Adaptive Predictive Energy Management Strategy for Integrating RES in Power Systems

What is it about?

This paper presents an adaptive predictive management strategy for integrating large-scale renewable energy sources in power systems. The variability and uncertainty of renewable energy increase the difficulty of the power system management. The problem becomes more challenging if the variable energy sources have large penetration ratio. The proposed strategy depends on robust optimization under unforeseen contingences and uncertain changes in intermittent resources output. The adaptive model predictive control is used to manipulate the set-points of the power system generating units to maximize profit at maximum security. Simulation studies are conducted to validate the effectiveness of the proposed strategy. The results show that the strategy is successfully able to maximize profit not only in normal operation case but also in the case of severe contingencies. In addition, the management strategy is flexible for customized plans of the grid operator and also it is scalable for system extensions. The developed strategy helps the management system to increase the renewable energy sources share at the minimum cost with maximum security.

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Photo by Feri & Tasos on Unsplash

Photo by Feri & Tasos on Unsplash

Why is it important?

This paper proposes a newly developed management system which has features of prediction and adoption while dispatch, manage and control the power system units. The optimization and control problem are solved via model predictive control. The introduced system adapter uses the actual system status to adjust system model, constraints, objective and weights/costs to resolve when the system sustained to any contingency or unforeseen event in the grid.

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