The idea of this workshop series is to bring together utility and TSO personnel using wind power forecasts daily, and to share some tips and tricks for making the best use of them. This is flanked with the latest news from research and notes from operational forecasters. For previous workshops, see here: the first, second and third workshop.
This workshop is again co-organised with the 9th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Power Plants on 18-19 October 2010. From 13-15 October, the regular UWIG Fall Technical Meeting was held as well.
Gregor Giebel, Risø DTU:
The new State-of-the-Art report and the European
Experience in SafeWind and other projects
In 2003, I authored a
35
page report on the State-of-the-Art in Short-term Prediction of Wind Power
for the Anemos project.
In the last two years, I updated the report to contain 70 pages and about 300
references (to be published just after this event). A general overview is given,
plus the differences between the old version and the new version is worked out.
Some emphasis is given to the current two large European development projects
which sponsored this exercise, the SafeWind
project related to better extreme event forecasts, and the
Anemos.plus project giving better
decision tools based on forecasting to end users.
Wei Yu, Environment Canada:
Wind Energy Forecasting R&D
and Demonstration Project in
Environment Canada (EC) and Hydro-Quebec (HQ) established a joint RDD (Research
and Development, and Demonstration) project on wind energy forecasting in 2006.
The objective of the project is to provide the industry a state-of-the-art
forecasting tool for better daily management of wind power and grid integration.
This presentation gives an overview on this RDD project The Canadian Limited
Area model, GEM-LAM 2.5km, was used for prediction of meteorological variables,
such as wind speed, wind direction, temperature, etc. The model was calibrated
with 24 historical events in 2005 over Gaspe regions of Quebec Province. This
experimental forecasting system has undergone tests in real-time for wind plants
in Quebec, Canada since May 2007. The meteorologists of EC and HQ evaluate the
daily forecasts using real-time observations from both EC meteorological
stations and masts installed in the wind plants. The hourly forecasts are
archived over the last 3 years and provide a valuable database for analysis of
the model’s performance and of other meteorological phenomena. The forecasting
system and validation results will be presented. Research needs for further
improvement of this forecasting system will also be discussed.
Chris Otton, Transpower, NZ:
What do we need from Wind Generation
Forecasting?
A number of the forecasting systems available approach the
generation forecasting challenge from the perspective of a centralised
forecaster. Transpower, as New Zealand's system operator, finds itself in the
position of requiring a forecast for it's security studies whilst maintaining a
separation of the market forecasting for generation scheduling that is required
of Wind Farm operators. This talk discusses Transpowers current requirements for
a wind generation forecast with a view to maintaining security of supply.
Coffee Break
Bill Henson, ISO New England, US:
The New England Wind Integration Study -
or how to learn from the early adopters of forecasting
Many recent studies as well as power system operators'
experiences have demonstrated the value of windpower forecasting. Windpower and
windpower forecasting are fields where tremendous technological progress is
taking place with advances being made in such areas as integrated remote
sensing, windplant grid support capability, ramp forecasting, etc. Is there an
optimal way forward for the power system integration of weather driven
generation (e.g. wind, solar) and the forecasting that facilitates these
resources? Is it possible for the systems being developed and implemented to
"leave room" for the incorporation of new capabilities-both in the forecasting
itself and in the data acquisition used to drive the forecasts? What lessons
can be learned from the pioneering integration experiences and early adopters of
windpower forecasts? ISO New England is finalizing the results of the New
England Wind Integration Study and has been considering these questions as the
region moves forward to implement the recommendations developed during the
study.
László Varga, E.On Hungary:
Probabilistic forecasts for balance circles
included wind generation
In market driven electricity trading the balance circle is
a group of producers, marketers, and consumers where a balancing mechanism is
used to match supply and demand in all time periods (e.g. every quarter hour).
The difference between the actual consumption and supply is balanced by external
sources or the transmission system operator, which results in the purchase costs
and imbalance charges. In this presentation an illustrative model of a balance
circle is presented to plan the cost of balancing energy. The circle includes a
wind turbine and an electricity consumer. The air temperature and the wind speed
influence the electric loads and the wind power output, consequently, the
accuracy of meteorological forecasts effects the planned electricity purchase.
Mathematical models are developed for the wind generator and the consumer loads.
The application of these models allows us to predict the balancing energy
requirements using deterministic (best guess) and probabilistic (ensemble)
weather forecasts. Since the imbalance price is much more expensive than the
spot market price a good schedule of energy purchase can reduce the balancing
charges. Based on the ensemble and ensemble mean weather forecasts for the wind
speed and air temperature we formed two schedules for the spot energy purchases.
Employing the probabilistic (ensemble) weather prediction decreasing in
operational costs could be achieved.
1230-1330: Lunch
Craig Collier, GL GarradHassan US:
Extreme Volatility of
the Wind: Forecaster Challenges and
Perspectives from Forecast Users
This presentation focuses on the causes
of large fluctuations in wind for western U.S. sites in complex terrain.
The challenges faced by forecasters for capturing “ramps” both deterministically
and probabilistically are described, and perspectives from forecast users are
presented. Cost and profitability impacts are defined, and metrics for
measuring forecast model fidelity for ramp detection and simulation are
provided.
Amanda Fong, WindLogics, US:
WindLogics Operational Wind Power Forecasting:
Need, Methodology, and Challenges
The downturn of the United States economy has emphasized
the need for an efficient, timely plan for incorporating renewable energy into
the grid system. Feeling the financial pinch from power consumers, the
independent system operators need to accurately balance generation and load on
the power grid in order to mitigate overall cost. To do so, the system
operators and utilities work together to schedule and coordinate power
generation, transmission and load demand. The utilities need an accurate wind
power forecast to provide the system operator with the best future wind
generation prediction. WindLogics intelligently combines public weather data
with wind plant information to create wind speed and power forecasts. In order
to provide the best forecast possible for our customers, a mathematical
computational learning system (CLS) is used to find trends comparing past power
forecasts and actual generation. Then going forward, the forecast uses scaled
data learned from the numerical relationships identified by the CLS, thus
improving overall forecast accuracy. Challenges with wind power forecasting
include impediments with forecasting small scale weather features, as well as
quality and availability of meteorological and operational data.
Ulrich Focken, energy&meteo systems, DE:
Experiences with Extreme Event
Warning and Ramp Forecasting for US Wind Farms
A reliable ramp forecast and warnings that indicate extreme
events, like shut-downs due to high wind speeds or icing are of high value for a
system operator. We present recent advances and practical experiences with ramp
event forecasting and warnings for wind farms in the United States (in
particular, the BPA ramp event project in the Pacific Northwest) and from
south-eastern Australia.
Coffee Break
Audun Botterud, Argonne National Laboratory, US:
Advances in probabilistic
forecasting with application to wind power trading
A. Botterud, J. Wang (Argonne National Laboratory), R. J.
Bessa, H.Keko, J. Sumaili, V. Miranda (INESC Porto)
The first part of the talk will give a brief overview of different approaches to
probabilistic wind power forecasting, with focus on two new kernel density
forecast methods. We will compare initial results from the two methods to
traditional approaches based on quantile regression. The second part will
present an application of probabilistic forecasts, i.e. a model for optimal
trading of wind power in electricity markets under uncertainty in wind power and
prices. We will show examples from an illustrative case study of a hypothetical
wind farm in Illinois.
Jian Ma, Yuri Makarov, Pacific Northwest National Laboratory, US:
A New Wind Forecast Error Model and Integrating Wind Generation Forecast
Uncertainty into Dispatch and Unit Commitment
This talk covers two projects regarding wind forecast
error simulation and integrating wind generation forecast uncertainty into
dispatch and unit commitment. 1) A new method using multiple cross-correlated
random processes to simulate wind forecast errors is developed. The method is
based on a transition probability matrix computed from an empirical error
distribution function. The derivation of the method and some experimental
results obtained by generating new forecast errors together with their
statistics are presented. 2) An approach to evaluate the uncertainties of the
ramping capacity and requirements caused by intermittent generation is
developed. A probabilistic algorithm based on histogram analysis is used. A
framework and a demonstration tool for integrating the proposed method with an
EMS system are developed.
Joel Bedard, École de technologie supérieure, CA:
Geophysic Model Output Statistics
for Short-Term Numerical Wind Predictions over Complex Sites
Joel Bedard, Wei Yu, Yves Gagnon, Christian Masson: A
Geophysic Model Output Statistic (GMOS) module is developed and applied for
optimal use of the NWP for a complex, coastal site in Atlantic Canada. GMOS
differs from other MOS that are widely used by meteorological centers in the
following aspects: 1) it takes into account the surrounding geophysical
parameters such as surface roughness, terrain height, etc., along with the wind
direction; 2) the proposed GMOS can be directly applied for model output
correction without any training, although a training of the GMOS will further
improve the results. The GMOS was applied to improve the Environment Canada
GEM-LAM 2.5km forecasts at North Cape (Prince Edward Island, Canada). It was
found that the GMOS improves the predictions RMSE by 25-30% for all time
horizons and almost all meteorological conditions. Also, the topographic
signature of the forecast error due to insufficient grid refinement is
eliminated and the NWP combined with the GMOS now outperforms the persistence
model from a 2h horizon, instead of 4h without the GMOS. Finally, the GMOS
developed for North Cape was applied and validated at another site located in
Bouctouche (New Brunswick, Canada). Similar improvements on the GEM-LAM 2.5km
forecasts were observed, thus showing the general applicability of the GMOS.
1700 (actually, was 1800): Close of workshop
Date and Venue: LOEWS Hotel Le Concord, Québec City, Canada, Room Jean Paul Lemieux. 16 October 2010, 09:00 to 17:00.
Registration: Please go here (you will need to set up an account, it's quick and afterwards you can change your data yourself, if need arises). There is a workshop fee of 199 EUR.