A two-stage stochastic programming approach for planning of SVCs in PV microgrids under load and PV uncertainty considering PV inverters reactive power using Honey Badger algorithm

In order to reduce the Static Var Compensators' (SVCs') initial investment costs and their anticipated yearly running costs, this paper offers a two-layer methodology for the allocation and sizing of the SVCs in radial distribution systems. First, the Power Loss (PLI) is used to choose the best candidate buses for allocating SVCs. A two-stage stochastic programming algorithm is then proposed to solve the sizing problem, with the Point Estimate Method (PEM) being used to account for the uncertainties in the PV and load powers. Analysis is also done on the advantages of combining the SVCs and the PV inverter's ability to provide reactive power. The optimi-zation problem is solved using Honey Badger Algorithm (HBA) and compared to Archimedes Optimization Al-gorithm (AOA), Beetle antenna based Grey Wolf Optimization (BGWO), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The IEEE 33 and 69 radial bus systems have been used to validate the suggested methodology. The findings demonstrate that, HBA models delivered the best outcomes in terms of convergence characteristics and computation time. When considering the PV inverter's capability to provide reactive power, estimated yearly operating costs are reduced by 17.44 % and 36.36 % for compensations of 600 kVAR and 1,000 kVAR, respectively.