Assessment and Enhancement of Uncertain Renewable Energy Hosting Capacity With/out Voltage Control Devices in Distribution Grids

Nowadays, with excessive integration of renewable energy sources (RESs), the distribution systems face several challenges due to exceeding the hosting capacity limit (HCL) of RESs. This article proposes a bi-stage approach to maximize the HCL considering RESs and load uncertainties. The first stage develops a multiobjective framework to adjust the system voltage profiles in a specific manner to avoid exceeding the voltage boundaries with high penetration of RESs. In the second stage, two processes are employed to maximize the HCL as the main objective function. In the first one, the photovoltaic (PV) and wind turbine (WT) plants are optimally allocated, while in the second process, a combination of three voltage control devices is proposed. A correlated multidimension probability uncertainty model is used to emulate the uncertainty of PV, WT, and load demand. Manta Ray foraging optimization (MRFO) algorithm is proposed to solve single-objective and multiobjective frameworks in the bi-stage approach considering the performance limits. The proposed approach is tested and validated on medium- and large-scale distribution systems. The effectiveness of the proposed MRFO is approved compared with two optimization algorithms. The proposed approach achieves up to 77.8% RESs integration from the total load demand for the tested systems.