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  • 2015-2019  (2)
  • 2005-2009  (3)
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  • 1
    Publication Date: 2020-08-05
    Language: English
    Type: article , doc-type:article
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Publication Date: 2020-08-05
    Language: English
    Type: article , doc-type:article
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    Publication Date: 2020-08-05
    Description: Energy storages can be of great value when added to power grids. They introduce the possibility to store and release energy whenever this is favorable. This is particularly relevant, for example, if power supply is volatile (as is the case with renewable energy) and the network is small (so that there are few other nodes that might balance fluctuations in consumption or production). We present models and methods from mathematical optimization for computing an optimized storage schedule for this purpose. We look at alternative optimization objectives, such as smallest possible peak load, low energy costs, or the close approximation of a prescribed load curve. The optimization needs to respect general operational and economic constraints as well as limitations in the use of storage, which are imposed by the chosen storage technology. We therefore introduce alternative approaches for modeling the non-linear properties of energy storages and study their impact on the efficiency of the optimization process. Finally, we present a computational study with batteries as storage devices. We use this to highlight the trade-off between solution quality and computational tractability. A version of the model for the purpose of leveling peaks and instabilities has been implemented into a control system for an office-building smart grid scenario.
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/pdf
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  • 4
    Publication Date: 2014-02-26
    Description: The performance evaluation of W-CDMA networks is intricate as cells are strongly coupled through interference. Pole equations have been developed as a simple tool to analyze cell capacity. Numerous scientific contributions have been made on their basis. In the established forms, the pole equations rely on strong assumptions such as homogeneous traffic, uniform users, and constant downlink orthogonality factor. These assumptions are not met in realistic scenarios. Hence, the pole equations are typically used during initial network dimensioning only. Actual network (fine-) planning requires a more faithful analysis of each individual cell's capacity. Complex analytical analysis or Monte-Carlo simulations are used for this purposes. In this paper, we generalize the pole equations to include inhomogeneous data. We show how the equations can be parametrized in a cell-specific way provided the transmit powers are known. This allows to carry over prior results to realistic settings. This is illustrated with an example: Based on the pole equation, we investigate the accuracy of average snapshot'' approximations for downlink transmit powers used in state-of-the-art network optimization schemes. We confirm that the analytical insights apply to practice-relevant settings on the basis of results from detailed Monte-Carlo simulation on realistic datasets.
    Keywords: ddc:000
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/pdf
    Format: application/postscript
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  • 5
    Publication Date: 2023-11-03
    Description: Energy storages can be of great value when added to power grids. They introduce the possibility to store and release energy whenever this is favorable. This is particularly relevant, for example, if power supply is volatile (as is the case with renewable energy) and the network is small (so that there are few other nodes that might balance fluctuations in consumption or production). We present models and methods from mathematical optimization for computing an optimized storage schedule for this purpose. We look at alternative optimization objectives, such as smallest possible peak load, low energy costs, or the close approximation of a prescribed load curve. The optimization needs to respect general operational and economic constraints as well as limitations in the use of storage, which are imposed by the chosen storage technology. We therefore introduce alternative approaches for modeling the non-linear properties of energy storages and study their impact on the efficiency of the optimization process. Finally, we present a computational study with batteries as storage devices. We use this to highlight the trade-off between solution quality and computational tractability. A version of the model for the purpose of leveling peaks and instabilities has been implemented into a control system for an office-building smart grid scenario.
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
    Library Location Call Number Volume/Issue/Year Availability
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