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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorKramer, Gert Jan
dc.contributor.authorWinden, J.J. van
dc.date.accessioned2018-04-23T17:01:06Z
dc.date.available2018-04-23T17:01:06Z
dc.date.issued2018
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/28964
dc.description.abstractHigh levels of variable renewable energy (VRE) induce supply-demand mismatches due to variability in electricity generation. To accommodate these fluctuations in residual load, power grid flexibility is required, which entails the ability of the power system to absorb or supply electricity when required. Flexibility can be enhanced through electricity storage, interconnection, demand-side management and flexible power plant dispatch. Since the residual load fluctuations depend on different cycling components of supply and demand, flexibility is required on specific cycling timeframes. This study investigates a spectral analysis which maps these supply- and demand fluctuations and the subsequent effect of deploying flexibility measures. Through direct Fourier transformation, generation and demand profiles are decomposed into individual time-varying components, showing on which timeframes dominant cycling components fluctuate. This visualises the residual load for different solar PV/wind-ratios in frequency and phase spectra. Subsequently, the effect of deploying flexibility measures is reflected as changes in these frequency spectra. To generate residual load curves, a power system model is created where three storage technologies and several other flexibility measures can be deployed. The frequency spectra show how solar PV generation is well-described by two diurnal and one seasonal fluctuations, where the latter is in antiphase with the seasonal demand fluctuation. Wind generation is shown to fluctuate more noisily, but is especially dominated by monthly fluctuations. Increased wind penetration thus induces residual loads on monthly timeframes whereas solar PV generation induces large daily and seasonal residual loads. The amplitudes of onshore wind fluctuations were furthermore higher than offshore wind. The generation mix inducing the lowest fluctuation volume was found to be a solar PV penetration of 25-40%. Additionally, inverse Fourier transformation exposed the extent to which supply and demand correspond on individual cycling timeframes. In terms of storage, battery storage reduces fluctuations on <12-hour timeframes in the frequency spectrum. The reducing effect increases with PV penetration due to increased discharge cycles. Compressed air energy storage is shown to be a cheaper option with stronger reduction potential on diurnal and weekly timeframes. Power-to-hydrogen conversion reduces fluctuations on diurnal, monthly and seasonal timeframes, but at high cycling costs. Even after combining storage with other flexibility measures, especially monthly fluctuations pose problematic supply-demand mismatches, inducing instances when VRE generation is close to zero and storage caverns are depleted. Additional findings include overgeneration has the potential to reduce fluctuations on all timeframes, especially when combined with gas-to-power combustion. Interconnection, interruptible loads and curtailment are furthermore shown to be important flexibility measures due to instances of high surplus/deficit. Concludingly, the research successfully investigated the application of spectral analyses in VRE integration research and provides a foundation for a new approach to flexibility strategies.
dc.description.sponsorshipUtrecht University
dc.format.extent11448484
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.titleSpectral analysis of supply-demand matching in power systems with high levels of VRE
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsVariable renewable energy, Fourier transformation, spectral analysis, grid flexibility, electricity storage
dc.subject.courseuuEnergy Science


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