Novel sensitivity models for electromechanical oscillations analysis in active distribution networks considering electrical vehicles optimal charging

The integration of distributed generators (DGs) from renewable sources and electric vehicles (EVs) poses challenges, notably in the optimal management of these resources to exploit all the advantages they can bring to the electrical network. This paper proposes three novel sensitivity models for dynamic analysis of low-frequency electromechanical oscillations in active distribution networks, considering a centralized and decentralized frequency control strategy. Additionally, a novel linear formulation has been devised to leverage the flexibility inherent in DGs in the EVs optimal charging, in which the DGs generation uncertainties are reduced by using a novel forecasting system combining the Monte Carlo method and Markov models. To carry out validation analysis, in-depth and extensive comparisons have been conducted through the definition of several study cases in a modified IEEE 37-bus distribution test system, taking into account the presence of EVs. Moreover, Fourier transforms and Wavelet methods were utilized to conduct response signals spectral and time series analysis, showing that integrating the proposed models into active distribution networks offers valuable insights for transient response studies, since these models provide a range of dynamic analysis options that can be selected based on the runtime speeds and the required level of results accuracy. •A new MILP formulation with distributed generation and electric vehicles.•Three new Sensitivity models for low-frequency electromechanical oscillations analysis.•Two important renewable energy sources are considered in the formulation.•Uncertainty of distributed generation reduced with an enhanced MCM and MkvM system.•Extensive analyses carried out through the definition of several study cases.