A Novel Optimal Placement of Multi-Type Sensors for Smart Grids Observability Using an Enhanced Graph Theory Search Algorithm

This paper presents a novel approach for optimal multi-type sensor placement using an enhanced graph theory search algorithm, aimed at minimizing both capital and operational costs. The proposed approach combines Phasor Measurement Units (PMUs) and Active and Reactive Power Meters (PQMs) to achieve full smart grid observability. Unlike traditional methods, which assume a fixed cost for PMUs regardless of the number of installed current channels, this approach introduces a binary decision variable for each PMU current channel. This variable is integrated into a dynamic cost model that captures both capital and operational expenses, enabling optimized allocation of PMU current channels. Additionally, the enhanced graph theory search algorithm leverages Ohm's and Kirchhoff's Current Laws to identify indirect observability between adjacent buses, expanding the solution space and optimality. Designed for flexibility and adaptability, the proposed method allows easy customization based on user preferences, enabling optimal PMU placement, incorporation of direct and indirect measurements, management of current channel limitations, and incorporation of PQMs. Tested on both transmission and distribution networks, the proposed method demonstrates superior performance in reducing monitoring costs and enhancing adaptability to specific user needs.