Identification of critical uncertain factors of distribution networks with high penetration of photovoltaics and electric vehicles

The increasing penetration of photovoltaics and electric vehicles exacerbates uncertainties of distribution networks, resulting in serious challenges to secure operation. To tackle the volatility caused by renewable generators and charging loads, a critical uncertain factors identification method is proposed to guide the allocation of flexible resources in this paper. First, diverse uncertainties in distribution networks are quantified and the low-rank approximation (LRA) approach is proposed to evaluate system voltage risk with the consideration of multivariate uncertainties. Then, global sensitivity analysis (GSA) is put forward to identify the critical uncertain factors under independent or correlated circumstances. The guidance for flexible resource allocation is further formulated based on the rank of global sensitivities. Numerical studies on the modified IEEE 33-node and IEEE 123-node systems indicate that the proposed method can effectively deal with the high-dimensional and non-Gaussian randomness in distribution networks. The system voltage risk can be alleviated through var capacity allocation of inverters in an economic manner. In addition, the proposed method has a light computational burden compared with Monte Carlo simulation and the polynomial chaos expansion method.