Towards Increasing Hosting Capacity of Modern Power Systems through Generation and Transmission Expansion Planning

The use of renewable and sustainable energy sources (RSESs) has become urgent to counter the growing electricity demand reduce carbon dioxide emissions. However, current studies are still lacking introduce a planning model that measures what extent networks can host RSESs in phase. In this paper, stochastic power system is proposed increase hosting capacity (HC) satisfy future load demands. regard, formulated consider larger number size generation transmission expansion projects installed than investment costs, without violating operating reliability constraints. A forecasting technique, built on an adaptive neural fuzzy system, was employed incorporated with predict annual growth. problem revealed as non-linear large-scale optimization problem, hybrid two meta-heuristic algorithms, namely, weighted mean vectors technique sine cosine algorithm, investigated solve it. benchmark realistic network were used verify strategy. results demonstrated effectiveness enhance HC. Besides this, proved efficiency optimizer for solving problem.