To enhance the reliability of the power grid, further processing of the power demand to achieve load balancing is regarded as a critical step in the context of smart grid. In this paper, dynamic offline and online scheduling algorithms are proposed to minimize the power fluctuations. For offline approach, full information in the power demand is available, possibly by predicting from the Power Utilities. We present an exact approach to allocate the elastic loads based on the inelastic loads information applying geometric water-filling algorithm. We also extend the approach to include the group and node power upper constraints. For online approach, two dynamic algorithms are investigated to achieve load balancing in the power grid without influencing user experience by dynamic water level adjustment. Facilitated by the proposed methodology, the Utilities can significantly reduce the cost of improving the power capacity and be able to offer more stable electricity power to the consumers.
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