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Here, climatological data of solar radiation and wind speed are used to simulate hourly capacity factors for solar and wind energy for Germany from 1995 to 2015. Using renewable energy production data for 2015 these data are converted into time series of generated electrical power. Events with very low energy production, i.e., shortfall events, have […]
In a collaborative effort to address climate change impacts on Tanzania’s hydropower sector, WEMC, TMA, and TANESCO have developed and implemented a machine learning model for hydropower generation forecasting. This model utilizes meteorological data to simulate historical electricity production, predict future output, and inform resource management decisions. The model’s capabilities were demonstrated through a case […]
In a 2009 study focused on optimal approaches to utility storm response, researchers delved into the practices, procedures, and lessons gleaned from major storm events within the United States. The aim was to dissect and articulate the successes and shortcomings encountered in the preparation, restoration, and winding down stages. The examination encompassed various aspects, such […]
Drawing on real experiences, this online resource provides a blueprint for building dynamic resilience to extreme weather events. 10 learning reviews identify the system failures triggered by extreme weather events, the impacts these failures, and lessons learnt from mitigation and recovery.
Nice Case Studies demonstrating how the use of improved climate forecasts, out to several months ahead, can add practical and economic value to decision-making processes and outcomes in both the energy and water sectors.
Eight case studies have been prepared in the project S2S4E to demonstrate the potential of the forecasts used in the Decision Support Tool (DST). The case studies analyze extreme events that occured in the past and present S2S4E forecasts that could have been available, to see if the forecasts could have added value to decision-making […]
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