This paper presents a realistic cost-effective model for optimal placement of phasor measurement units (PMUs) for complete observability of a power system considering practical cost implications. The proposed model considers hidden or otherwise unaccounted practical costs involved in PMU installation. Consideration of these hidden but significant and integral part of total PMU installation costs was inspired from practical experience on a real-life project. The proposed model focuses on the minimization of total realistic costs instead of a widely used theoretical concept of a minimal number of PMUs. The proposed model has been applied to IEEE 14-bus, IEEE 24-bus, IEEE 30-bus, New England 39-bus, and large power system of 300 buses and real life Danish grid. A comparison of the presented results with those reported by traditional methods has also been shown to justify the effectiveness of the proposed model with regard to its realistic and practical nature.Index Terms-KCL, KVL, optimal placement of PMUs, phasor measurement units (PMUs), power system observability.

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With increasing penetrations of wind generation, based on power‐electronic converters, power systems are transitioning away from well‐understood synchronous generator‐based systems, with growing implications for their stability. Issues of concern will vary with system size, wind penetration level, geographical distribution and turbine type, network topology, electricity market structure, unit commitment procedures, and other factors. However, variable‐speed wind turbines, both onshore and connected offshore through DC grids, offer many control opportunities to either replace or enhance existing capabilities. Achieving a complete understanding of future stability issues, and ensuring the effectiveness of new measures and policies, is an iterative procedure involving portfolio development and flexibility assessment, generation cost simulations, load flow, and security analysis, in addition to the stability analysis itself, while being supported by field demonstrations and real‐world model validation. WIREs Energy Environ 2017, 6:e216. doi: 10.1002/wene.216 This article is categorized under: Wind Power > Systems and Infrastructure Energy Infrastructure > Systems and Infrastructure