Hybrid Harris Hawks optimizer for integration of renewable energy sources considering stochastic behavior of energy sources

Renewable energy sources powered distributed generation (RES-DG) is getting more indispensable to encounter the considerable increase in demand for electric energy owing to its techno-economic benefits and eco-friendly nature. An economic solution to this demand can only be obtained with the optimal placement and sizing of RES-DGs. The optimal siting and sizing of RES-DG, such as Photovoltaic (PV) and Wind Turbine (WT) is still a hot topic due to the uncertainties in solar irradiance (SI) and wind speed (WS). The main objective of this research paper is to develop a RES-DG siting and sizing strategy for the discrete, nonlinear siting and sizing pattern of RES-DGs using a novel hybrid Harris' Hawk optimizer (HHHO), considering the stochastic nature of SI and WS. The Weibull and Beta probability density functions (PDFs) are utilized for modeling the stochastic nature of WS and SI, respectively. The optimization of the multiobjective function comprises active power loss reduction, enhancement in voltage profile, and improvement in voltage stability index (VSI). Different scenarios of single and multiple RES-DGs and capacitor banks (CB) are examined to validate the efficiency of the proposed novel HHHO based RES-DGs siting and sizing strategy. The results show a considerable reduction in power loss, enhancement in the system voltage profile, and improvement in VSI. Evaluation of results by comparing withstate-of-art hybrid algorithms shows that the proposed solution using HHHO algorithm is globally optimum.