Applying the Crow Search Algorithm for the Optimal Integration of PV Generation Units in DC Networks

This paper presents an efficient master–slave methodology to solve the problem of integrating photovoltaic (PV) generators into DC grids for a planning period 20 years. The is mathematically formulated as Mixed-Integer Nonlinear Programming (MINLP) with objective minimizing total annual operating cost. main stage, consisting discrete-continuous version Crow search algorithm (DCCSA), in charge determining installation positions PV and their corresponding power ratings. On other hand, at slave level, successive approximation flow method used determine function value. Numerical results on 33- 69-bus test systems demonstrate applicability, efficiency robustness developed approach respect different methodologies previously discussed scientific literature, such vortex algorithm, generalized normal distribution optimizer particle swarm optimization algorithm. tests are performed MATLAB programming environment using proprietary scripts.