Impact of wind power on power system operation

Impact of Wind Energy on Power System Operation Joris Soens web-event Leonardo ENERGY 16 February 2006 Katholieke Universiteit Leuven Faculteit Ingenieurswetenschappen Departement Elektrotechniek (ESAT) Afdeling ELECTA

Presentation Outline

Introduction: wind power in Belgium, state of the art

installed power, turbine types

interaction with power grid

Dynamic modelling of wind power generators

Aggregated wind power in the Belgian control area

hourly time series

value of wind power

Conclusions

Introduction Dynamic Modelling Aggregated Wind Power Conclusions

I. Wind power, state of the art

Levels of installed wind power in Europe Introduction Dynamic Modelling Aggregated Wind Power Conclusions Installed [MW] end 2003 New [MW] 2004 Installed [MW] end 2004 Germany 14.609 2.037 16.629 Spain 6.203 2.065 8.263 Denmark 3.115 9 3.117 ... Netherlands 910 197 1.078 ... Belgium 68 28 95 (> 160 in 2005) Europe (EU25) 28.568 5.703 34.205

Control options for wind turbines

Speed control

fixed speed

variable speed limited range

variable speed wide range

Reactive power control

Blade angle & active power control

fixed blade

pitchable blade

Yaw control

highly dependent on generator type Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Generator types for wind turbines (I)

squirrel cage induction generator

nearly fixed speed

always inductive load

Turbine Grid shaft & gearbox wind SCIG ~ Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Turbine generator types (II)

doubly fed induction generator

variable speed – limited range

reactive power controllable

shaft & gearbox DFIG Converter ~ Grid Crowbar Turbine Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Turbine generator types (III)

synchronous generator, direct drive

variable speed – wide range -> no gearbox

reactive power controllable

Introduction Dynamic Modelling Aggregated Wind Power Conclusions SG Turbine Converter ~ Grid Permanent Magnet OR Field Winding

Interaction with power grid

Until recently:

wind power = negative load

Now:

wind power = actively contributing to power system control

ride-through capability

voltage control

output power control

specific grid connection requirements

development requires dynamic models

Example: ride-through requirement

Wind turbine disconnects at light grid disturbance

Disconnection causes new grid disturbance

Cascade-effect may result in major sudden loss of wind power

Example:

Spain, February 26, 2004

600 MW loss of wind power due to one grid fault

Therefore: definition of voltage profiles that must not lead to disconnection

Example: ride-through requirement by E.ON Netz (Germany)

Each voltage dip remaining above red line must not result in disconnection of the generator

Within the grey area, extra reactive power is demanded from the wind power generator to deliver voltage support

II. Dynamic modelling of wind power generators

Dynamic modelling of wind turbines for use in power system simulation

Power system simulation software:

simulate dynamically short-circuits, load steps, switching event ....

interaction wind turbine model and grid model:

grid controlled wind turbine grid dispatch & control wind speed injected current voltage at turbine node reference P and Q controlled grid parameters Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Detailed turbine model with doubly fed induction generator v wind u turb q ref p ref i turb Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Detailed turbine model: simulation examples

step-wise wind speed increase

voltage dip at turbine generator

Detailed turbine model: simulation example I (1) simulation input: step-wise increasing wind speed wind speed at hub height 400 600 800 1000 1200 1600 1800 2000 10 20 [m/s] time [s] Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Detailed turbine model: simulation example I (2) 400 600 800 1000 1200 1600 1800 2000 time [s] 0,5 1 power [p.u.] variable speed & pitch control fixed speed & pitch control fixed speed & no pitch control turbine power for increasing wind speed Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Detailed turbine model: simulation example I (3) 400 600 800 1000 1200 1600 1800 2000 time [s] 0,5 1 speed [p.u.] turbine speed for increasing wind speed variable speed turbine constant speed turbine Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Detailed turbine model: simulation example I (4) zoom on turbine speed variable speed: propeller speed variable speed: generator speed fixed speed: propeller speed fixed speed: generator speed 995 1000 1005 1010 1015 1020 1025 0.95 1 1,05 time [s] speed [p.u.] Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Detailed turbine model: simulation example II (1) 1000 1001 1002 voltage at turbine generator 0.4 0.6 1 [p.u.] 0.8 0.2 time [s] simulation input: voltage dip at turbine generator Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Detailed turbine model: simulation example II (2) 1000 1005 1010 1015 time [s] 0.9 1 1.1 1.2 speed [p.u.] propeller speed generator speed propeller and generator speed during voltage dip, for fixed-speed turbine with induction generator Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Detailed turbine model: simulation example II (3) propeller and generator speed during voltage dip, for variable-speed turbine with doubly fed induction generator 1000 1005 1010 1015 time [s] 0.9 1 1.1 1.2 speed [p.u.] propeller speed generator speed Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Dynamic turbine model: conclusions

Detailed model allows

examination of interaction between turbine and grid

electrical & mechanical quantities

good understanding of turbine behaviour

thorough insight in mechanical and electrical behaviour of turbine/grid

simulation of ‘heavy’ transients

help to set up connection requirements

III. Aggregated wind power in the Belgian control area Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Wind power in Belgium 95 MW wind power in total installed by end of 2004 (onshore) One offshore wind farm (216 - 300 MW) permitted and near construction phase (start construction soon) Legal supporting framework for offshore wind farms ‘established’ in January 2005 Best wind resources are offshore or in the west part (near shore) Introduction Dynamic Modelling Aggregated Wind Power Conclusions

High voltage grid in Belgium Introduction Dynamic Modelling Aggregated Wind Power Conclusions 150 kV 220 kV 400 kV

Aggregated wind power in the Belgian control area

Time series of aggregated wind power

Value of aggregated wind power

Time series for aggregated wind power

Research project ELIA - ELECTA

Research goal

estimation of hourly fluctuation of aggregated wind power in Belgium

Use

estimation of need for regulating power

estimation of value of wind power

Available data

Wind speed measurements at three sites in Belgium

Scenarios for future installed wind power

Available wind speed data Wind speed data from meteo-stations Ostend, Brussels, Elsenborn Three-year period (2001 – 2003), hourly resolution Anemometer height: 10 m Complementary to data from European Wind Atlas (turbulence, landscape roughness…) Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Available wind speed data Ostend 140 km Brussels 110 km Elsenborn 60 km 140 km prevailing wind direction Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Scenarios for installed wind turbines

Turbine type parameters:

power curve

hub height

Developed algorithm allows arbitrary number of types

In following application: two turbine types

Scenario I Evenly distributed Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Scenario II Concentrated Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Scenario III One offshore farm Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Scenario IV Scen. II + Scen. III Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Algorithm output: aggregated wind power time series Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Quantization of power fluctuations: power transition matrices

Number of occurrences that a power value in hour H is in given range

As a function of power value in hour H – 1, H – 4….

Example: H vs. H-1 matrix for Scenario 1

H vs. H-1 matrices for all scenarios Scenario I Scenario II Scenario III Scenario IV Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Value of aggregated wind power

Possible indicators for value of wind power

Capacity factor

Capacity credit

Potential reduction of CO 2 -emission by total power generation park in Belgium

Capacity factor

Calculated for separate turbine or for aggregated park

Most important parameter for turbine exploiters, when money income ~ produced energy

capacity factor = annual energy production [MWh] installed power [MW] x 8760 [h] Introduction Dynamic Modelling Aggregated Wind Power Conclusions Scenario capacity factor [%] equivalent full-load hours I 20 1752 II 26 2278 III 31 2715 IV 29 2540

Capacity credit: definition

reliable capacity

amount of installed capacity in a power system, available with given reliability to cover the total power demand

loss of load probability (LOLP)

probability that total power demand exceeds the reliable capacity

capacity credit of wind power

Amount of conventional power generation plants that can be replaced by a given level of wind power, without increase of the LOLP

Capacity credit: calculation H( 0 ) = LOLP = 4 h/year Assumption: probability that Total power demand > (reliable capacity + D MW ) Impact of additional power generator (park), with production probability p( P plant ) Introduction Dynamic Modelling Aggregated Wind Power Conclusions

LOLP graphical Introduction Dynamic Modelling Aggregated Wind Power Conclusions 0 500 4 3 2 1 0 D (Demand not served) [MW] [hour/year]  = 30 Q peak = 13.5 GW H(0) = 4 h/year LOLP H (D )

Capacity credit graphical 0 500 4 3 2 1 0 D (Demand not served) [MW] H (D ) & H 2 (D) Introduction Dynamic Modelling Aggregated Wind Power Conclusions [hour/year]

Absolute capacity credit for wind power in Belgium 1000 2000 3000 4000 0 100 200 300 400 5000 Installed wind power [MW] Capacity credit [MW] Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Shortcomings of capacity factor/credit as value indicator

Moment of energy production?

Instantaneous demand for electrical energy?

Energy production in next time sample?

True value indicator must reflect difference of a chosen paramater, between case with and without wind power

This requires

Knowledge of entire power system

Dynamic simulation of entire power system

Dynamic simulation of entire power system (1)

Simulation tool PROMIX (‘Production Mix’)

Input data:

Parameters for all power plants in control area

Power range

Costs of start-up and continuous operation

Time for start-up and power regulation

Fuel consumption, gas emissions... for various operating regimes

Time series of aggregated load in control area (resolution: 1 hour)

Dynamic simulation of entire power system (2)

Output:

Optimal power generation pattern for every hour

Fuel consumption, emissions, costs... for every plant & hour

Integrating wind power time series in input data

As equivalent reduction of aggregated load

For large values: ‘reliable’ wind power required

Results: CO 2 -emission abatement for various levels of installed wind power

Relative annual abatement of CO 2 -emission Scenario I 5 10 15 20 0 2 4 6 8 Installed wind power [% of peak demand] CO 2 emission abatement [% of reference case] Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Relative annual abatement of CO 2 -emission 5 10 15 20 0 2 4 6 8 Installed wind power [% of peak demand] Introduction Dynamic Modelling Aggregated Wind Power Conclusions Scenario III CO 2 emission abatement [% of reference case]

Conclusions Value of wind power

Capacity factor: 20 - 31 % (spreading)

Capacity credit: 30 -10 % (installed power)

CO 2 emission abatement:

Optimum: 4% reduction for installed wind power equal to 5% of peak demand ( = 700 MW)

IV. Conclusions

Conclusions (1)

Technical challenges for wind power integration are identified

Dynamic models are developed

responding to needs of quantifying higher electrical & mechanical demands towards wind turbines

detailed dynamic models, assessing all mechanical/electrical quantities

simplified dynamic models, allowing rough estimates of wind power absorption potential at busbar

Hourly fluctuations of aggregated wind power in Belgium are quantified

Value of wind power in Belgium assessed with three indicators

Capacity factor

Capacity credit

Abatement of CO 2 -emission by total power generation park

> 700 MW installed power: wind power ≠ negative load

Conclusions (2) Introduction Dynamic Modelling Aggregated Wind Power Conclusions

Recommendations for further research

Accurate wind speed forecasting

Integrating forecast updates in implementation of electricity market

Electricity storage

Demand side management

Impact of wind power on European border-crossing power flows

Introduction Dynamic Modelling Aggregated Wind Power Conclusions Impact of wind energy in a future power grid Ph.D Joris Soens – 15 december 2005, K.U.Leuven http://hdl.handle.net/1979/161