APPLICATION OF COST FUNCTIONS FOR LARGE SCALE INTEGRATION OF WIND POWER USING A MULTI-SCHEME ENSEMBLE PREDICTION TECHNIQUE - Energy Research Developments: Tidal Energy, Energy Efficiency and Solar Energy - page 335

Chapter 12
A PPLICATION OF C OST F UNCTIONS FOR L ARGE
S CALE I NTEGRATION OF W IND P OWER U SING
A M ULTI - SCHEME E NSEMBLE P REDICTION
T ECHNIQUE
Markus Pahlow 1∗ , Corinna Mohrlen 2† and Jess U. Jørgensen 2‡
1 Department of Civil and Environmental Engineering, Institute of Hydrology,
Water Resources Management and Environmental Engineering,
Ruhr-University Bochum, 44780 Bochum, Germany
2 WEPROG, Eschenweg 8, 71155 Altdorf, Germany
Abstract
The use of ensemble techniques for wind power forecasting aids in the integration
of large scale wind energy into the future energy mix and offers various possibilities
for optimisation of reserve allocation and operating costs. In this chapter we will
describe and discuss recent advances in the optimisation of wind power forecasts to
minimise operating costs by using a multi-scheme ensemble prediction technique to
demonstrate our theoretical investigations. In recent years a number of optimisation
schemes to balance wind power with pumped hydro power have been investigated.
Hereby the focus of the optimisation was on compensating the fluctuations of wind
power generation. These studies assumed that the hydro plant was dedicated to the
wind plant, which would be both expensive and energy inefficient in most of today's
and expected future electricity markets, unless the wind generation is correlated and
has a very strong variability. Instead a pooling strategy is introduced that also includes
other sources of energy suitable to balance and remove the peaks of wind energy, such
as biogas or a combined heat and power (CHP) plant. The importance of such pools
of energy is that power plants with storage capacity are included to enable the pool to
diminish speculations on the market against wind power in windy periods, when the
price is below the marginal cost and when the competitiveness of wind power as well
as the incentives to investments in wind power become inefficient and unattractive.
∗ E-mail address: [e-mail]
† E-mail address: [e-mail]
‡ E-mail address: [e-mail]