Multi-objective optimal power flow using quasi-oppositional teaching learning based optimization
The optimal power flow problem is formulated as a multi-objective optimization problem. A teaching learning based optimization (TLBO) algorithm is presented for solving the OPF problem. Modifying the TLBO algorithm by applying opposition based learning (OBL) to enhance its search ability. The proposed approaches are implemented on three standard test systems. The effectiveness of the proposed TLBO and QOTLBO approaches are compared with NSGA-II, MOHS, EP, EPM and SFLA.
multi-objective optimization optimal power flow teaching learning based optimization quasi-oppositional based learning voltage stability index