Fuzzy model predictive control for frequency regulation of temporary microgrids during load restoration

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Abstract
Temporary microgrids containing a high proportion of distributed renewable generations can offer great benefits during the recovery stage after large‐scale power system blackout, by picking up critical load and speeding up the entire grid recovery process. To solve the frequency security problem of temporary microgrids faced in the load restoration process, this paper proposes an adaptive fuzzy model predictive control (adaptive fuzzy‐MPC) strategy to obtain effective frequency regulation to suit the special characteristics of this process. First, the load restoration plan within a short time frame is regarded as the feedforward information and assists in the establishment of the MPC model. Then, considering the uncertainty of renewable distributed generations, the regulation resources are cooperated by an adaptive fuzzy controller which provides the weights of different regulation resources adopted in MPC. Specifically, the base weights of the energy storage system and renewable distributed generations are obtained from fuzzy rules, and then the weight for each regulation resource is modified by the designed adjustment rules. Simulation results illustrate that the proposed strategy can efficiently improve frequency performance while making various frequency regulation resources with different regulation capacities cooperate properly, which can further accelerate the load restoration progress and enhance system resilience.
Funding Information
  • State Grid Corporation of China (5108‐202219050A‐1‐1‐ZN)

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