Redundant placement of phasor measurement unit using multi objective evolutionary algorithms based on modified spectral clustering

Optimal placement of phasor measurement unit (OPPMU) considering controlled islanding is a high dimensional constrained optimization problem that determines optimum location of PMU. Controlled islanding can be used as an effective emergency action to split a large scale power system into islands for avoiding blackouts. This paper proposes an optimal PMU placement model considering power system controlled islanding. So that the power network remains observable under controlled islanding as well as normal operating condition. A new method based on spectral clustering is proposed to handle multiple constraints in order to guarantee the stability of generated islands. The objective function used in this controlled islanding algorithm is the minimal power flow disruption. Constraints such as generator coherency, load–generation imbalance are considered for spectral clustering. OPPMU is formed for the obtained islands using two conflicting objectives of minimizing the number of PMU and maximizing the measurement redundancy using conventional mixed integer linear programming, real coded genetic algorithm(RGA), non dominated sorting differential evolutionary algorithm, and modified non dominated sorting GA II (MNSGA II). RGA with simulated binary crossover and non dominated sorting differential evolution with improved crowding distance and mutation is implemented. In MNSGA II proposed a variant which reduces the run-time complexity using the technique space–time-trade-off. Simulation results using NE 39 and IEEE 118 bus test systems show that the proposed method is computationally efficient when solving controlled islanding based OPPMU problem.