Stochastic management of automated grids in a social–economic–technical framework considering switching scheme and renewable sources

Abstract

This study aims to address this issue by improving the social, economic and technical objective functions in an automated distribution system. Optimal switching is regarded as a strategic approach for satisfying these goals. Due to the growing popularity of the renewable energy sources of wind type, several wind turbines are considered in the grid. Such a grid structure requires a powerful and reliable framework which can consider the correlation effects between wind turbines and run optimal switching to reconfigure the grid, simultaneously. Therefore, a novel stochastic framework based on scenario reduction is deployed which can model the uncertainties of the wind turbines, market price and load demands in the operation time horizon. The objective functions to be optimised are the total automated grid costs as the economic function, and the total grid emission and the system average interruption duration index as the social functions. This is a complex non-linear and mixed integer problem which needs a global optimiser to get solved. Therefore, an efficient and accurate heuristic optimisation algorithm-based crow search is proposed to solve the problem. A two-stage modification method is also proposed which improves the crow search algorithm performance using an IEEE test system.