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June 30, 2015
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Efficient Analysis of Smart Meter Energy DataSmart grids are joining a growing list of "big data" sources in the forthcoming Internet of Things, and carry with them unique challenges and opportunities related to software. Although the application of big data technique to smart grid data promises tangible economic benefits, for example through reductions in peak power consumption for energy providers and in the monthly usage for energy consumers, the processing overheads associated with some energy analytics computations put these benefits into question given the high costs of high-performance computation. This project focuses on the analysis of data from smart grids, specifically periodic energy consumption readings from smart meters deployed in consumer households, with the goal or reducing the cost of analytics computations through efficient algorithms. |
Smart Grid Load Balancing & Energy Storage by Power-to-Gas via MethanationOne of the main challenges in large scale utilization of renewable solar and wind energy sources is their unreliable nature. Transient fluctuations in solar and wind power supply result in significant grid load variations that can even lead to power blackouts. Smart Grid energy transmission and storage can compensate for these fluctuations allowing accommodation of larger renewable resources in a reliable manner. The goal of this project is to develop a highly efficient methanation system which can be easily and effectively integrated into the Power-to-Gas system while using wind and sun as sources of renewable energy for H2 generation(by electrolysis) and biogas and landfill gas as sources of carbon (CO2 sequestrated from power plants can be utilized as well). |
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