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Specifying compute as the grid value is the same as using the default gridding.
Fig. 1 Smart grid value chain.
Power consumption is the last step on smart grid value chain and it involves the users of electricity, both residential and industrial.
The Smart Electric Power Alliance's (SEPA) recent Utilities and Electric Vehicles: Evolving to Unlock Grid Value report found 74% of utilities were in the early stage of EV programs, 23% were in the intermediate stage, and 3% were in late stages; each stage was determined based on level of consumer engagement, as well as availability of incentives and rate programs.
In line with the above, various techniques have been proposed for calculating average grid value to be used for simulation grid (Aavatsmark et al. 2010; Mallison et al. 2014; Wu and Parashkevov 2010).
Power generation is the first step in smart grid value chain, it includes power sources such as nuclear, hydropower and renewable and it relays on wide area monitoring and control technologies to communicate with the next step called power distribution.
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The min and max grid values are manually set.
Analysis may produce unrealistic extrema in the grid values, especially near the edges of the spatial domain.
First, we set all voxel weights to zero, so that new data will overwrite the initial grid values.
Numeric gives both the grid values and the data values as numbers; text gives times as month-year while continuing to give the data as numbers.
Individual grid values were then summed to obtain an estimate of volume loss from the glaciological basin (km3) and multiplied by 0.9 to obtain an estimate of ice mass loss (Gt).
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