Renewable energy generation assessment in terms of small-signal stability

The popularity and role of renewable energy in the power grid are increasing nowadays as countries are shifting to cleaner forms of energy. This brings new challenges in maintaining a secure and stable power system, as renewable energy is known to be intermittent in nature and may introduce stability issues to the grid. In this paper, a screening framework of renewable energy generation scenarios is proposed to determine which power system conditions and scenarios will make the system unstable. The scenario screening framework is based on a sensitivity analysis of the system eigenvalues with respect to the renewable energy penetration to the system. The average scheduled renewable energy output, forecasting error standard deviation, average forecasting error, and bus location of the renewable energy source were used to define a renewable energy generation scenario. Depending on the amount and variability of renewable energy, there is a possibility for a critical eigenvalue to cross the imaginary axis. The estimated eigenvalue location resulting from the penetration of variable renewable energy is computed by adding the computed eigenvalue sensitivity to the initial operating point. If any of the estimated system eigenvalues cross the imaginary axis, the power system might be unstable in this scenario, so it requires more detailed simulations and countermeasures. Renewable energy forecasting was done using the long short-term memory model, and the proposed method was simulated using the IEEE 39-bus New England test system. The results of the proposed method were verified by comparing the simulation results to the eigenanalysis solution. The obtained results have shown that the proposed method can determine whether the renewable energy generation scenario is critical in power system operation.