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Modeling and Forecasting Electricity Demand
Modeling and Forecasting Electricity Demand
Knygos.lt klubas Knygos.lt nariams
83,57 €
-30%
Įprastai
119,39 €
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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…
  • Leidėjas:
  • Metai: 2015
  • Puslapiai: 115
  • ISBN-10: 3658086688
  • ISBN-13: 9783658086688
  • Formatas: 14.8 x 21 x 0.8 cm, minkšti viršeliai
  • Kalba: Anglų

Modeling and Forecasting Electricity Demand (el. knyga) (skaityta knyga) | knygos.lt

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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.

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  • Autorius: Kevin Berk
  • Leidėjas:
  • Metai: 2015
  • Puslapiai: 115
  • ISBN-10: 3658086688
  • ISBN-13: 9783658086688
  • Formatas: 14.8 x 21 x 0.8 cm, minkšti viršeliai
  • Kalba: Anglų

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.

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