Comparison of lossless compression schemes for high rate electrical grid time series for smart grid monitoring and analysis

The smart power grid of the future will utilize waveform level monitoring with sampling rates in the kilohertz range for detailed grid status assessment. To this end, we address the challenge of handling large raw data amount with its quasi-periodical characteristic via lossless compression. We compare different freely available algorithms and implementations with regard to compression ratio, computation time and working principle to find the most suitable compression strategy for this type of data. Algorithms from the audio domain (ALAC, ALS, APE, FLAC & TrueAudio) and general archiving schemes (LZMA, Delfate, PPMd, BZip2 & Gzip) are tested against each other. We assemble a dataset from openly available sources (UK-DALE, MIT-REDD, EDR) and establish dataset independent comparison criteria. This combination is a first detailed open benchmark to support the development of tailored lossless compression schemes and a decision support for researchers facing data intensive smart grid measurement

Erfassung von Bodenveränderungen anhand des Monitoringnetzwerks Boden-Dauerbeobachtung Schleswig-Holstein (BDF-SH)

The first evaluation of the regional long-term soil monitoring network Boden-Dauerbeobachtung Schleswig-Holstein (BDF-SH SMN) aimed to evaluating (a) the quality of the SMN and (b) three case studies. The SMN includes chemical, physical and biological soil measurements at 37 sites every three to six years, detailed farm management data and an intensive monitoring using annual soil measurements and weekly leachate data. The assessments of the quality of the BDF-SH SMN compared to national and international standards and literature revealed that the SMN largely fulfils the requirements of a soil and soil organic carbon (SOC) monitoring network. Apart from some limitations in the first years, the SMN has been assessed as highly suitable for detecting changes in soil. The first case study was implemented at two sites which had been converted from grassland/pasture into cropland. The study determined the impact of land use change on SOC, soil water, microbial biomass, earthworms, micro-annelids and other indicators. SOC loss was about 20% of the topsoil carbon stock. Soil water and pore properties changed, and soil fauna and microbial indicators decreased. The second case study aimed to determine the cause of measured soil and SOC losses in Ap horizons in maize monoculture of Northern Germany. The main objective was to determine whether these losses can be explained by wind erosion shown on the use of a process-based model. In the long-term context of 10 years wind erosion was not measured directly. A suitable estimation approach was linking high-quality soil/farming monitoring and wind speed data with modeling results at two sites. The model SWEEP, validated for German sandy soils, was used and modified for the purpose of this study. At both sites there was a good agreement between measurements and modeling results. The crosscheck was done using the resulting enrichment ratios (ERs) which were comparable to the literature. The results suggested that wind erosion caused significant long-term soil and SOC losses. The approach used results of prior studies and is applicable to similar well-studied sites without other noteworthy SOC losses. The third case study at four sites investigated whether, and under which circumstances, annual soil carbon and nutrient measurements are more beneficial within a SMN than common five- to ten-year measurements using an approach of modeling (DNDC) and nutrient balancing. The comparison showed that both modeled and calculated values could reproduce measured trends only to a limited extent and could not depict short-term variations in soil. The measured short-term variations in soil which were due to field heterogeneities caused by farm management. The conclusion was that here only annual measurements can depict the soil’s variability and contribute to the identification of the true long-term trend. The main conclusion was that (a) the quality of the BDF-SH SMN is in accordance with national and international standards in terms of detecting changes in soil and establishing time series and (b) how the broad range of data can be used to detect changes in soil resulting from degradation and how process-based modeling can be of use for this purpose. Additionally, some limitations of the SMN were shown. With the results of the thesis, the value of the BDF-SH SMN is more accessible to international scientific studies and networks and can be used easier as its quality level and its characteristics were described in a research context