power plants

final forecast

online data

forecaster external data

>>>How do numerical prediction models see the world?

>>>Gridded!

>>>With different spatial resolutions!


approx. 40 km


approx. 40 km

approx.9 km

>>>Spatial interpolation needed

grid points

site to be forecasted

>>>… vertical interpolation is also needed

100 m

10 m

wind speed

heig

hthub height unstable

NWP datastable

NWP data

wind profile changes with atmospheric conditions

>>>Combination of weather models

Weighting factors according to capabilities in different weather situations

Weather classification

Weather data

wind powerprediction

Single wind power predictions

>>>Benefit of combination

wind power

>>>

combination

measurement

solar power prediction

Benefit of combination

>>>

Forecast improvement due to intelligent model combination !

combination

measurement

solar power prediction

Benefit of combination

>>>Different types of forecast errors

Large amount of different types of errors:

… errors in meteorological forecasts




… errors in power transformation





… unknown status of power plants

>>>„Artificial“ forecasting errors due to unknown plant status

Wind farm availability below 100 %

>>>„Artificial“ forecasting errors due to unknown plant status

Wind farm availability below 100 %

Wind farm shut down due to grid congestion

>>>To be considered: curtailment and scheduled outages

Prediction using curtailment information(wind farm limited to 80 MW)

Prediction assuming full availability of wind farm (200 MW installed capacity)

Time schedules for planned outages or curtailments can be transmitted to Previento to be considered in the forecasts.





… unknown status of power plants

… difficult meteorological situations

>>>Difficult meteorological situations: wind

ROTOR BLADE ICING


STABILITY EFFECTS


TIMING OF COLD FRONTS


STORM – CUT OFF


SNOW ON PV MODULES


SAHARA DUST


FOG


CONVECTIVE CLOUDS AND THUNDERSTORMS


SOLAR ECLIPSE

>>>… some more literature

Variable Renewable Energy Forecasting - Integration into Electricity Grids and Makets - A Best Practice Guide

Release: Original publication July 2015

>>>

Thanks for your attention!www.energymeteo.com

Jan [email protected]

solar and wind power forecasting

Data & Analytics