40,95 €
40,95 €
inkl. MwSt.
Sofort per Download lieferbar
payback
20 °P sammeln
40,95 €
40,95 €
inkl. MwSt.
Sofort per Download lieferbar

Alle Infos zum eBook verschenken
payback
20 °P sammeln
Als Download kaufen
40,95 €
inkl. MwSt.
Sofort per Download lieferbar
payback
20 °P sammeln
Jetzt verschenken
40,95 €
inkl. MwSt.
Sofort per Download lieferbar

Alle Infos zum eBook verschenken
payback
20 °P sammeln
  • Format: PDF

The master thesis of Kevin Berk develops a stochastic model for the electricity demand of small and medium-sized companies that is flexible enough so that it can be used for various business sectors.
The model incorporates the grid load as an exogeneous factor and seasonalities on a daily, weekly and yearly basis. It is demonstrated how the model can be used e.g. for estimating the risk of retail contracts. The uncertainty of electricity demand is an important risk factor for customers as well as for utilities and retailers. As a consequence, forecasting electricity load and its risk is now…mehr

Produktbeschreibung
The master thesis of Kevin Berk develops a stochastic model for the electricity demand of small and medium-sized companies that is flexible enough so that it can be used for various business sectors.

The model incorporates the grid load as an exogeneous factor and seasonalities on a daily, weekly and yearly basis. It is demonstrated how the model can be used e.g. for estimating the risk of retail contracts. The uncertainty of electricity demand is an important risk factor for customers as well as for utilities and retailers. As a consequence, forecasting electricity load and its risk is now an integral component of the risk management for all market participants.


Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Autorenporträt
Kevin Berk is a Ph.D. student at the Mathematics Department of the University Siegen, Germany. His major research focus is risk management and time series models with applications in energy markets.