Multi-Objective Model for Allocation of Gas Turbines with the Aim of Black-Start Capability Enhancement in Smart Grids

Installation of new power generating units as backup black-start (BBS) sources is a vital issue to improve the acceleration of power network restoration, especially when a serious problem is occurred in main BS units (BSUs) and leads to fail in operation. Accordingly, this work address a new design for the optimal locating of the Gas-based Turbine (GT) as BBS to improve the smart grid performance during both restoration and normal conditions. To this end, there will be incompatible fitness functions to be minimized. Therefore, a multi-objective problem (MOP) including a mixed integer Non-linear programming (MINLP), is formulated. The Pareto answers of the proposed MOP as the best solutions are modified and extracted by utilizing a meta-heuristic method, called crow search algorithm (CSA). A typical test system is employed for evaluation of the given plan. The extracted outcomes reveal that the network can desirably operate from this design not only to favorably enhance the capability of BSUs, but also to improve the power system performance in normal conditions. It also provides the better start-up program of non-black-start (NBS) power sources with the optimal paths during the restoration process.