aspects of relevance in offshore wind farm reliability assessment nicola barberis negra...

Aspects of Relevance in Offshore Wind Farm Reliability

Assessment

Nicola Barberis Negra

[email protected]

2nd PhD Seminar on Wind Energy in Europe

Risø National Laboratory, 4-5 October 2006

5th October 2006 Nicola Barberis Negra - [email protected] 2

Outline

• Introduction to Reliability

• Why Wind Generation into Reliability

• Example of Evaluation

• Conclusions

• Questions


Outline




• Conclusions

• Questions


Introduction - Definition

What is Reliability?

“Overall ability of the system to perform its function adequately, for the period of time considered, under the operation conditions intended”

Reliability in Power System

• Operation

• Planning


Introduction – Structure of Reliability

Generating Units and Load

HLI + Transmission System

HLII + Distribution System

Generation facilities

Transmission facilities

Distribution facilities

Hierarchical Level I

(HLI)

Hierarchical Level II

(HLII)

Hierarchical Level III

(HLIII)


Introduction – Structure of Reliability

Two new aspects

• Distributed Generation

• Private Suppliers

Generating Units and Load

HLI + Transmission System

HLII + Distribution System

Generation facilities

Transmission facilities

Distribution facilities

Hierarchical Level I

(HLI)

Hierarchical Level II

(HLII)

Hierarchical Level III

(HLIII)


Introduction – Evaluation Methods

• Deterministic solutions

– First used approaches

– No uncertainty can be included

• Probabilistic methods

– Analytical models or simulations

– Uncertainty may be included

– Broad range of studies


Outline




• Conclusions

• Questions


Why Wind Energy

• New structure of power systems

– Increase of installed capacity (e.g. Germany)

– Increase of wind energy penetration (e.g. Denmark)

• Evolution of Installations

– Onshore installations (smaller and distributed)

– Offshore installations (larger and concentrated)


Why Wind Energy - Aspects of Relevance

1. Simulation of wind speed (WS)

2. Wake effects

3. Wind turbine technology

4. Offshore environment

5. Different wind speed in the installation site

6. Power collection grid in the wind park

7. Correlation of output power for different wind farms

8. Grid connection configuration

9. Hub height variations


Outline




• Conclusions

• Questions


Example – Monte Carlo Simulation

“Estimation of a-posteriori reliability indices by simulating the actual random behaviour of the system for the period intended”

Main steps:

1. Simulation and system definition

2. Components availability in each sample

3. Synthetic Wind speed time series in each sample

4. Wind farm output power in each sample

5. Wind farm index evaluation


Example – Simulation Definition

Sequential Monte Carlo simulation

• Period of 1 year with hourly step (8760 hours)

• Relevant aspects included

– Random wind speed time series

– Wind turbine technology

– Power collection grid in the wind park

– Grid connection configuration

– Offshore environment


Example – System Definition

Component data

Nr. Failure rate MTTR

Wind turbine (Vestas V90) 25 1,5 1/y 490 h/y

Cable (~700 m) 25 0,015 1/y/km 1440 h/y

Connector (~10 km) 3 0,015 1/y/km 1440 h/y

Wind farm layout


Example – Simulation Procedure

2. Component availability

3. Wind speed time series

4. Wind Farm output power

5. Wind Farm Indices


Example – Results

1. IWP =Installed Wind Power

2. IWE = Installed Wind Energy

3. EAWE = Expected Available Wind Energy

4. EGWEWTF = EAWE With WT Failure

5. EGWE = Expected Generated Wind Energy

6. CF = Capacity Factor

7. GR = Generation Ratio

Index Value Unit

1. IWP 75 MW

2. IWE 657000,00 MWh

3. EAWE 281657,91 MWh

4. EGWEWTF 260479,91 MWh

5. EGWE 258344,21 MWh

6. CF 0,3932 -

7. GR 0,9237 -

Simulation time 10722 s

Result accuracy 0,2 %

Nr of Samples 485 -


Example – Comments

• Different aspects of wind farm production

• Relevance of including component failures (indices 3 to 5)

• CF reasonable for offshore installations

• Huge computational time

• Possibility of plotting index distribution functions

Index Value Unit

1. IWP 75 MW

2. IWE 657000,00 MWh

3. EAWE 281657,91 MWh

4. EGWEWTF 260479,91 MWh

5. EGWE 258344,21 MWh

6. CF 0,3932 -

7. GR 0,9237 -

Simulation time 10722 s

Result accuracy 0,2 %

Nr of Samples 485 -


Outline




• Conclusions

• Questions


Conclusions

• Relevance of including wind generation into power system reliability assessment

• Importance of 9 aspects for the problem

• Monte Carlo simulation is a powerful tool, but it needs some optimizations

• Future developments

– Inclusion of all missed aspects

– Improvement of the simulation

– HLI and HLII analysis


Outline




• Conclusions

• Questions

aspects of relevance in offshore wind farm reliability assessment nicola barberis negra...

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