• Energy Research
• other engineering and technologies close
• US close
• CH close
• English close

Solar tracking systems increase the electricity production by about 30% relative to fixed installations. A robust design of the mechanical system requiring less material than 100kg steel per kW nominal PV module power is essential to further improve the economics of PV tracker plants. The Solar Wings approach reaches this goal by using steel cables as a mounting system for the PV modules and benefits by the long-time experience of project partner BMF using steel cables in transportation systems such as ski-lift, funicular, aerial passenger lines. Tests with the first Solar Wings prototype in Switzerland passed successfully. The first 600 kW PV plant powered by the one axis Solar Wings tracking system will put into operation in December 2008 in Southern Germany. To maximize reliability and reduce maintenance costs only one electrical three-phase asynchronous motor is used to track 100kW PV modules. A two-axis tracking Solar Wings system will be available next year. Further development targets are low optical concentration by the use of planar mirrors mounted on a parallel axis to the PV module axis. PV modules and mirrors track individually and thus an increase of the electricity production of higher than 60% relative to fixed mounted installation is expected. First results of the measured increase of performance by individual tracking of the planar mirrors and the PV modules, performed on a small scale dish model, are reported. 23rd European Photovoltaic Solar Energy Conference and Exhibition, 1-5 September 2008, Valencia, Spain; 2790-2794

{"references": ["U.S. Energy Information Administration. \"How much energy is\nconsumed in residential and commercial buildings in the United States?\"\nAvailable at: http://www.eia.gov/tools/faqs/faq.cfm?id=86&t=1", "S. Darby, \"The effectiveness of feedback on energy consumption.\"\nEnvironmental Change Institute, University of Oxford, 2006. Available\nat: http://www.globalwarmingisreal.com/energyconsump-feedback.pdf.\nVisited: September 2015", "J. S. John, \"Putting energy disaggregation tech to the test,\" November,\n2013. Greentech Media. Available at:\nhttp://www.greentechmedia.com/articles/read/putting-energydisaggregation-tech-to-the-test.\nVisited: September 2015", "A. Zoha, A. Gluhak, M. A. Imran, S. Rajasegarar, \"Non-intrusive load\nmonitoring approaches for disaggregated energy sensing: a survey,\"\nSensors, vol. 12, no. 12, pp. 16838-16866, December 2012.", "G. W. Hart, \"Nonintrusive appliance load monitoring,\" in Proc. of the\nIEEE, vol. 80, pp. 1870-1891, December 1992.", "M. Baranski, J. Voss, \"Non-intrusive appliance load monitoring based\non Optical Sensor,\" IEEE Bologna PowerTech Conference, Bologna,\nItaly, June 2003. Available at:\nhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1304732", "L. Farinaccio, R. Zmeureanu, \"Using a pattern recognition approach to\ndisaggregate the total electricity consumption in a house into the major\nen-uses,\" Elsevier, Energy and Buildings, vol. 30, no. 3, pp. 245-259,\nAugust 1999.", "J. M. Abreu, F. C. Pereira, P. Ferr\u00e3o, \"Using pattern recognition to\nidentify habitual behavior in residential electricity consumption,\"\nElsevier, Energy and Buildings, vol. 49, pp. 479-487, June 2012.", "C. Beckel, L. Sadamori, S. Santini, \"Automatic socio-economic\nclassification of households using electricity consumption data,\" in\nProc. of the 4th international conference on future energy systems, New\nYork, 2013, pp. 75-86.\n[10] H. Zhao, F. Magoul\u00e8s, \"A review on the prediction of building energy\nconsumption,\" Elsevier, Renewable and Sustainable Energy Reviews,\nvol. 16, no. 6, pp. 3586-3592, August 2012.\n[11] G. K. F. Tso, K. K. W. Yau, \"Predicting electricity energy consumption:\nA comparison of regression analysis, decision tree and neural networks,\"\nElsevier, Energy, vol. 32, no. 9, pp. 1761-1768, September 2007.\n[12] F. Farzan, S. A. Vaghefi, K. Mahani, M. A. Jafari, J. Gong, \"Operational\nplanning for multi-building portfolio in an uncertain energy market,\"\nElsevier, Energy and Buildings, vol. 103, pp. 271-283, September 2015."]} Energy disaggregation has been focused by many energy companies since energy efficiency can be achieved when the breakdown of energy consumption is known. Companies have been investing in technologies to come up with software and/or hardware solutions that can provide this type of information to the consumer. On the other hand, not all people can afford to have these technologies. Therefore, in this paper, we present a methodology for breaking down the aggregate consumption and identifying the highdemanding end-uses profiles. These energy profiles will be used to build the forecast model for optimal control purpose. A facility with high cooling load is used as an illustrative case study to demonstrate the results of proposed methodology. We apply a high level energy disaggregation through a pattern recognition approach in order to extract the consumption profile of its rooftop packaged units (RTUs) and present a forecast model for the energy consumption.

Research in the field of precision agriculture is becoming increasingly important due to the growing world population whilst area for cultivation remains constant or declines. In this context, methods of monitoring in?season plant development with high resolution and accuracy are necessary. Studies show that terrestrial laser scanning (TLS) can be applied to capture small objects like crops. In this contribution, the results of multi-temporal field campaigns with the terrestrial laser scanner Riegl LMS-Z420i are shown. Four surveys were carried out in the growing period 2012 on a field experiment where various barley varieties were cultivated in small-scale plots. In order to measure the plant height above ground, the TLS-derived point clouds are interpolated to generate Crop Surface Models with a very high resolution of 1 cm. For all campaigns, a common reference surface, representing the Digital Elevation Model was used to monitor plant height in the investigated period. Manual plant height measurements were carried out to verify the results. The very high coefficients of determination (R² = 0.89) between both measurement methods show the applicability of the approach presented. Furthermore, destructive biomass sampling was performed to investigate the relation to plant height. Biomass is an important parameter for evaluating the actual crop status, but non-destructive methods of directly measuring crop biomass do not exist. Hence, other parameters like reflectance are considered. The focus of this study is on non-destructive measurements of plant height. The high coefficients of determination between plant height and fresh as well as dry biomass (R² = 0.80, R² = 0.77) support the usability of plant height as a predictor. The study presented here demonstrates the applicability of TLS in monitoring plant height development with a very high spatial resolution. Proceedings of the Workshop on UAV-based Remote Sensing Methods for Monitoring Vegetation Kölner geographische Arbeiten, 94 ISSN:0454-1294

In the Meyer-Burger labs, pilot production of its proprietary 6''-Heterojunction (HJT) cells has been conducted on full-scale production tools (Roth & Rau Helia PECVD & Helia PVD). Overall, close to 10.000 cells have been manufactured with efficiencies up to 21,1%. From theses HJT cells, 60-cell modules have been produced. Temperature coefficient measurements of both cells and modules have been conducted by independent institutes, resulting in outstanding -0,20%/K and -0,22%/K, respectively. The modules have been deployed on an outdoor test field in Mid-European climate conditions for over 1 year. The results demonstrate the durability of the HJT modules and comparison with standard crystalline modules show an increase of energy yield of up to 7% on sunny days already in spring time. Under hot climate conditions in southern regions this increase is supposed to be even higher, making HJT modules extremely suitable for southern climates and low LCOE´s. 28th European Photovoltaic Solar Energy Conference and Exhibition; 1887-1889

Utility regulators frequently attempt to use tariff structures to pursue both distributional and efficiency goals. Efficiency necessitates setting prices as close to marginal costs as possible while still allowing the firm to cover its costs. The common distributional goal is to protect low-income customers from high prices. Perhaps nowhere is the conflict between these goals greater than in the use of increasing-block residential utility pricing, in which the marginal price to the customer increases as the customer’s usage rises. Since the 2000-01 California electricity crisis, the state has adopted some of the most steeply increasing-block tariffs in electric utility history, but the distributional and efficiency effects have not been analyzed in detail. Using a novel approach for matching customer bill data with census data on area income distributions, I derive estimates of the income redistribution effected by the increasing-block tariffs used by California regulated electric utilities. I find that the rate structure does redistribute income to lower-income groups, but that the effect is fairly modest, particularly compared to a means-tested program also in use. While the distributional impact of these tariffs do not seem to be large, the efficiency costs may not be great either. Examining the distribution of customer demand quantities, I find preliminary evidence that customers do not respond to the increasing marginal prices they face.