Filters

2011 - 20144

More filters

20204
Reset filters

Settings

End date: 2014 × Start date: 2010 × DDC: 620 × WGL Institute: PIK ×

Search Results

Now showing 1 - 4 of 4
  • Thumbnail Image
    Item
    Bio-IGCC with CCS as a long-term mitigation option in a coupled energy-system and land-use model
    (Amsterdam [u.a.] : Elsevier, 2011) Klein, D.; Bauer, N.; Bodirsky, B.; Dietrich, J.P.; Popp, A.
    This study analyses the impact of techno-economic performance of the BIGCC process and the effect of different biomass feedstocks on the technology's long term deployment in climate change mitigation scenarios. As the BIGCC technology demands high amounts of biomass raw material it also affects the land-use sector and is dependent on conditions and constraints on the land-use side. To represent the interaction of biomass demand and supply side the global energy-economy-climate model ReMIND is linked to the global land-use model MAgPIE. The link integrates biomass demand and price as well as emission prices and land-use emissions. Results indicate that BIGCC with CCS could serve as an important mitigation option and that it could even be the main bioenergy conversion technology sharing 33% of overall mitigation in 2100. The contribution of BIGCC technology to long-term climate change mitigation is much higher if grass is used as fuel instead of wood, provided that the grass-based process is highly efficient. The capture rate has to significantly exceed 60 % otherwise the technology is not applied. The overall primary energy consumption of biomass reacts much more sensitive to price changes of the biomass than to technoeconomic performance of the BIGCC process. As biomass is mainly used with CCS technologies high amounts of carbon are captured ranging from 130 GtC to 240 GtC (cumulated from 2005-2100) in different scenarios.
  • Thumbnail Image
    Item
    Tackling long-term climate change together: The case of flexible CCS and fluctuating renewable energy
    (Amsterdam [u.a.] : Elsevier, 2011) Ludig, S.; Haller, M.; Bauer, N.
    The present study aims at shedding light into the interaction of fluctuating renewables and the operational flexibility of post-combustion capture plants in the framework of a long-term model. We developed a model of the electricity sector taking into account both long-term investment time scales to represent plant fleet development under economic and climate constraints as well as short time scales to consider fluctuations of demand and renewable energy sources. The LIMES model allows us to determine the respective roles of renewables and CCS in climate change mitigation efforts within the electricity sector. Furthermore, we assess the influence of natural gas prices on fuel choice and investigate the shares of competing CCS approaches in the technology mix. We find that the optimal technology mix includes large shares of renewables and simultaneously different competing CCS technologies, depending on emission constraints and fuel prices.
  • Thumbnail Image
    Item
    Improving power grid transient stability by plug-in electric vehicles
    (Bristol : Institute of Physics Publishing, 2014) Gajduk, A.; Todorovski, M.; Kurths, J.; Kocarev, L.
    Plug-in electric vehicles (PEVs) can serve in discharge mode as distributed energy and power resources operating as vehicle-to-grid (V2G) devices and in charge mode as loads or grid-to-vehicle devices. It has been documented that PEVs serving as V2G systems can offer possible backup for renewable power sources, can provide reactive power support, active power regulation, load balancing, peak load shaving, can reduce utility operating costs and can generate revenue. Here we show that PEVs can even improve power grid transient stability, that is, stability when the power grid is subjected to large disturbances, including bus faults, generator and branch tripping, and sudden large load changes. A control strategy that regulates the power output of a fleet of PEVs based on the speed of generator turbines is proposed and tested on the New England 10-unit 39-bus power system. By regulating the power output of the PEVs we show that (1) speed and voltage fluctuations resulting from large disturbances can be significantly reduced up to five times, and (2) the critical clearing time can be extended by 20-40%. Overall, the PEVs control strategy makes the power grid more robust.
  • Thumbnail Image
    Item
    A semantic sensor web for environmental decision support applications
    (Basel : MDPI AG, 2011) Gray, A.J.G.; Sadler, J.; Kit, O.; Kyzirakos, K.; Karpathiotakis, M.; Calbimonte, J.-P.; Page, K.; Garćia-Castro, R.; Frazer, A.; Galpin, I.; Fernandes, A.A.A.; Paton, N.W.; Corcho, O.; Koubarakis, M.; de Roure, D.; Martinez, K.; Gómez-Pérez, A.
    Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g., flood emergency response. For these applications, the sensor readings need to be put in context by integrating them with other sources of data about the surrounding environment. Traditional systems for predicting and detecting floods rely on methods that need significant human resources. In this paper we describe a semantic sensor web architecture for integrating multiple heterogeneous datasets, including live and historic sensor data, databases, and map layers. The architecture provides mechanisms for discovering datasets, defining integrated views over them, continuously receiving data in real-time, and visualising on screen and interacting with the data. Our approach makes extensive use of web service standards for querying and accessing data, and semantic technologies to discover and integrate datasets. We demonstrate the use of our semantic sensor web architecture in the context of a flood response planning web application that uses data from sensor networks monitoring the sea-state around the coast of England.