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. Adaptive model predictive control is used to manipulate the power system energy unit's set-points to maximize profit at maximum security. Simulation studies are conducted to validate the effectiveness of the introduced strategy. The results show that the proposed strategy is successfully able to maximize profit not only in normal operation case but also in the case of severe contingencies. In addition to, the management strategy is flexible for customized plans of the grid operator and it is scalable for system extensions. The developed strategy helps the management system to increase the free renewable energy sources share at the minimum cost with maximum security.

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