Substation Related Forecasts of Electrical Energy Storage Systems: Transmission System Operator Requirements
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 network...
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Format: | Article |
Language: | English |
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MDPI AG
2020-11-01
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Series: | Energies |
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Online Access: | https://www.mdpi.com/1996-1073/13/23/6207 |
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author | Tamara Schröter André Richter Jens Götze André Naumann Jenny Gronau Martin Wolter |
author_facet | Tamara Schröter André Richter Jens Götze André Naumann Jenny Gronau Martin Wolter |
author_sort | Tamara Schröter |
collection | DOAJ |
description | 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. |
first_indexed | 2024-03-10T14:34:00Z |
format | Article |
id | doaj.art-6dfbb831fa594794b455153e0b2b8209 |
institution | Directory Open Access Journal |
issn | 1996-1073 |
language | English |
last_indexed | 2024-03-10T14:34:00Z |
publishDate | 2020-11-01 |
publisher | MDPI AG |
record_format | Article |
series | Energies |
spelling | doaj.art-6dfbb831fa594794b455153e0b2b82092023-11-20T22:19:42ZengMDPI AGEnergies1996-10732020-11-011323620710.3390/en13236207Substation Related Forecasts of Electrical Energy Storage Systems: Transmission System Operator RequirementsTamara Schröter0André Richter1Jens Götze2André Naumann3Jenny Gronau4Martin Wolter5Chair Electric Power Systems and Renewable Energy Sources, Otto Institute of Electric Power Systems, von Guericke University, 39106 Magdeburg, GermanyChair Electric Power Systems and Renewable Energy Sources, Otto Institute of Electric Power Systems, von Guericke University, 39106 Magdeburg, GermanyFraunhofer Institute for Factory Operation and Automation IFF, 39106 Magdeburg, GermanyFraunhofer Institute for Factory Operation and Automation IFF, 39106 Magdeburg, Germany50Hertz Transmission GmbH, 15366 Neuenhagen bei Berlin, GermanyChair Electric Power Systems and Renewable Energy Sources, Otto Institute of Electric Power Systems, von Guericke University, 39106 Magdeburg, GermanyThe 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.https://www.mdpi.com/1996-1073/13/23/6207storage operation forecastload forecastgeneration forecastTSO operational planning |
spellingShingle | Tamara Schröter André Richter Jens Götze André Naumann Jenny Gronau Martin Wolter Substation Related Forecasts of Electrical Energy Storage Systems: Transmission System Operator Requirements Energies storage operation forecast load forecast generation forecast TSO operational planning |
title | Substation Related Forecasts of Electrical Energy Storage Systems: Transmission System Operator Requirements |
title_full | Substation Related Forecasts of Electrical Energy Storage Systems: Transmission System Operator Requirements |
title_fullStr | Substation Related Forecasts of Electrical Energy Storage Systems: Transmission System Operator Requirements |
title_full_unstemmed | Substation Related Forecasts of Electrical Energy Storage Systems: Transmission System Operator Requirements |
title_short | Substation Related Forecasts of Electrical Energy Storage Systems: Transmission System Operator Requirements |
title_sort | substation related forecasts of electrical energy storage systems transmission system operator requirements |
topic | storage operation forecast load forecast generation forecast TSO operational planning |
url | https://www.mdpi.com/1996-1073/13/23/6207 |
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