T. Youssef

Adaptive Predictive Energy Management Strategy for Integrating Intermittent Resources in Power Systems

In this paper, we develop a power system adaptive and predictive management strategy for integrating large-scale renewable energy penetration in the power systems. The variability and uncertainty of renewable energy increase the difficulty of the power system management extremely. Also, the problem becomes more challenging if the variable energy has large penetration. The proposed strategy depends on robust optimization under unforeseen contingencies and uncertain changes in intermittent resources output.

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Data-Centric Hierarchical Distributed Model Predictive Control for Smart Grid Energy Management

The smart grid energy management with variable renewable energy resources presents many challenges to the grid operation. An optimized solution to manage the available resources is necessary to achieve reliable operation. This paper presents the hierarchical distributed model predictive control (HDMPC) to solve the energy management problem in the multitime frame and multilayer optimization strategy.
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