Phasor measurement units (PMUs) are essential tools for monitoring, protection and control of power systems. The optimal PMU placement (OPP) problem refers to the determination of the minimal number of PMUs and their corresponding locations in order to achieve full network observability. This paper introduces a recursive Tabu search (RTS) method to solve the OPP problem. More specifically, the traditional Tabu search (TS) metaheuristic algorithm is executed multiple times, while in the initialisation of each TS the best solution found from all previous executions is used. The proposed RTS is found to be the best among three alternative TS initialisation schemes, in regard to the impact on the success rate of the algorithm. A numerical method is proposed for checking network observability, unlike most existing metaheuristic OPP methods, which are based on topological observability methods. The proposed RTS method is tested on the IEEE 14, 30, 57 and 118‐bus test systems, on the New England 39‐bus test system and on the 2383‐bus power system. The obtained results are compared with other reported PMU placement methods. The simulation results show that the proposed RTS method finds the minimum number of PMUs, unlike earlier methods which may find either the same or even higher number of PMUs.

This study presents a new approach for optimal placement of synchronised phasor measurement units (PMUs) to ensure complete power system observability in the presence of non‐synchronous conventional measurements and zero injections. Currently, financial or technical restrictions prohibit the deployment of PMUs on every bus, which in turn motivates their strategic placement across the power system. PMU allocation is optimised here based on measurement observability criteria for achieving solvability of the power system state estimation. Most of the previous work has proposed topological observability based methods for optimal PMU placement (OPP), which may not always ensure numerical observability required for successful execution of state estimation. The proposed OPP method finds out the minimum number and the optimal locations of PMUs required to make the power system numerically observable. The problem is formulated as a binary semi‐definite programming (BSDP) model, with binary decision variables, minimising a linear objective function subject to linear matrix inequality observability constraints. The BSDP problem is solved using an outer approximation scheme based on binary integer linear programming. The developed method is conducted on IEEE standard test systems. A large‐scale system with 3120 buses is also analysed to exhibit the applicability of proposed model to practical power system cases.

This paper presents an efficient and comprehensive method to find out the minimum number and corresponding locations of phasor measurement units (PMUs) guaranteeing full numerical observability of a power system as well as maximizing the measurement redundancy in conjunction with pre-existing conventional measurements. Furthermore, the effect of the number of available channels of PMUs on their optimal placement can be taken into account. The proposed optimal PMU placement (OPP) formulation is extended to consider the case of two types of contingencies, single PMU loss and single branch outage. The objective in the OPP method is the numerical observability, unlike the majority of earlier works which are based on topological observability and do not always ensure numerical observability required for successful execution of state estimation. The problem is formulated as a binary semidefinite programming model with binary decision variables, minimizing a linear objective function subject to linear matrix inequality observability constraints. The binary semidefinite programming problem is solved using an outer approximation scheme based on binary integer linear programming. The effectiveness of the proposed method is verified on different IEEE test systems.

Transition to smart distribution grids is highly dependent upon their reliable real-time monitoring. Optimally allocated measurement devices are the backbone of advanced metering systems for concrete observability and accurate state estimation (SE). This paper proposes a new approach for optimized meter placement in distribution grids by minimizing errors in estimated state vector. The placement problem is formulated on the principles of Fisher information formalism and exploits the D-optimality criterion in the context of convex optimization theory. A Boolean-convex model is developed for minimizing an objective function expressing a measure of the SE quality, subject to linear equality constraints. The proposed algorithm is characterized by flexibility and low complexity. Thorough simulations, using a 136-bus distribution network, are carried out to verify the performance of the proposed approach.