An Adaptive Optimal Scheduling Strategy for Islanded Micro-Energy Grid Considering the Multiple System Operating States

Various disturbances can lead to frequency deviations and multiple operating states of the islanded micro-energy grid (MEG) system. However, the existing research on optimal scheduling of MEG does not perform optimal scheduling based on the frequency deviation division, which is difficult to adapt to the variable operating states of MEG. Therefore, this paper proposes an adaptive optimal scheduling strategy for islanded MEG based on the classification of the frequency deviation. Firstly, the MEG is divided into four operating states according to the frequency deviation: frequency normal, frequency alert, frequency emergency, and frequency collapse. Secondly, a multi-objective optimization model of the MEG is established considering the frequency deviation, operating cost, and user satisfaction. Then a method of adaptively adjusting the weight coefficients of each sub-objective is proposed using adaptive scheduling rules which are defined according to the frequency deviation. By classifying the system state using the frequency, the proposed strategy can avoid load shedding during normal operation and quickly restore stable operation during an emergency state, realizing the stable operation and economic dispatch of the MEG under different frequency deviations. In addition, the stability of the system is analyzed using zero-poles. Finally, the simulation results verify the feasibility of the proposed strategy.