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Wind power is unanimously recognized as one of the major drivers of the energy transition. Increasing renewable power generation introduces significant challenges for both the operation and planning of power systems, driven by the intrinsic uncertainty of stochastic renewable resources and by the growing spatial distribution of generation assets. Wind power presents a distinctive set of challenges in this context.

Integrating intermittent distributed generation, distributed storage systems, electric vehicles, and flexible loads will present security, stability, and power quality challenges in future smart grids. The amount of data to be processed to face these issues can overwhelm grid operation tools and conventional IT-based applications, limiting situational awareness and decision support. Decentralized and self-organizing technologies can help with that problem. In a self-organizing system, information processing is based on local interactions of its elementary parts (dynamic agents), enabling the cooperative solution of complex decision-making problems by only requiring local information exchange without needing a fusion center for data collection and processing.

Wide area monitoring, protection and control systems (WAMPACs) have been recognized as the most promising enabling technologies to meet challenges of modern electric power transmission systems, where reliability, economics, environmental and other social objectives must be balanced to optimize the grid assets and satisfy growing electrical demand. To this aim WAMPAC requires precise phasor and frequency information, which are acquired by deploying multiple time synchronized sensors, known as Phasor Measurement Units (PMUs), providing precise synchronized information about voltage and current phasors, frequency and rate-of-change-of-frequency.