Addressing system strength and reliability concerns in renewable energy-based weak grids using synchronous condensers determined by hybrid GRU-classical optimization method

Owing to the higher-integration of renewable energy generators (REGs), conventional coal-based synchronous generators are being decommissioned from generation fleets, resulting in system strength and reliability concerns. Along with the increasing load demand, deficiency of system strength can be a huge risk to system stability and can eventually lead to blackouts by disconnecting REGs from grid systems. In the literature, researchers and power engineers have proposed to deploy synchronous condensers (SynCons) as a mitigation strategy to address the system strength and reliability challenges. SynCons are, however, expensive and require investigation for higher reliability results before installation. To address the concerns, SynCons’ optimal sizes, placement and reliability assessment are investigated in this paper. The proposed solution is achieved by modeling an optimization problem and retaining SynCons-related costs low while maintaining short circuit ratio and minimizing loss of load probability, measurement indexes of system strength and reliability analysis of a grid above a satisfactory level respectively. A hybrid data-driven gated recurrent unit (GRU)-classical optimization framework is developed for data processing and achieving the optimization results. The implemented learning model is capable of achieving higher accuracy 99.691% and lower computation time 0.023 sec when compared with the existing learning models. Additionally, the obtained results, such as transient stability and economic analysis of SynCons-conducted weak-grid present that the proposed solution can significantly perform 21.581% cost minimization and 6.391% reliability enhancement.