WIND ENERGY FORECASTING
BY USING ARTIFICIAL NEURAL NETWORK - GENETIC ALGORITHM
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As wind is an intermittent generation resource andweather changes can cause large and rapid changes inoutput, system operators will need accurate androbust wind energy forecasting systems in the future.Rapid changes of wind generation relative to loadrequire rapid dispatching of generation andtransmission resources to balance generation versusload, regulate voltage and frequency, and maintainsystem performance within the limits established byNational Grid. Wind energy forecasts can help theenergy network operator to anticipate rapid changesof wind energy generation versus load and to make thed...
As wind is an intermittent generation resource and
weather changes can cause large and rapid changes in
output, system operators will need accurate and
robust wind energy forecasting systems in the future.
Rapid changes of wind generation relative to load
require rapid dispatching of generation and
transmission resources to balance generation versus
load, regulate voltage and frequency, and maintain
system performance within the limits established by
National Grid. Wind energy forecasts can help the
energy network operator to anticipate rapid changes
of wind energy generation versus load and to make the
decisions. The study has been done for ANN and also
with the combination of ANN and GA for short term
wind power forecasting of wind power plants. The
performance of these developed forecasting models
have been tested and analyzed with wind power data
available from the operational records of wind power
plants. The results show that the combination of ANN
and GA model does wind power output forecasting very
well except during the gust. This forecasting model
can also be implemented in different time-scales,
which will help wind energy trading in the open
electricity markets.
weather changes can cause large and rapid changes in
output, system operators will need accurate and
robust wind energy forecasting systems in the future.
Rapid changes of wind generation relative to load
require rapid dispatching of generation and
transmission resources to balance generation versus
load, regulate voltage and frequency, and maintain
system performance within the limits established by
National Grid. Wind energy forecasts can help the
energy network operator to anticipate rapid changes
of wind energy generation versus load and to make the
decisions. The study has been done for ANN and also
with the combination of ANN and GA for short term
wind power forecasting of wind power plants. The
performance of these developed forecasting models
have been tested and analyzed with wind power data
available from the operational records of wind power
plants. The results show that the combination of ANN
and GA model does wind power output forecasting very
well except during the gust. This forecasting model
can also be implemented in different time-scales,
which will help wind energy trading in the open
electricity markets.
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