Abstract

Due to the highly complex and dynamic electrical characteristics of the 3-phase unbalanced power delivery networks (PDNs), it is challenging for utilities to observe the network entirely. This impediment necessitates the PDNs to become intelligent nowadays in the presence of various smart devices. Micro-phasor measurement units (µPMUs) are expected to play a crucial role in observing the smart power distribution system due to their micro-seconds resolution and millidegree precision accuracy. The placement of µPMUs in PDNs is also very challenging due to their associated costs. So, allocating a minimal number of µPMUs in PDN with fulfilling the topological observability can elucidate the issue of real-time visibility of the entire system. This paper presents a novel co-optimized placement strategy of µPMUs (CPMP) in PDNs that minimizes the µPMU numbers and the estimation error in the buses other than the µPMU assigned nodes. This work also displays a novel dynamic heuristic distribution system state estimation (DDSSE) to estimate the system's unknown states by using only the information of bus voltage phasors at the µPMU specified buses. The DDSSE is used to estimate the root mean square error (RMSE) in estimated voltage magnitudes and angles. Besides this, the efficacy of the grey-wolf optimizer (GWO) is presented in this work to solve the newly formulated placement problem. The results are validated on an Indian 19-bus and 34-bus unbalanced radial distribution system (URDS), and a detailed comparative study of different heuristic algorithms is also analyzed in this work.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.