Substation Related Forecasts of Electrical Energy Storage Systems: Transmission System Operator Requirements

Tamara Schröter, André Richter, Jens Götze, André Naumann, Jenny Gronau and Martin Wolter
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Tamara Schröter: Chair Electric Power Systems and Renewable Energy Sources, Otto Institute of Electric Power Systems, von Guericke University, 39106 Magdeburg, Germany
André Richter: Chair Electric Power Systems and Renewable Energy Sources, Otto Institute of Electric Power Systems, von Guericke University, 39106 Magdeburg, Germany
Jens Götze: Fraunhofer Institute for Factory Operation and Automation IFF, 39106 Magdeburg, Germany
André Naumann: Fraunhofer Institute for Factory Operation and Automation IFF, 39106 Magdeburg, Germany
Jenny Gronau: 50Hertz Transmission GmbH, 15366 Neuenhagen bei Berlin, Germany
Martin Wolter: Chair Electric Power Systems and Renewable Energy Sources, Otto Institute of Electric Power Systems, von Guericke University, 39106 Magdeburg, Germany

Energies, 2020, vol. 13, issue 23, 1-26

Abstract: The growth in volatile renewable energy (RE) generation is accompanied by an increasing network load and an increasing demand for storage units. Household storage systems and micro power plants, in particular, represent an uncertainty factor for distribution networks, as well as transmission networks. Due to missing data exchanges, transmission system operators cannot take into account the impact of household storage systems in their network load and generation forecasts. Thus, neglecting the increasing number of household storage systems leads to increasing forecast inaccuracies. To consider the impact of the storage systems on forecasting, this paper presents a new approach to calculate a substation-specific storage forecast, which includes both substation-specific RE generation and load forecasts. For the storage forecast, storage systems and micro power plants are assigned to substations. Based on their aggregated behavior, the impact on the forecasted RE generation and load is determined. The load and generation are forecasted by combining several optimization approaches to minimize the forecasting errors. The concept is validated using data from the German transmission system operator, 50 Hertz Transmission GmbH. This investigation demonstrates the significance of using a battery storage forecast with an integrated load and generation forecast.

Keywords: storage operation forecast; load forecast; generation forecast; TSO operational planning (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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