Chennai:
The wind producers in the state have something to cheer about with the
launch of nation’s first wind power forecasting micro pilot project in
Tamil Nadu after the sector suffered huge losses in the last two
years.
Ranked top among the states generating wind energy, the fortunes of
wind energy producers declined two years ago after the Union
government brought in new guidelines and changed the grid frequency
after the northern grid tripped in 2012.
Prof K Kasturirangian, chairman of Indian wind Power Association told
reporters on the sidelines of Wind Power Forecasting Service said that
three billion units of wind energy worth Rs 900 crore were lost due to
change in the grid frequency which was reduced after the tripping of
northern grid that blacked out 22 states.
Tamil Nadu Transmission Corporation Limited was cautious over
scheduling of wind power due to fluctuations as nobody had an idea of
how much wind power was available to be scheduled for state load
dispatch centre as a result three billion units of wind power was
lost, he said.
But now with wind power forecasting, TRANSCO will have the data of
wind power available every 15 minutes through the substations, he
said.
“Now TRANSCO will know the availability of wind power and have a
proper mix by utilising total wind energy resources available,” he
said.
Talking about the project, K Boopathi, additional director and head
Wind Resource Assessment Unit, National Institute of Wind Energy told
reporters that the micro-project would be implemented in four sub
stations in Ayyanaruthu in Kaythar and Udumalpet. “From there it will
be expanded across the state in 134 substations,” he added.
Although, there has been many service providers providing wind power
production forecasting, this is the first such project by Ministry of
New and Renewable Energy.
Varsha Joshi, joint secretary (wind energy), MNRE, said National
Institute of Wind Energy and MNRE in collaboration with Vortex
Factoria de Calculs, Spain is ready to provide its wind power
forecasting services initially in Tamil Nadu. “This will be extended
to entire country,” she added.
Boopathi said the project aims to provide forecasting services to the
wind industry for every 15 minutes forecast upto 10 days ahead. “this
will support the load dispatch centres for scheduling and dispatching
of electricity from wind farms for demand supply management with ease,
Bhoopathi added.
Box:
Why wind power forecasting:
1. The state power distribution company wants wind power forecasting
service in order to manage grid properly and effectively
2. The wind power forecast will provide forecast of wind and wind
power from wind farm or substation.
3. The equipment in the substation will accumulate data every 15
minutes and send it to NIWE through FTP
4. The data will then be transferred to State Load Despatch Centre
which will know how much units of wind energy is available to be
transferred to the grid.
5. This will ensure high level of wind energy evacuation and mitigate
effects on the stability of the grid and security of energy supply
The wind producers in the state have something to cheer about with the
launch of nation’s first wind power forecasting micro pilot project in
Tamil Nadu after the sector suffered huge losses in the last two
years.
Ranked top among the states generating wind energy, the fortunes of
wind energy producers declined two years ago after the Union
government brought in new guidelines and changed the grid frequency
after the northern grid tripped in 2012.
Prof K Kasturirangian, chairman of Indian wind Power Association told
reporters on the sidelines of Wind Power Forecasting Service said that
three billion units of wind energy worth Rs 900 crore were lost due to
change in the grid frequency which was reduced after the tripping of
northern grid that blacked out 22 states.
Tamil Nadu Transmission Corporation Limited was cautious over
scheduling of wind power due to fluctuations as nobody had an idea of
how much wind power was available to be scheduled for state load
dispatch centre as a result three billion units of wind power was
lost, he said.
But now with wind power forecasting, TRANSCO will have the data of
wind power available every 15 minutes through the substations, he
said.
“Now TRANSCO will know the availability of wind power and have a
proper mix by utilising total wind energy resources available,” he
said.
Talking about the project, K Boopathi, additional director and head
Wind Resource Assessment Unit, National Institute of Wind Energy told
reporters that the micro-project would be implemented in four sub
stations in Ayyanaruthu in Kaythar and Udumalpet. “From there it will
be expanded across the state in 134 substations,” he added.
Although, there has been many service providers providing wind power
production forecasting, this is the first such project by Ministry of
New and Renewable Energy.
Varsha Joshi, joint secretary (wind energy), MNRE, said National
Institute of Wind Energy and MNRE in collaboration with Vortex
Factoria de Calculs, Spain is ready to provide its wind power
forecasting services initially in Tamil Nadu. “This will be extended
to entire country,” she added.
Boopathi said the project aims to provide forecasting services to the
wind industry for every 15 minutes forecast upto 10 days ahead. “this
will support the load dispatch centres for scheduling and dispatching
of electricity from wind farms for demand supply management with ease,
Bhoopathi added.
Box:
Why wind power forecasting:
1. The state power distribution company wants wind power forecasting
service in order to manage grid properly and effectively
2. The wind power forecast will provide forecast of wind and wind
power from wind farm or substation.
3. The equipment in the substation will accumulate data every 15
minutes and send it to NIWE through FTP
4. The data will then be transferred to State Load Despatch Centre
which will know how much units of wind energy is available to be
transferred to the grid.
5. This will ensure high level of wind energy evacuation and mitigate
effects on the stability of the grid and security of energy supply
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