Markov Chain based Very Short Term Load Forecasting realizing Conditional Expectation

Conference: International ETG Congress 2017 - International ETG Congress 2017
11/28/2017 - 11/29/2017 at Bonn, Deutschland

Proceedings: ETG-Fb. 155: International ETG Congress 2017

Pages: 6Language: englishTyp: PDF

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Authors:
Staats, Joachim; Bruce-Boye, Cecil (Center of Excellence for the Intelligent Use of Energy, Lübeck University of Ap-plied Sciences, Lübeck, Germany)
Weirich, Theo (Stadtwerke Norderstedt, Norderstedt, Germany)
Watts, David (European XFEL GmbH, Schenefeld, Germany)

Abstract:
The short-cycle time resolved energy consumption data obtained from smart metering devices allow the energy consumption profile of households to be determined and forecasted using methods of predictive analytics. A Markov chain based method realizing conditional expectation was formulated using the conditional transition probability between consecutive states. The direct formulation as the conditional expectation is a new form of evaluating a Markov chain based model for an approach to forecasting. It was found to give comparable results to those from autoregressive methods. In addition, a key advantage of the Markov chain based method of conditional expectation is its simplicity, computational speed and stability. It comprises the forecast of the conditional and the unconditional probability distribution.